diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..bee181164ee09dfb96fa71ed6cfb9d63d50a1d68
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_cachemask_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_channel_affine_cachemask_out(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_channel_affine_cachemask(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3a918173b1fe0aadebe2d77c28e658e8c879ac7a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fake_quantize_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.h
new file mode 100644
index 0000000000000000000000000000000000000000..090b3728f9ae0f487a59ddf948161f462713f2be
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine.h
@@ -0,0 +1,35 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fake_quantize_per_tensor_affine_ops.h>
+
+namespace at {
+
+
+// aten::fake_quantize_per_tensor_affine(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> Tensor
+inline at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) {
+    return at::_ops::fake_quantize_per_tensor_affine::call(self, scale, zero_point, quant_min, quant_max);
+}
+
+// aten::fake_quantize_per_tensor_affine.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max) -> Tensor
+inline at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max) {
+    return at::_ops::fake_quantize_per_tensor_affine_tensor_qparams::call(self, scale, zero_point, quant_min, quant_max);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask.h
new file mode 100644
index 0000000000000000000000000000000000000000..3de21f778747b101da67b6e32d43475583ffb485
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fake_quantize_per_tensor_affine_cachemask_ops.h>
+
+namespace at {
+
+
+// aten::fake_quantize_per_tensor_affine_cachemask(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor output, Tensor mask)
+inline ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) {
+    return at::_ops::fake_quantize_per_tensor_affine_cachemask::call(self, scale, zero_point, quant_min, quant_max);
+}
+
+// aten::fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) {
+    return at::_ops::fake_quantize_per_tensor_affine_cachemask_out::call(self, scale, zero_point, quant_min, quant_max, out0, out1);
+}
+// aten::fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_outf(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) {
+    return at::_ops::fake_quantize_per_tensor_affine_cachemask_out::call(self, scale, zero_point, quant_min, quant_max, out0, out1);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..1d1889c075f55e40e95a1ab5180576d7505afbba
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fake_quantize_per_tensor_affine_cachemask_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fake_quantize_per_tensor_affine_cachemask_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fake_quantize_per_tensor_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad, const at::Tensor & mask);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & mask);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3310acd1e66c10882f73cf15bf4252593c17cbc1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_outf(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..6b03e7111b705181620fb17378a8ebec5afebfcb
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_cachemask_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_out(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fd92f267b467ec3b7cac5677725345c41d90cb5a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..5cdb7be53f564fa46254e09e26caa0fe96b129f8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+TORCH_API at::Tensor fake_quantize_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..8b09b103c04a4d48cb12d61f83c7956086aeaf44
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fake_quantize_per_tensor_affine_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fake_quantize_per_tensor_affine {
+  using schema = at::Tensor (const at::Tensor &, double, int64_t, int64_t, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fake_quantize_per_tensor_affine";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fake_quantize_per_tensor_affine(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max);
+};
+
+struct TORCH_API fake_quantize_per_tensor_affine_tensor_qparams {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fake_quantize_per_tensor_affine";
+  static constexpr const char* overload_name = "tensor_qparams";
+  static constexpr const char* schema_str = "fake_quantize_per_tensor_affine.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight.h
new file mode 100644
index 0000000000000000000000000000000000000000..78084d5d33103757cf28971f36a91cbf2b98cd61
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_linear_fp16_weight_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor
+inline at::Tensor fbgemm_linear_fp16_weight(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias) {
+    return at::_ops::fbgemm_linear_fp16_weight::call(input, packed_weight, bias);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8c145586f9822f499a95baaf52082c2dfa410921
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_linear_fp16_weight(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation.h
new file mode 100644
index 0000000000000000000000000000000000000000..8cd9d5832e06e2945ccd668ce7fbdde559af1470
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_linear_fp16_weight_fp32_activation(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor
+inline at::Tensor fbgemm_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias) {
+    return at::_ops::fbgemm_linear_fp16_weight_fp32_activation::call(input, packed_weight, bias);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..20a7f4db77c793f6fd673f1a7248b9e9cea7f4d1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..78cf2b93526e5b1d604996322738a4d029966800
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..2c0f38c8e1df9d63071d697d9cf6cf4248fc669e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_fp32_activation_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_linear_fp16_weight_fp32_activation {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_linear_fp16_weight_fp32_activation";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_linear_fp16_weight_fp32_activation(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..e509994bb449b4a1ca7a246e86cc1eead8c344c6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_linear_fp16_weight(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..4a7006074ace4b53e4152c053604d9a83a39cc2b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_fp16_weight_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_linear_fp16_weight {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_linear_fp16_weight";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h
new file mode 100644
index 0000000000000000000000000000000000000000..932db4f7adc8070d4b3253aaae92613aaa5243b7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_linear_int8_weight_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_linear_int8_weight(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor
+inline at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias) {
+    return at::_ops::fbgemm_linear_int8_weight::call(input, weight, packed, col_offsets, weight_scale, weight_zero_point, bias);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..92420e3c34efc509ea881207be885c5d4a80d65a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.h
new file mode 100644
index 0000000000000000000000000000000000000000..d03ca3a4725ef966cf3331ee3e5e9629d0679bb1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_linear_int8_weight_fp32_activation_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_linear_int8_weight_fp32_activation(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor
+inline at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias) {
+    return at::_ops::fbgemm_linear_int8_weight_fp32_activation::call(input, weight, packed, col_offsets, weight_scale, weight_zero_point, bias);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2d66e8b04e5db132e860f74d59aad7a4b8ff4106
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..096759cb15971990ef7420d05c33d0bc79d71ce3
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..3e1c701a7df01eefc422975a9912ade387afdd27
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_fp32_activation_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_linear_int8_weight_fp32_activation {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_linear_int8_weight_fp32_activation";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_linear_int8_weight_fp32_activation(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..65a4fed52b797d1456abe5dd7e028e46fe6ca369
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..479f4c38d709290949c1ef940623db5483870a53
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_int8_weight_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_linear_int8_weight {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_linear_int8_weight";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_linear_int8_weight(Tensor input, Tensor weight, Tensor packed, Tensor col_offsets, Scalar weight_scale, Scalar weight_zero_point, Tensor bias) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h
new file mode 100644
index 0000000000000000000000000000000000000000..8b4502b428df0462747d517c94bb536183e598fd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_linear_quantize_weight_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int)
+inline ::std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight(const at::Tensor & input) {
+    return at::_ops::fbgemm_linear_quantize_weight::call(input);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a44bb97fa48c6db6501faa7b9f506c81b1d128b9
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight(const at::Tensor & input);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..7e8ea939412cd7dad9d3bd3035e6f6dca959b370
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight(const at::Tensor & input);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..7dfe49713c2620644acad567443e2cb841681dd2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_linear_quantize_weight_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_linear_quantize_weight {
+  using schema = ::std::tuple<at::Tensor,at::Tensor,double,int64_t> (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_linear_quantize_weight";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int)";
+  static ::std::tuple<at::Tensor,at::Tensor,double,int64_t> call(const at::Tensor & input);
+  static ::std::tuple<at::Tensor,at::Tensor,double,int64_t> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16.h
new file mode 100644
index 0000000000000000000000000000000000000000..c7c5e28f5dc2d4f70b5bdbb608987809f715d71d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_pack_gemm_matrix_fp16_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor
+inline at::Tensor fbgemm_pack_gemm_matrix_fp16(const at::Tensor & input) {
+    return at::_ops::fbgemm_pack_gemm_matrix_fp16::call(input);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..cd9ab325220f69f555ad9807b15208e62ebf16a0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_pack_gemm_matrix_fp16(const at::Tensor & input);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..223b3a6da47184c5f100ed84500bd7322e2230d8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_pack_gemm_matrix_fp16(const at::Tensor & input);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..c825f5a218bc98a9fb4e7585b8bd4a5df5fbb6a4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_gemm_matrix_fp16_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_pack_gemm_matrix_fp16 {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_pack_gemm_matrix_fp16";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor";
+  static at::Tensor call(const at::Tensor & input);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix.h
new file mode 100644
index 0000000000000000000000000000000000000000..c29de80b3a63042b52f6b8c7baa9539c919244f8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix.h
@@ -0,0 +1,35 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fbgemm_pack_quantized_matrix_ops.h>
+
+namespace at {
+
+
+// aten::fbgemm_pack_quantized_matrix(Tensor input) -> Tensor
+inline at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input) {
+    return at::_ops::fbgemm_pack_quantized_matrix::call(input);
+}
+
+// aten::fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor
+inline at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input, int64_t K, int64_t N) {
+    return at::_ops::fbgemm_pack_quantized_matrix_KN::call(input, K, N);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..59c0b33958f224a4254e38e4b94db8e831990539
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input);
+TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input, int64_t K, int64_t N);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..5695942bfb45f85fc256242c0262c43be1b2af04
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input);
+TORCH_API at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input, int64_t K, int64_t N);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..afc73ad95222c2bb851f022c4a475e4e75ad8dba
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fbgemm_pack_quantized_matrix_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fbgemm_pack_quantized_matrix {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_pack_quantized_matrix";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fbgemm_pack_quantized_matrix(Tensor input) -> Tensor";
+  static at::Tensor call(const at::Tensor & input);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input);
+};
+
+struct TORCH_API fbgemm_pack_quantized_matrix_KN {
+  using schema = at::Tensor (const at::Tensor &, int64_t, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fbgemm_pack_quantized_matrix";
+  static constexpr const char* overload_name = "KN";
+  static constexpr const char* schema_str = "fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, int64_t K, int64_t N);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t K, int64_t N);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h
new file mode 100644
index 0000000000000000000000000000000000000000..13e1ea8d3a1f3c0ed65735eae424b098fd18bf91
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout.h
@@ -0,0 +1,35 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/feature_alpha_dropout_ops.h>
+
+namespace at {
+
+
+// aten::feature_alpha_dropout(Tensor input, float p, bool train) -> Tensor
+inline at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train) {
+    return at::_ops::feature_alpha_dropout::call(input, p, train);
+}
+
+// aten::feature_alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)
+inline at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train) {
+    return at::_ops::feature_alpha_dropout_::call(self, p, train);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..29cdd6392e00467bc08f0fac60061e91d980664b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train);
+TORCH_API at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8ab6513a95257a61d345ba58efd4e93766bb4866
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train);
+TORCH_API at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..8a19e7e94f040e364d1a1e3fddc9c7541b4169f6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_alpha_dropout_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API feature_alpha_dropout {
+  using schema = at::Tensor (const at::Tensor &, double, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::feature_alpha_dropout";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "feature_alpha_dropout(Tensor input, float p, bool train) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, double p, bool train);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, bool train);
+};
+
+struct TORCH_API feature_alpha_dropout_ {
+  using schema = at::Tensor & (at::Tensor &, double, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::feature_alpha_dropout_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "feature_alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, double p, bool train);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, bool train);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout.h
new file mode 100644
index 0000000000000000000000000000000000000000..96ab123bf5cfecd9f71512c56c7aa82c9a660c53
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout.h
@@ -0,0 +1,35 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/feature_dropout_ops.h>
+
+namespace at {
+
+
+// aten::feature_dropout(Tensor input, float p, bool train) -> Tensor
+inline at::Tensor feature_dropout(const at::Tensor & input, double p, bool train) {
+    return at::_ops::feature_dropout::call(input, p, train);
+}
+
+// aten::feature_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)
+inline at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train) {
+    return at::_ops::feature_dropout_::call(self, p, train);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1a3ca662b32ffec219e226c197e8ec207fa117bc
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor feature_dropout(const at::Tensor & input, double p, bool train);
+TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..df6dc55c53ed3a09d622546e59496f1a196cd921
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor feature_dropout(const at::Tensor & input, double p, bool train);
+TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..d5c05cef7111db3081372dff4e3c8cd4fe113e48
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/feature_dropout_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API feature_dropout {
+  using schema = at::Tensor (const at::Tensor &, double, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::feature_dropout";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "feature_dropout(Tensor input, float p, bool train) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, double p, bool train);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, bool train);
+};
+
+struct TORCH_API feature_dropout_ {
+  using schema = at::Tensor & (at::Tensor &, double, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::feature_dropout_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "feature_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, double p, bool train);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, bool train);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft.h
new file mode 100644
index 0000000000000000000000000000000000000000..0bc872e2d2a4a2ebfe13bf438a5573bb05e27e1e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft.h
@@ -0,0 +1,91 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_fft_ops.h>
+
+namespace at {
+
+
+// aten::fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor
+inline at::Tensor fft_fft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor fft_fft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm);
+  }
+}
+
+// aten::fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor
+inline at::Tensor fft_fft_symint(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft::call(self, n, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor fft_fft(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft::call(self, n, dim, norm);
+  }
+}
+
+// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft_out::call(self, n, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft_out::call(self, n, dim, norm, out);
+  }
+}
+
+// aten::fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft_symint_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft_out::call(self, n, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft_out::call(self, n, dim, norm, out);
+  }
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2.h
new file mode 100644
index 0000000000000000000000000000000000000000..ccab51d208c639ee3b6ef7af767f6567cc19b2a0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2.h
@@ -0,0 +1,91 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_fft2_ops.h>
+
+namespace at {
+
+
+// aten::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor
+inline at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+  }
+}
+
+// aten::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor
+inline at::Tensor fft_fft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2::call(self, s, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor fft_fft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2::call(self, s, dim, norm);
+  }
+}
+
+// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fft2_out::call(self, s, dim, norm, out);
+  }
+}
+
+// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft2_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fft2_out::call(self, s, dim, norm, out);
+  }
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e27e16e9472317ddcb815f429f12b7711655b7f7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,28 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor fft_fft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+TORCH_API at::Tensor & fft_fft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c09ecd5e225a0c70515702be1d8353ecfa67f21d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_fft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ba46e2752f25b7db07c89386a3a49c0d78826150
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft2_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fft_fft2 {
+  using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional<c10::string_view>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fft2";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm);
+};
+
+struct TORCH_API fft_fft2_out {
+  using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::IntArrayRef, ::std::optional<c10::string_view>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fft2";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..845e5ad621989dbf896ce048631b0089d91ab3ee
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,28 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_fft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor fft_fft_symint(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+TORCH_API at::Tensor & fft_fft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft_symint_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..72d56374ffc414c29133e7809cb5c9bdcee8b515
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_fft_symint(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fft_symint_out(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..b6e3986b1634ee2f4c5dfd783be46d401ede9e1e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fft_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fft_fft {
+  using schema = at::Tensor (const at::Tensor &, ::std::optional<c10::SymInt>, int64_t, ::std::optional<c10::string_view>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fft";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fft_fft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm);
+};
+
+struct TORCH_API fft_fft_out {
+  using schema = at::Tensor & (const at::Tensor &, ::std::optional<c10::SymInt>, int64_t, ::std::optional<c10::string_view>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fft";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fft_fft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h
new file mode 100644
index 0000000000000000000000000000000000000000..bf9b64442bed66d352f4946f779453c6212a0572
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq.h
@@ -0,0 +1,43 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_fftfreq_ops.h>
+
+namespace at {
+
+
+// aten::fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor fft_fftfreq(int64_t n, double d=1.0, at::TensorOptions options={}) {
+    return at::_ops::fft_fftfreq::call(n, d, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor fft_fftfreq(int64_t n, double d, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::fft_fftfreq::call(n, d, dtype, layout, device, pin_memory);
+}
+
+// aten::fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftfreq_out(at::Tensor & out, int64_t n, double d=1.0) {
+    return at::_ops::fft_fftfreq_out::call(n, d, out);
+}
+// aten::fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftfreq_outf(int64_t n, double d, at::Tensor & out) {
+    return at::_ops::fft_fftfreq_out::call(n, d, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9aadeecda67b12059dd3e118530adc6a6bb1e207
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor fft_fftfreq(int64_t n, double d=1.0, at::TensorOptions options={});
+TORCH_API at::Tensor fft_fftfreq(int64_t n, double d, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & fft_fftfreq_out(at::Tensor & out, int64_t n, double d=1.0);
+TORCH_API at::Tensor & fft_fftfreq_outf(int64_t n, double d, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..5fc19cf4611b5159c4c7ebcd286084feb91529e7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_fftfreq(int64_t n, double d=1.0, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & fft_fftfreq_out(int64_t n, double d, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..19f3e6da9efcae6b16a07bf5e529c9a91230c301
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftfreq_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fft_fftfreq {
+  using schema = at::Tensor (int64_t, double, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fftfreq";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fft_fftfreq(int n, float d=1.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t n, double d, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API fft_fftfreq_out {
+  using schema = at::Tensor & (int64_t, double, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fftfreq";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fft_fftfreq.out(int n, float d=1.0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t n, double d, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, double d, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn.h
new file mode 100644
index 0000000000000000000000000000000000000000..64df4d2ac781466b8368887d378ef5fc7b340e42
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn.h
@@ -0,0 +1,91 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_fftn_ops.h>
+
+namespace at {
+
+
+// aten::fft_fftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor
+inline at::Tensor fft_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor fft_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+  }
+}
+
+// aten::fft_fftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor
+inline at::Tensor fft_fftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn::call(self, s, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor fft_fftn(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn::call(self, s, dim, norm);
+  }
+}
+
+// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fftn_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_fftn_out::call(self, s, dim, norm, out);
+  }
+}
+
+// aten::fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_fftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fftn_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_fftn_out::call(self, s, dim, norm, out);
+  }
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8f4bfdbdadb28eb49b8675e634447c9af741dfee
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,28 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_fftn(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor fft_fftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fftn_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fftn_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+TORCH_API at::Tensor & fft_fftn_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fftn_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c83daa0ad8fe72c47f314a7309a4fcf774bc105f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_fftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::OptionalIntArrayRef dim=::std::nullopt, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_fftn_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..b57c69a66285bdc00381675711cf201334d545fc
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftn_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fft_fftn {
+  using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional<c10::string_view>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fftn";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fft_fftn(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm);
+};
+
+struct TORCH_API fft_fftn_out {
+  using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, at::OptionalIntArrayRef, ::std::optional<c10::string_view>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_fftn";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fft_fftn.out(Tensor self, SymInt[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift.h
new file mode 100644
index 0000000000000000000000000000000000000000..bcc1e0a9cd3492410765b3459a958571e7f0684a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_fftshift_ops.h>
+
+namespace at {
+
+
+// aten::fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor
+inline at::Tensor fft_fftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt) {
+    return at::_ops::fft_fftshift::call(self, dim);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..32cc58634dd657ea29c3930196eca9280593f10a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_fftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..521bac0cbd22fbf0c39cbdfc7d9f7842bc0ce53b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_fftshift_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_fftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft.h
new file mode 100644
index 0000000000000000000000000000000000000000..54c1c769997e95dbbeeb6dd2ab81d6db8b886082
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft.h
@@ -0,0 +1,91 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_hfft_ops.h>
+
+namespace at {
+
+
+// aten::fft_hfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor
+inline at::Tensor fft_hfft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor fft_hfft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm);
+  }
+}
+
+// aten::fft_hfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor
+inline at::Tensor fft_hfft_symint(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft::call(self, n, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor fft_hfft(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft::call(self, n, dim, norm);
+  }
+}
+
+// aten::fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_hfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_hfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_hfft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_hfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & fft_hfft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_hfft_out::call(self, n.has_value() ? ::std::make_optional(c10::SymInt(*n)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_hfft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft_out::call(self, n, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_hfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft_out::call(self, n, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fft_hfft_symint_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_hfft_out::call(self, n, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & fft_hfft_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out) {
+    return at::_ops::fft_hfft_out::call(self, n, dim, norm, out);
+  }
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2.h
new file mode 100644
index 0000000000000000000000000000000000000000..ccf1d634853d2b870268d236ac2046218c3d3d8d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2.h
@@ -0,0 +1,91 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fft_hfft2_ops.h>
+
+namespace at {
+
+
+// aten::fft_hfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor
+inline at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm);
+  }
+}
+
+// aten::fft_hfft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor
+inline at::Tensor fft_hfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2::call(self, s, dim, norm);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2::call(self, s, dim, norm);
+  }
+}
+
+// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out) {
+    return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out) {
+    return at::_ops::fft_hfft2_out::call(self, s.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*s)) : ::std::nullopt, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline const at::Tensor & fft_hfft2_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt) {
+    return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out);
+  }
+}
+
+// aten::fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
+inline const at::Tensor & fft_hfft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out) {
+    return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out) {
+    return at::_ops::fft_hfft2_out::call(self, s, dim, norm, out);
+  }
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0f9f64565a01a8cde80ce6b519d8e38dd190e60d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,28 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_hfft2(const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor fft_hfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API const at::Tensor & fft_hfft2_out(const at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API const at::Tensor & fft_hfft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out);
+TORCH_API const at::Tensor & fft_hfft2_symint_out(const at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API const at::Tensor & fft_hfft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..5cdafd3e1c597bd50bcf8ed4c5c3d5ddb5b4f36e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft2_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fft_hfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=::std::nullopt, at::IntArrayRef dim={-2,-1}, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API const at::Tensor & fft_hfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, ::std::optional<c10::string_view> norm, const at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5f466fabe8f1ca1397c30badbf54fb199e9ca957
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,28 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fft_hfft(const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor fft_hfft_symint(const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_hfft_out(at::Tensor & out, const at::Tensor & self, ::std::optional<int64_t> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_hfft_outf(const at::Tensor & self, ::std::optional<int64_t> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+TORCH_API at::Tensor & fft_hfft_symint_out(at::Tensor & out, const at::Tensor & self, ::std::optional<c10::SymInt> n=::std::nullopt, int64_t dim=-1, ::std::optional<c10::string_view> norm=::std::nullopt);
+TORCH_API at::Tensor & fft_hfft_symint_outf(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..cbe2fab078b584210b71678a75d7847ce82ff2ab
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fft_hfft_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fft_hfft {
+  using schema = at::Tensor (const at::Tensor &, ::std::optional<c10::SymInt>, int64_t, ::std::optional<c10::string_view>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_hfft";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fft_hfft(Tensor self, SymInt? n=None, int dim=-1, str? norm=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm);
+};
+
+struct TORCH_API fft_hfft_out {
+  using schema = at::Tensor & (const at::Tensor &, ::std::optional<c10::SymInt>, int64_t, ::std::optional<c10::string_view>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fft_hfft";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fft_hfft.out(Tensor self, SymInt? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<c10::SymInt> n, int64_t dim, ::std::optional<c10::string_view> norm, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e63589bdf51dba98604c69c8258d76c592bb09c2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flip_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API flip {
+  using schema = at::Tensor (const at::Tensor &, at::IntArrayRef);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::flip";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "flip(Tensor self, int[] dims) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::IntArrayRef dims);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims);
+};
+
+struct TORCH_API flip_out {
+  using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::flip";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "flip.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e887daab391a3a1b4946f203502101379559ed33
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/flipud_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API flipud {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::flipud";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "flipud(Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power.h
new file mode 100644
index 0000000000000000000000000000000000000000..3170a58728b0becacc976c630a8232b216b47bbb
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power.h
@@ -0,0 +1,67 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/float_power_ops.h>
+
+namespace at {
+
+
+// aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent) {
+    return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out);
+}
+// aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) {
+    return at::_ops::float_power_Tensor_Tensor_out::call(self, exponent, out);
+}
+
+// aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor
+inline at::Tensor float_power(const at::Tensor & self, const at::Tensor & exponent) {
+    return at::_ops::float_power_Tensor_Tensor::call(self, exponent);
+}
+
+// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent) {
+    return at::_ops::float_power_Scalar_out::call(self, exponent, out);
+}
+// aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) {
+    return at::_ops::float_power_Scalar_out::call(self, exponent, out);
+}
+
+// aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor
+inline at::Tensor float_power(const at::Scalar & self, const at::Tensor & exponent) {
+    return at::_ops::float_power_Scalar::call(self, exponent);
+}
+
+// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent) {
+    return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out);
+}
+// aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & float_power_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) {
+    return at::_ops::float_power_Tensor_Scalar_out::call(self, exponent, out);
+}
+
+// aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor
+inline at::Tensor float_power(const at::Tensor & self, const at::Scalar & exponent) {
+    return at::_ops::float_power_Tensor_Scalar::call(self, exponent);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..4c6144c97749766aacbe55a450887cb804ea4c61
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/float_power_ops.h
@@ -0,0 +1,105 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API float_power_Tensor_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Tensor_Tensor_out";
+  static constexpr const char* schema_str = "float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out);
+};
+
+struct TORCH_API float_power_Tensor_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Tensor_Tensor";
+  static constexpr const char* schema_str = "float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & exponent);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent);
+};
+
+struct TORCH_API float_power_Scalar_out {
+  using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out);
+};
+
+struct TORCH_API float_power_Scalar {
+  using schema = at::Tensor (const at::Scalar &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "float_power.Scalar(Scalar self, Tensor exponent) -> Tensor";
+  static at::Tensor call(const at::Scalar & self, const at::Tensor & exponent);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent);
+};
+
+struct TORCH_API float_power_Tensor_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Tensor_Scalar_out";
+  static constexpr const char* schema_str = "float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out);
+};
+
+struct TORCH_API float_power_Tensor_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power";
+  static constexpr const char* overload_name = "Tensor_Scalar";
+  static constexpr const char* schema_str = "float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & exponent);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent);
+};
+
+struct TORCH_API float_power__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & exponent);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & exponent);
+};
+
+struct TORCH_API float_power__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::float_power_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & exponent);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & exponent);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h
new file mode 100644
index 0000000000000000000000000000000000000000..fc85edd89744f261cac5beb3772479adce61a23c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/floor_ops.h>
+
+namespace at {
+
+
+// aten::floor(Tensor self) -> Tensor
+inline at::Tensor floor(const at::Tensor & self) {
+    return at::_ops::floor::call(self);
+}
+
+// aten::floor_(Tensor(a!) self) -> Tensor(a!)
+inline at::Tensor & floor_(at::Tensor & self) {
+    return at::_ops::floor_::call(self);
+}
+
+// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::floor_out::call(self, out);
+}
+// aten::floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::floor_out::call(self, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..add8e67dd2cfc29ef7a6533c46619132417d4aac
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor floor(const at::Tensor & self);
+TORCH_API at::Tensor & floor_(at::Tensor & self);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9b5a7a81f6ff35e83040c8a006e13cfb61b236f3
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor floor(const at::Tensor & self);
+TORCH_API at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & floor_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..28541d74214abc405ba8655c6a0c6f16ac0b3df4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor floor(const at::Tensor & self);
+TORCH_API at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & floor_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h
new file mode 100644
index 0000000000000000000000000000000000000000..ff24dcdff97978e09bbbc82dd9c3fdac4ce247fb
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/floor_divide_ops.h>
+
+namespace at {
+
+
+// aten::floor_divide(Tensor self, Tensor other) -> Tensor
+inline at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::floor_divide::call(self, other);
+}
+
+// aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::floor_divide_out::call(self, other, out);
+}
+// aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::floor_divide_out::call(self, other, out);
+}
+
+// aten::floor_divide.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::floor_divide_Scalar::call(self, other);
+}
+
+// aten::floor_divide.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::floor_divide_Scalar_out::call(self, other, out);
+}
+// aten::floor_divide.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::floor_divide_Scalar_out::call(self, other, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2fe850e86c4bcbf6cae16477de5719c2e7e7cfd9
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Scalar & other);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7090885b67804b4a1aab60661260a7bf6c4ddba4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..df88be22fdad5e1a25076febd2a72810fb6dab06
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..73aa1ed5a954297106af6832677d047638b5b990
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_meta_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..692e1180d04ebd4c7be7a89bc26e823a1d656ccc
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_native.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor floor_divide_sparse(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & floor_divide_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_sparse_(at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & floor_divide_Scalar_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Scalar & other);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ee6c99fb77c6a4338b132eccef39339b5764336f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_divide_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API floor_divide {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "floor_divide(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API floor_divide__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "floor_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API floor_divide_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API floor_divide_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "floor_divide.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API floor_divide__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "floor_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API floor_divide_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_divide";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "floor_divide.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..b919014fcce1041549e5e85662cf4cfcfb6814db
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_floor : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..058fdbb796fc12e1238b3a76ade4575504b0f0f0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor floor(const at::Tensor & self);
+TORCH_API at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & floor_(at::Tensor & self);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..bcc949dab627526156e9513e07d68b05fc9f1b74
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_native.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/floor_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_floor_out : public at::meta::structured_floor {
+void impl(const at::Tensor & self, const at::Tensor & out);
+};
+TORCH_API at::Tensor floor_sparse(const at::Tensor & self);
+TORCH_API at::Tensor & floor_sparse_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & floor_sparse_(at::Tensor & self);
+TORCH_API at::Tensor floor_sparse_csr(const at::Tensor & self);
+TORCH_API at::Tensor & floor_sparse_csr_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & floor_sparse_csr_(at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..b9e861a6661dcd77f00e105bacfcfa499f02e495
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/floor_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API floor {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "floor(Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+struct TORCH_API floor_ {
+  using schema = at::Tensor & (at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "floor_(Tensor(a!) self) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self);
+};
+
+struct TORCH_API floor_out {
+  using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::floor";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "floor.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.h
new file mode 100644
index 0000000000000000000000000000000000000000..6a6cbd71a01126c467a667d2d845c9a01751e164
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fmax_ops.h>
+
+namespace at {
+
+
+// aten::fmax(Tensor self, Tensor other) -> Tensor
+inline at::Tensor fmax(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmax::call(self, other);
+}
+
+// aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmax_out::call(self, other, out);
+}
+// aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::fmax_out::call(self, other, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9b539c92c5ead61c9c46e99e6041436f7aa24eb8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ecc15bf7ab06a46aa2e290a333d93d0d41671a92
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..97054aebdf2a440f0f51abf4f003663fc6d05c32
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..20492b854dc7970c97060c4e362b5967f98efd18
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fmax : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1c51ba2002c4422ab5f3279397efb82e76e312ad
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..772b90b546a0e86e240c393b70e490b11e4a6598
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fmax_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_fmax_out : public at::meta::structured_fmax {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..9d1cbfdb30f1dfaad12588847ec1481e3188d648
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmax_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fmax {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmax";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fmax(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API fmax_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmax";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin.h
new file mode 100644
index 0000000000000000000000000000000000000000..51bdbb26702b1f9a33e87f305a5f33c62aa460be
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fmin_ops.h>
+
+namespace at {
+
+
+// aten::fmin(Tensor self, Tensor other) -> Tensor
+inline at::Tensor fmin(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmin::call(self, other);
+}
+
+// aten::fmin.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmin_out::call(self, other, out);
+}
+// aten::fmin.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::fmin_out::call(self, other, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c237d8d482305ff2bdf607e5a9e8af4da5ccd98b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2704b39f184b620509594d67052fd03f9fd20663
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..eda5c345f10a9c5bb46a14776d6dd40805928803
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..059748dc1f2956d48c8e23b354226fa9801613da
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fmin : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b7c1a54fe39fcfd062131299d3fc28a37372cd6a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..18c13c80e42b10f9de979fbf0ff5af4a921ae409
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fmin_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_fmin_out : public at::meta::structured_fmin {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..7b67ec14d1ed4d015a3a457e014ac467680ed09d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmin_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fmin {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmin";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fmin(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API fmin_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmin";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "fmin.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod.h
new file mode 100644
index 0000000000000000000000000000000000000000..72e2c36d87c288d983baec0d67d233a45a2b905e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fmod_ops.h>
+
+namespace at {
+
+
+// aten::fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::fmod_Scalar_out::call(self, other, out);
+}
+// aten::fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmod_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::fmod_Scalar_out::call(self, other, out);
+}
+
+// aten::fmod.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor fmod(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::fmod_Scalar::call(self, other);
+}
+
+// aten::fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmod_Tensor_out::call(self, other, out);
+}
+// aten::fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::fmod_Tensor_out::call(self, other, out);
+}
+
+// aten::fmod.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor fmod(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::fmod_Tensor::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e5842c4a4bc52301f61dc685e316efc068e63f5d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Scalar & other);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a93af795ba6130deb5c016110ec8d823fe028b72
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..03558b958e83967b5274d3bb50d298a5869265ba
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e910d990f42b6cbcf29f9505cd8b2e8bc06a8463
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..e57dfa88967bb36f4fec4750c3e6fa9d1e9a5f1c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fmod_Tensor : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d785c97d7d639e4db2843e430e711b2d45efb6ec
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..43aeea62323226f94fed66a1271aaaf81ebd6137
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fmod_meta.h>
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & fmod_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Scalar & other);
+struct TORCH_API structured_fmod_out : public at::meta::structured_fmod_Tensor {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..cadcf00abe1d08486627aa2159361f0a5a34aaf7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fmod_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fmod_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+struct TORCH_API fmod_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "fmod.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API fmod__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API fmod_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API fmod_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "fmod.Tensor(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API fmod__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fmod_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac.h
new file mode 100644
index 0000000000000000000000000000000000000000..7cbec262d076a6770f63aac05c15a99c5f71a757
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/frac_ops.h>
+
+namespace at {
+
+
+// aten::frac(Tensor self) -> Tensor
+inline at::Tensor frac(const at::Tensor & self) {
+    return at::_ops::frac::call(self);
+}
+
+// aten::frac_(Tensor(a!) self) -> Tensor(a!)
+inline at::Tensor & frac_(at::Tensor & self) {
+    return at::_ops::frac_::call(self);
+}
+
+// aten::frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::frac_out::call(self, out);
+}
+// aten::frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::frac_out::call(self, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4b77882d7756f03fd5ebf2b73fc5ef0ba0a25b2d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor frac(const at::Tensor & self);
+TORCH_API at::Tensor & frac_(at::Tensor & self);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4252aa4d5b9782e823edad49d0244aa23952698f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor frac(const at::Tensor & self);
+TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & frac_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1145715947f92322b84af159b27065a9398f89b8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor frac(const at::Tensor & self);
+TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & frac_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..d163209720dff7a4df0b4d751e0c8c5a131f8f96
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_frac : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..48ceec3d83c5563c6075c3c55e913287a091e9cf
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor frac(const at::Tensor & self);
+TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & frac_(at::Tensor & self);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..af00a64acc1589b90a7835c95907d03f977bb7fa
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_native.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/frac_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_frac_out : public at::meta::structured_frac {
+void impl(const at::Tensor & self, const at::Tensor & out);
+};
+TORCH_API at::Tensor frac_sparse(const at::Tensor & self);
+TORCH_API at::Tensor & frac_sparse_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & frac_sparse_(at::Tensor & self);
+TORCH_API at::Tensor frac_sparse_csr(const at::Tensor & self);
+TORCH_API at::Tensor & frac_sparse_csr_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & frac_sparse_csr_(at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6256a29564b28d06fe7140156fa2ffa79ea5f79c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frac_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API frac {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frac";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "frac(Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+struct TORCH_API frac_ {
+  using schema = at::Tensor & (at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frac_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "frac_(Tensor(a!) self) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self);
+};
+
+struct TORCH_API frac_out {
+  using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frac";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d.h
new file mode 100644
index 0000000000000000000000000000000000000000..4fde93de0aa829e352544d6df75ee3c83c8408b8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fractional_max_pool2d_ops.h>
+
+namespace at {
+
+
+// aten::fractional_max_pool2d.output(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) {
+    return at::_ops::fractional_max_pool2d_output::call(self, kernel_size, output_size, random_samples, output, indices);
+}
+// aten::fractional_max_pool2d.output(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices) {
+    return at::_ops::fractional_max_pool2d_output::call(self, kernel_size, output_size, random_samples, output, indices);
+}
+
+// aten::fractional_max_pool2d(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) {
+    return at::_ops::fractional_max_pool2d::call(self, kernel_size, output_size, random_samples);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..bdda0855e2205b7cf28744125b55fd0deb9b7e62
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fractional_max_pool2d_backward_ops.h>
+
+namespace at {
+
+
+// aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) {
+    return at::_ops::fractional_max_pool2d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input);
+}
+// aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) {
+    return at::_ops::fractional_max_pool2d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input);
+}
+
+// aten::fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor
+inline at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) {
+    return at::_ops::fractional_max_pool2d_backward::call(grad_output, self, kernel_size, output_size, indices);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..374070e1b1ea9bb9b6b80f73dc9667eec350c48c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..24d179e058031f4970cb95a7ed71fdebaf01e6a4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe10f78d34355d617c659ddce3acc4fb8377d0d1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..82c6a0c27b7401c851dce0d45b182cc171d07466
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fractional_max_pool2d_backward : public at::impl::MetaBase {
+    
+    
+    void meta(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..64561c87b0da88a0458f9b0a07963a82b9da4b23
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..0e84278738443013428d5e1758d213db30d21188
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fractional_max_pool2d_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_fractional_max_pool2d_backward_cpu : public at::meta::structured_fractional_max_pool2d_backward {
+void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_fractional_max_pool2d_backward_cuda : public at::meta::structured_fractional_max_pool2d_backward {
+void impl(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..78009ec8ca6c7e97969a8c80acae315e673e0502
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fractional_max_pool2d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool2d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+};
+
+struct TORCH_API fractional_max_pool2d_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool2d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..bf6f82acb6027a80f801cb557d25a351a87b7f50
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..daedf8e6be2336e1d8f28163c98d9b9c12e0ad2f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e58635d893b27a96dd5cdbacb712f2175ead1f2e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..a0bde9faeffa4cbd265687632a7e24083146f361
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fractional_max_pool2d : public at::impl::MetaBase {
+    
+    
+    void meta(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..72aa13a125e391972648f248c28c4c2c9a3e5da5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..4400198ffa4a79677b63ad12bb7d43506a56c7d1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fractional_max_pool2d_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_fractional_max_pool2d_out_cpu : public at::meta::structured_fractional_max_pool2d {
+void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, const at::Tensor & output, const at::Tensor & indices);
+};
+struct TORCH_API structured_fractional_max_pool2d_out_cuda : public at::meta::structured_fractional_max_pool2d {
+void impl(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, const at::Tensor & output, const at::Tensor & indices);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..3cd5e809006b7818970e34381b1a951296631f94
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool2d_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fractional_max_pool2d_output {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool2d";
+  static constexpr const char* overload_name = "output";
+  static constexpr const char* schema_str = "fractional_max_pool2d.output(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+};
+
+struct TORCH_API fractional_max_pool2d {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool2d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fractional_max_pool2d(Tensor self, int[2] kernel_size, int[2] output_size, Tensor random_samples) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d.h
new file mode 100644
index 0000000000000000000000000000000000000000..bb47270eb38ca5ceb56f2be1b0ccfa4376d4aa79
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fractional_max_pool3d_ops.h>
+
+namespace at {
+
+
+// aten::fractional_max_pool3d.output(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) {
+    return at::_ops::fractional_max_pool3d_output::call(self, kernel_size, output_size, random_samples, output, indices);
+}
+// aten::fractional_max_pool3d.output(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices) {
+    return at::_ops::fractional_max_pool3d_output::call(self, kernel_size, output_size, random_samples, output, indices);
+}
+
+// aten::fractional_max_pool3d(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples) {
+    return at::_ops::fractional_max_pool3d::call(self, kernel_size, output_size, random_samples);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..7eb3a832ff125839d2b26360c5db78d6d57934a8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fractional_max_pool3d_backward_ops.h>
+
+namespace at {
+
+
+// aten::fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & fractional_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) {
+    return at::_ops::fractional_max_pool3d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input);
+}
+// aten::fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & fractional_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) {
+    return at::_ops::fractional_max_pool3d_backward_grad_input::call(grad_output, self, kernel_size, output_size, indices, grad_input);
+}
+
+// aten::fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor
+inline at::Tensor fractional_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) {
+    return at::_ops::fractional_max_pool3d_backward::call(grad_output, self, kernel_size, output_size, indices);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1282e3cfbddbe76d8cd749edb64cb28ed8a0a336
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor fractional_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2481afb3a9c3d918e90d4adb6325664986afbf58
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor fractional_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..4181d812014b906272561a3b8d1ec0bfa46dc561
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_native.h
@@ -0,0 +1,24 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fractional_max_pool3d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_out_cpu(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+TORCH_API at::Tensor fractional_max_pool3d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+TORCH_API at::Tensor & fractional_max_pool3d_backward_out_cuda(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..565812234d40e40d60e0b89101f0f0be0cf49996
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fractional_max_pool3d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool3d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input);
+};
+
+struct TORCH_API fractional_max_pool3d_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool3d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fdf6534cf41bfba0453d57bb3d9c26cc021ab5a7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..02a82c860f24c22aadf10f242d172fdd9bfc2b37
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7ea591768bd37f66e5918f6dd021d352a5cd2941
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..667dce4fc27ff66bfa3a710a9f780a55ccc2a2cb
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta.h
@@ -0,0 +1,239 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_fractional_max_pool3d : public at::impl::MetaBase {
+    
+                template <bool POOLSIZET = false, bool POOLSIZEH = false, bool POOLSIZEW = false, bool OUTPUTT = false, bool OUTPUTH = false, bool OUTPUTW = false, bool NUMBATCH = false, bool NUMPLANES = false, bool INPUTT = false, bool INPUTH = false, bool INPUTW = false>
+                struct TORCH_API precompute_out {
+                    
+                    precompute_out<true, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_poolSizeT(int64_t value) {
+                        static_assert(POOLSIZET == false, "poolSizeT already set");
+                        precompute_out<true, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = value;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, true, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_poolSizeH(int64_t value) {
+                        static_assert(POOLSIZEH == false, "poolSizeH already set");
+                        precompute_out<POOLSIZET, true, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = value;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, true, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_poolSizeW(int64_t value) {
+                        static_assert(POOLSIZEW == false, "poolSizeW already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, true, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = value;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, true, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_outputT(int64_t value) {
+                        static_assert(OUTPUTT == false, "outputT already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, true, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = value;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, true, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_outputH(int64_t value) {
+                        static_assert(OUTPUTH == false, "outputH already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, true, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = value;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, true, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> set_outputW(int64_t value) {
+                        static_assert(OUTPUTW == false, "outputW already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, true, NUMBATCH, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = value;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, true, NUMPLANES, INPUTT, INPUTH, INPUTW> set_numBatch(int64_t value) {
+                        static_assert(NUMBATCH == false, "numBatch already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, true, NUMPLANES, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = value;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, true, INPUTT, INPUTH, INPUTW> set_numPlanes(int64_t value) {
+                        static_assert(NUMPLANES == false, "numPlanes already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, true, INPUTT, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = value;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, true, INPUTH, INPUTW> set_inputT(int64_t value) {
+                        static_assert(INPUTT == false, "inputT already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, true, INPUTH, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = value;
+ret.inputH = this->inputH;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, true, INPUTW> set_inputH(int64_t value) {
+                        static_assert(INPUTH == false, "inputH already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, true, INPUTW> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = value;
+ret.inputW = this->inputW;
+return ret;
+                    }
+                
+
+                    precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, true> set_inputW(int64_t value) {
+                        static_assert(INPUTW == false, "inputW already set");
+                        precompute_out<POOLSIZET, POOLSIZEH, POOLSIZEW, OUTPUTT, OUTPUTH, OUTPUTW, NUMBATCH, NUMPLANES, INPUTT, INPUTH, true> ret;
+ret.poolSizeT = this->poolSizeT;
+ret.poolSizeH = this->poolSizeH;
+ret.poolSizeW = this->poolSizeW;
+ret.outputT = this->outputT;
+ret.outputH = this->outputH;
+ret.outputW = this->outputW;
+ret.numBatch = this->numBatch;
+ret.numPlanes = this->numPlanes;
+ret.inputT = this->inputT;
+ret.inputH = this->inputH;
+ret.inputW = value;
+return ret;
+                    }
+                
+                    int64_t poolSizeT;
+int64_t poolSizeH;
+int64_t poolSizeW;
+int64_t outputT;
+int64_t outputH;
+int64_t outputW;
+int64_t numBatch;
+int64_t numPlanes;
+int64_t inputT;
+int64_t inputH;
+int64_t inputW;
+            };
+    using meta_return_ty = precompute_out <true, true, true, true, true, true, true, true, true, true, true>;
+    meta_return_ty meta(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..aeb1de214d8f99f5a112e2357851093f1f7ee407
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..74bdcde879bdc245c29363d54b2b4e60573c6311
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/fractional_max_pool3d_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_fractional_max_pool3d_out_cpu : public at::meta::structured_fractional_max_pool3d {
+void impl(const at::Tensor & self, int64_t poolSizeT, int64_t poolSizeH, int64_t poolSizeW, int64_t outputT, int64_t outputH, int64_t outputW, const at::Tensor & random_samples, int64_t numBatch, int64_t numPlanes, int64_t inputT, int64_t inputH, int64_t inputW, const at::Tensor & output, const at::Tensor & indices);
+};
+struct TORCH_API structured_fractional_max_pool3d_out_cuda : public at::meta::structured_fractional_max_pool3d {
+void impl(const at::Tensor & self, int64_t poolSizeT, int64_t poolSizeH, int64_t poolSizeW, int64_t outputT, int64_t outputH, int64_t outputW, const at::Tensor & random_samples, int64_t numBatch, int64_t numPlanes, int64_t inputT, int64_t inputH, int64_t inputW, const at::Tensor & output, const at::Tensor & indices);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ec8e50749c81253c4f169c26f4827822733baa39
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fractional_max_pool3d_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fractional_max_pool3d_output {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool3d";
+  static constexpr const char* overload_name = "output";
+  static constexpr const char* schema_str = "fractional_max_pool3d.output(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples, *, Tensor(a!) output, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices);
+};
+
+struct TORCH_API fractional_max_pool3d {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fractional_max_pool3d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fractional_max_pool3d(Tensor self, int[3] kernel_size, int[3] output_size, Tensor random_samples) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp.h
new file mode 100644
index 0000000000000000000000000000000000000000..b1643f7b5fe635dc54e209a33b204c5be7dbffc1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/frexp_ops.h>
+
+namespace at {
+
+
+// aten::frexp.Tensor(Tensor self) -> (Tensor mantissa, Tensor exponent)
+inline ::std::tuple<at::Tensor,at::Tensor> frexp(const at::Tensor & self) {
+    return at::_ops::frexp_Tensor::call(self);
+}
+
+// aten::frexp.Tensor_out(Tensor self, *, Tensor(a!) mantissa, Tensor(b!) exponent) -> (Tensor(a!) mantissa, Tensor(b!) exponent)
+inline ::std::tuple<at::Tensor &,at::Tensor &> frexp_out(at::Tensor & mantissa, at::Tensor & exponent, const at::Tensor & self) {
+    return at::_ops::frexp_Tensor_out::call(self, mantissa, exponent);
+}
+// aten::frexp.Tensor_out(Tensor self, *, Tensor(a!) mantissa, Tensor(b!) exponent) -> (Tensor(a!) mantissa, Tensor(b!) exponent)
+inline ::std::tuple<at::Tensor &,at::Tensor &> frexp_outf(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent) {
+    return at::_ops::frexp_Tensor_out::call(self, mantissa, exponent);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7f23ed030ecac100ae8bc0be877ab6b85a91a3e6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> frexp(const at::Tensor & self);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7e0e57c4b9968c165ef584bb37592a601954d882
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cpu_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> frexp_out(at::Tensor & mantissa, at::Tensor & exponent, const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> frexp_outf(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..110d845cfae8b794b2f9d7fffba44174e57ea6f8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_cuda_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> frexp_out(at::Tensor & mantissa, at::Tensor & exponent, const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> frexp_outf(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..27eac8da1346fb97d0dcc6e3ecd6e4526250dd3e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> frexp(const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> frexp_out(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..eb42a704fbc70369b8e1b8913d515d6919f3d32e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frexp_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API frexp_Tensor {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frexp";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "frexp.Tensor(Tensor self) -> (Tensor mantissa, Tensor exponent)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+struct TORCH_API frexp_Tensor_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frexp";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "frexp.Tensor_out(Tensor self, *, Tensor(a!) mantissa, Tensor(b!) exponent) -> (Tensor(a!) mantissa, Tensor(b!) exponent)";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm.h
new file mode 100644
index 0000000000000000000000000000000000000000..655034eebc5761d1d9bff2ddbdadb82dd829a623
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/frobenius_norm_ops.h>
+
+namespace at {
+
+
+// aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor
+inline at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) {
+    return at::_ops::frobenius_norm_dim::call(self, dim, keepdim);
+}
+
+// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & frobenius_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false) {
+    return at::_ops::frobenius_norm_out::call(self, dim, keepdim, out);
+}
+// aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & frobenius_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) {
+    return at::_ops::frobenius_norm_out::call(self, dim, keepdim, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5ad00b4311a2fadc2c4f5fcfd5223ea427d41fa1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false);
+TORCH_API at::Tensor & frobenius_norm_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false);
+TORCH_API at::Tensor & frobenius_norm_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..a4afd84d9678136255beda99578984648aecf7c2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor frobenius_norm(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false);
+TORCH_API at::Tensor & frobenius_norm_out(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..f11016b710739b224be97c8a15367b4146499cc9
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/frobenius_norm_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API frobenius_norm_dim {
+  using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frobenius_norm";
+  static constexpr const char* overload_name = "dim";
+  static constexpr const char* schema_str = "frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim);
+};
+
+struct TORCH_API frobenius_norm_out {
+  using schema = at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::frobenius_norm";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_blob.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_blob.h
new file mode 100644
index 0000000000000000000000000000000000000000..e82fc4f3e7ab262140e43d7b73c75ec7a9125d81
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_blob.h
@@ -0,0 +1,167 @@
+#pragma once
+#include <ATen/core/Tensor.h>
+
+namespace at {
+
+namespace detail {
+
+TORCH_API inline void noopDelete(void*) {}
+
+} // namespace detail
+
+/// Provides a fluent API to construct tensors from external data.
+///
+/// The fluent API can be used instead of `from_blob` functions in case the
+/// required set of parameters does not align with the existing overloads.
+///
+///     at::Tensor tensor = at::for_blob(data, sizes)
+///             .strides(strides)
+///             .context(context, [](void *ctx) { delete static_cast<Ctx*>(ctx);
+///             }) .options(...) .make_tensor();
+///
+class TORCH_API TensorMaker {
+  friend TensorMaker for_blob(void* data, IntArrayRef sizes) noexcept;
+
+ public:
+  using ContextDeleter = DeleterFnPtr;
+
+  TensorMaker& strides(OptionalIntArrayRef value) noexcept {
+    strides_ = value;
+
+    return *this;
+  }
+
+  TensorMaker& storage_offset(std::optional<int64_t> value) noexcept {
+    storage_offset_ = value;
+
+    return *this;
+  }
+
+  TensorMaker& deleter(std::function<void(void*)> value) noexcept {
+    deleter_ = std::move(value);
+
+    return *this;
+  }
+
+  TensorMaker& context(void* value, ContextDeleter deleter = nullptr) noexcept {
+    ctx_ = std::unique_ptr<void, ContextDeleter>{
+        value, deleter != nullptr ? deleter : detail::noopDelete};
+
+    return *this;
+  }
+
+  TensorMaker& target_device(std::optional<Device> value) noexcept {
+    device_ = value;
+
+    return *this;
+  }
+
+  TensorMaker& options(TensorOptions value) noexcept {
+    opts_ = value;
+
+    return *this;
+  }
+
+  TensorMaker& resizeable_storage() noexcept {
+    resizeable_ = true;
+
+    return *this;
+  }
+
+  TensorMaker& allocator(c10::Allocator* allocator) noexcept {
+    allocator_ = allocator;
+
+    return *this;
+  }
+
+  Tensor make_tensor();
+
+ private:
+  explicit TensorMaker(void* data, IntArrayRef sizes) noexcept
+      : data_{data}, sizes_{sizes} {}
+
+  std::size_t computeStorageSize() const noexcept;
+
+  DataPtr makeDataPtrFromDeleter() noexcept;
+
+  DataPtr makeDataPtrFromContext() noexcept;
+
+  IntArrayRef makeTempSizes() const noexcept;
+
+  void* data_;
+  IntArrayRef sizes_;
+  OptionalIntArrayRef strides_{};
+  std::optional<int64_t> storage_offset_{};
+  std::function<void(void*)> deleter_{};
+  std::unique_ptr<void, ContextDeleter> ctx_{nullptr, detail::noopDelete};
+  std::optional<Device> device_{};
+  TensorOptions opts_{};
+  bool resizeable_{};
+  c10::Allocator* allocator_{};
+};
+
+inline TensorMaker for_blob(void* data, IntArrayRef sizes) noexcept {
+  return TensorMaker{data, sizes};
+}
+
+inline Tensor from_blob(
+    void* data,
+    IntArrayRef sizes,
+    IntArrayRef strides,
+    const std::function<void(void*)>& deleter,
+    const TensorOptions& options = {},
+    const std::optional<Device> target_device = std::nullopt) {
+  return for_blob(data, sizes)
+      .strides(strides)
+      .deleter(deleter)
+      .options(options)
+      .target_device(target_device)
+      .make_tensor();
+}
+
+inline Tensor from_blob(
+    void* data,
+    IntArrayRef sizes,
+    IntArrayRef strides,
+    int64_t storage_offset,
+    const std::function<void(void*)>& deleter,
+    const TensorOptions& options = {},
+    const std::optional<Device> target_device = std::nullopt) {
+  return for_blob(data, sizes)
+      .strides(strides)
+      .storage_offset(storage_offset)
+      .deleter(deleter)
+      .options(options)
+      .target_device(target_device)
+      .make_tensor();
+}
+
+inline Tensor from_blob(
+    void* data,
+    IntArrayRef sizes,
+    std::function<void(void*)> deleter,
+    const TensorOptions& options = {},
+    const std::optional<Device> target_device = std::nullopt) {
+  return for_blob(data, sizes)
+      .deleter(std::move(deleter))
+      .options(options)
+      .target_device(target_device)
+      .make_tensor();
+}
+
+inline Tensor from_blob(
+    void* data,
+    IntArrayRef sizes,
+    IntArrayRef strides,
+    const TensorOptions& options = {}) {
+  return for_blob(data, sizes).strides(strides).options(options).make_tensor();
+}
+
+inline Tensor from_blob(
+    void* data,
+    IntArrayRef sizes,
+    const TensorOptions& options = {}) {
+  return for_blob(data, sizes).options(options).make_tensor();
+}
+
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file.h
new file mode 100644
index 0000000000000000000000000000000000000000..d7f275ddbd2c026ab51846af3873643b7469a31d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file.h
@@ -0,0 +1,43 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/from_file_ops.h>
+
+namespace at {
+
+
+// aten::from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor from_file(c10::string_view filename, ::std::optional<bool> shared=::std::nullopt, ::std::optional<int64_t> size=0, at::TensorOptions options={}) {
+    return at::_ops::from_file::call(filename, shared, size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor from_file(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::from_file::call(filename, shared, size, dtype, layout, device, pin_memory);
+}
+
+// aten::from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & from_file_out(at::Tensor & out, c10::string_view filename, ::std::optional<bool> shared=::std::nullopt, ::std::optional<int64_t> size=0) {
+    return at::_ops::from_file_out::call(filename, shared, size, out);
+}
+// aten::from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & from_file_outf(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, at::Tensor & out) {
+    return at::_ops::from_file_out::call(filename, shared, size, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3cf1301731c9fb6439c2e6c21a12337e85afc034
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & from_file_out(at::Tensor & out, c10::string_view filename, ::std::optional<bool> shared=::std::nullopt, ::std::optional<int64_t> size=0);
+TORCH_API at::Tensor & from_file_outf(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..965a4716bae88023abe23e8280dd84253618385a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_cpu_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor from_file(c10::string_view filename, ::std::optional<bool> shared=::std::nullopt, ::std::optional<int64_t> size=0, at::TensorOptions options={});
+TORCH_API at::Tensor from_file(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..2b48f31bf1acae54f51ea92d63cd34467f6ea3ec
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & from_file_out(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, at::Tensor & out);
+TORCH_API at::Tensor from_file(c10::string_view filename, ::std::optional<bool> shared=::std::nullopt, ::std::optional<int64_t> size=0, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..b829bf1822eae203d97ca5e30377813b596d9e12
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/from_file_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API from_file {
+  using schema = at::Tensor (c10::string_view, ::std::optional<bool>, ::std::optional<int64_t>, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::from_file";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API from_file_out {
+  using schema = at::Tensor & (c10::string_view, ::std::optional<bool>, ::std::optional<int64_t>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::from_file";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, ::std::optional<bool> shared, ::std::optional<int64_t> size, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full.h
new file mode 100644
index 0000000000000000000000000000000000000000..e7a0660584a4c55470c8bc3a7d9fffbb0350e80f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full.h
@@ -0,0 +1,131 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/full_ops.h>
+
+namespace at {
+
+
+// aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::TensorOptions options={}) {
+    return at::_ops::full_names::call(size, fill_value, names, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::full_names::call(size, fill_value, names, dtype, layout, device, pin_memory);
+}
+
+// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) {
+    return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) {
+    return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+  }
+}
+
+// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, dtype, layout, device, pin_memory);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::full::call(c10::fromIntArrayRefSlow(size), fill_value, dtype, layout, device, pin_memory);
+  }
+}
+
+// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) {
+    return at::_ops::full::call(size, fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor full(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={}) {
+    return at::_ops::full::call(size, fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+  }
+}
+
+// aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::full::call(size, fill_value, dtype, layout, device, pin_memory);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor full(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::full::call(size, fill_value, dtype, layout, device, pin_memory);
+  }
+}
+
+// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value) {
+    return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value) {
+    return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out);
+  }
+}
+
+// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) {
+    return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) {
+    return at::_ops::full_out::call(c10::fromIntArrayRefSlow(size), fill_value, out);
+  }
+}
+
+// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value) {
+    return at::_ops::full_out::call(size, fill_value, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & full_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value) {
+    return at::_ops::full_out::call(size, fill_value, out);
+  }
+}
+
+// aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_symint_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) {
+    return at::_ops::full_out::call(size, fill_value, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & full_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) {
+    return at::_ops::full_out::call(size, fill_value, out);
+  }
+}
+
+// aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names) {
+    return at::_ops::full_names_out::call(size, fill_value, names, out);
+}
+// aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::Tensor & out) {
+    return at::_ops::full_names_out::call(size, fill_value, names, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4d85aa566cec158d40123473ea769e3c5563307e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,34 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::TensorOptions options={});
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names);
+TORCH_API at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::Tensor & out);
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={});
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={});
+TORCH_API at::Tensor full_symint(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value);
+TORCH_API at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
+TORCH_API at::Tensor & full_symint_out(at::Tensor & out, c10::SymIntArrayRef size, const at::Scalar & fill_value);
+TORCH_API at::Tensor & full_symint_outf(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like.h
new file mode 100644
index 0000000000000000000000000000000000000000..05a8d238a8b9f9825bd3bb0a8abbaa8802012b2f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like.h
@@ -0,0 +1,43 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/full_like_ops.h>
+
+namespace at {
+
+
+// aten::full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
+inline at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, at::TensorOptions options={}, ::std::optional<at::MemoryFormat> memory_format=::std::nullopt) {
+    return at::_ops::full_like::call(self, fill_value, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt(), c10::impl::check_tensor_options_and_extract_memory_format(options, memory_format));
+}
+// aten::full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
+inline at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory, ::std::optional<at::MemoryFormat> memory_format) {
+    return at::_ops::full_like::call(self, fill_value, dtype, layout, device, pin_memory, memory_format);
+}
+
+// aten::full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_like_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format=::std::nullopt) {
+    return at::_ops::full_like_out::call(self, fill_value, memory_format, out);
+}
+// aten::full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & full_like_outf(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format, at::Tensor & out) {
+    return at::_ops::full_like_out::call(self, fill_value, memory_format, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d72131e5182de5ff8c56b88c577a6d670c597493
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, at::TensorOptions options={}, ::std::optional<at::MemoryFormat> memory_format=::std::nullopt);
+TORCH_API at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory, ::std::optional<at::MemoryFormat> memory_format);
+TORCH_API at::Tensor & full_like_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format=::std::nullopt);
+TORCH_API at::Tensor & full_like_outf(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..f96db01b810bcf8765f46ab59f577c8d370caecd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={}, ::std::optional<at::MemoryFormat> memory_format=::std::nullopt);
+TORCH_API at::Tensor & full_like_out(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..7fd33b7465a0e8d3c81210adbde21b5e43970208
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_like_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API full_like {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>, ::std::optional<at::MemoryFormat>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full_like";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory, ::std::optional<at::MemoryFormat> memory_format);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory, ::std::optional<at::MemoryFormat> memory_format);
+};
+
+struct TORCH_API full_like_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, ::std::optional<at::MemoryFormat>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full_like";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, ::std::optional<at::MemoryFormat> memory_format, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..2e714be1dea653028f78c0bf47652c23b6d420e5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_native.h
@@ -0,0 +1,24 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & full_names_out(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::Tensor & out);
+TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & full_out(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..87118050f4d36580960e749ec7cfb93731a5c9b4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/full_ops.h
@@ -0,0 +1,61 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API full_names {
+  using schema = at::Tensor (at::IntArrayRef, const at::Scalar &, ::std::optional<at::DimnameList>, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full";
+  static constexpr const char* overload_name = "names";
+  static constexpr const char* schema_str = "full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API full {
+  using schema = at::Tensor (c10::SymIntArrayRef, const at::Scalar &, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API full_out {
+  using schema = at::Tensor & (c10::SymIntArrayRef, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
+};
+
+struct TORCH_API full_names_out {
+  using schema = at::Tensor & (at::IntArrayRef, const at::Scalar &, ::std::optional<at::DimnameList>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::full";
+  static constexpr const char* overload_name = "names_out";
+  static constexpr const char* schema_str = "full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Scalar & fill_value, ::std::optional<at::DimnameList> names, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant.h
new file mode 100644
index 0000000000000000000000000000000000000000..853f512320b0ae162b3a3b73e72e41d6449c4091
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/fused_moving_avg_obs_fake_quant_ops.h>
+
+namespace at {
+
+
+// aten::fused_moving_avg_obs_fake_quant(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> Tensor
+inline at::Tensor fused_moving_avg_obs_fake_quant(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false) {
+    return at::_ops::fused_moving_avg_obs_fake_quant::call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..73f6f25f294c9f12c3835023bf1853237858663f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor fused_moving_avg_obs_fake_quant(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..0cb658f448304ac499dc172673828d9fc674b110
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor fused_moving_avg_obs_fake_quant(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..cf54a0c3ef873872720bf75c773f6b632bd260f1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/fused_moving_avg_obs_fake_quant_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API fused_moving_avg_obs_fake_quant {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, double, int64_t, int64_t, int64_t, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::fused_moving_avg_obs_fake_quant";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "fused_moving_avg_obs_fake_quant(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather.h
new file mode 100644
index 0000000000000000000000000000000000000000..f893171b9cac2068512d259e1dd7c7b04a00f355
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gather_ops.h>
+
+namespace at {
+
+
+// aten::gather.out(Tensor self, int dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false) {
+    return at::_ops::gather_out::call(self, dim, index, sparse_grad, out);
+}
+// aten::gather.out(Tensor self, int dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gather_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out) {
+    return at::_ops::gather_out::call(self, dim, index, sparse_grad, out);
+}
+
+// aten::gather(Tensor self, int dim, Tensor index, *, bool sparse_grad=False) -> Tensor
+inline at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false) {
+    return at::_ops::gather::call(self, dim, index, sparse_grad);
+}
+
+// aten::gather.dimname_out(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false) {
+    return at::_ops::gather_dimname_out::call(self, dim, index, sparse_grad, out);
+}
+// aten::gather.dimname_out(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gather_outf(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out) {
+    return at::_ops::gather_dimname_out::call(self, dim, index, sparse_grad, out);
+}
+
+// aten::gather.dimname(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False) -> Tensor
+inline at::Tensor gather(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false) {
+    return at::_ops::gather_dimname::call(self, dim, index, sparse_grad);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..807f2f4049014d4f7474a616a00d4cb6758981a6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gather_backward_ops.h>
+
+namespace at {
+
+
+// aten::gather_backward(Tensor grad, Tensor self, int dim, Tensor index, bool sparse_grad) -> Tensor
+inline at::Tensor gather_backward(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad) {
+    return at::_ops::gather_backward::call(grad, self, dim, index, sparse_grad);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e011fe80c204dbe15109ae566539ecc9f34f68b1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor gather_backward(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..6845ba21d6849ca01daa0d00a871dac3582f551d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor gather_backward(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..76ad29f53751c073f27b39e22829b77bc8b2e5e8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_backward_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gather_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gather_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gather_backward(Tensor grad, Tensor self, int dim, Tensor index, bool sparse_grad) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e257e0bcbdd5ebb32a2692394de5c899a9d1b8c4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..54e866da05dfb7c5afa762c43ba89342cd12913a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor gather(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_outf(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8b15c129ebe178ce5ed6e1a17b61e2b2aa75bada
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6e65e01b1c738445c82198ed1797ceeb296f4c3f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..c34194699c9659bd3a9cdc487ccec349f2780732
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_gather : public at::impl::MetaBase {
+    
+    
+    void meta(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..828620d2bca938902fd15f1b41be0d003022132b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..51c768ff7b71a6a2b2fa81f8980367e9b8190aa2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_native.h
@@ -0,0 +1,25 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/gather_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_gather_out : public at::meta::structured_gather {
+void impl(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, const at::Tensor & out);
+};
+TORCH_API at::Tensor gather(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad=false);
+TORCH_API at::Tensor & gather_out(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe06750582187e8e29726c75b942e7c0ea557664
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gather_ops.h
@@ -0,0 +1,61 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gather_out {
+  using schema = at::Tensor & (const at::Tensor &, int64_t, const at::Tensor &, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gather";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "gather.out(Tensor self, int dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+};
+
+struct TORCH_API gather {
+  using schema = at::Tensor (const at::Tensor &, int64_t, const at::Tensor &, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gather";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gather(Tensor self, int dim, Tensor index, *, bool sparse_grad=False) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
+};
+
+struct TORCH_API gather_dimname_out {
+  using schema = at::Tensor & (const at::Tensor &, at::Dimname, const at::Tensor &, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gather";
+  static constexpr const char* overload_name = "dimname_out";
+  static constexpr const char* schema_str = "gather.dimname_out(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out);
+};
+
+struct TORCH_API gather_dimname {
+  using schema = at::Tensor (const at::Tensor &, at::Dimname, const at::Tensor &, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gather";
+  static constexpr const char* overload_name = "dimname";
+  static constexpr const char* schema_str = "gather.dimname(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, bool sparse_grad);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd.h
new file mode 100644
index 0000000000000000000000000000000000000000..2b367c7b33053b7eaceaac200068972958fec8ca
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gcd_ops.h>
+
+namespace at {
+
+
+// aten::gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::gcd_out::call(self, other, out);
+}
+// aten::gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::gcd_out::call(self, other, out);
+}
+
+// aten::gcd(Tensor self, Tensor other) -> Tensor
+inline at::Tensor gcd(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::gcd::call(self, other);
+}
+
+// aten::gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!)
+inline at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::gcd_::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..50918137f2522ff9cf22356afdadafa2f36843ca
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor gcd(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2a7689c34f2e206bbe5a4565d0fb10ffcf1c281b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor gcd(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..25d9eeba2e135814d373f9046fb4fe472afa60bf
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor gcd(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..79bcd6195ddbdae06e291491d39816ab9bf82d14
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_gcd : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b4da98875bd67285dcbe23e315738679c527937e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor gcd(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..446db7321ad862e0ccf56669b39fa4e865cd379d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/gcd_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_gcd_out : public at::meta::structured_gcd {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..cca0c06155d09248d3b8f365a35c6c537b5081dd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gcd_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gcd_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gcd";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API gcd {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gcd";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gcd(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API gcd_ {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gcd_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge.h
new file mode 100644
index 0000000000000000000000000000000000000000..34cc41531f0b2625a996cc8d9228ff8064c23444
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/ge_ops.h>
+
+namespace at {
+
+
+// aten::ge.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::ge_Scalar_out::call(self, other, out);
+}
+// aten::ge.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::ge_Scalar_out::call(self, other, out);
+}
+
+// aten::ge.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor ge(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::ge_Scalar::call(self, other);
+}
+
+// aten::ge.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::ge_Tensor_out::call(self, other, out);
+}
+// aten::ge.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::ge_Tensor_out::call(self, other, out);
+}
+
+// aten::ge.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor ge(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::ge_Tensor::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ae541f9888e9ee6de2b631a2fcb8d98498db1c06
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..df4d5cacf056e8034a01dd16be954f8372f7285b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cpu_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..31d7d4adbbf922df5553a89357895981a9fa2822
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_cuda_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..b72e9c5a2d11da6a200fa9f98759de2249bc9c1b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta.h
@@ -0,0 +1,32 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_ge_Scalar : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Scalar & other);
+};
+struct TORCH_API structured_ge_Tensor : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e488b458e4648d336637dee2bd1939f4bd430a03
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_meta_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8a943808f081eab3f6287e62a7de913874172403
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_native.h
@@ -0,0 +1,31 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/ge_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_ge_Scalar_out : public at::meta::structured_ge_Scalar {
+void impl(const at::Tensor & self, const at::Scalar & other, const at::Tensor & out);
+};
+TORCH_API at::Tensor ge_scalar_nested(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor ge_quantized_cpu(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & ge_out_quantized_cpu(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+struct TORCH_API structured_ge_Tensor_out : public at::meta::structured_ge_Tensor {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+TORCH_API at::Tensor ge_quantized_cpu(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & ge_out_quantized_cpu(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..09fb9a9c3a4e7ecefd67c4a50ca1c70e7d6a1b57
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ge_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API ge_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "ge.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+struct TORCH_API ge_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "ge.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API ge_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "ge.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API ge_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "ge.Tensor(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API ge__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "ge_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API ge__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ge_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "ge_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h
new file mode 100644
index 0000000000000000000000000000000000000000..a50481909e19216e0d3fcc09a0c59122fb81a85b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gelu_ops.h>
+
+namespace at {
+
+
+// aten::gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none") {
+    return at::_ops::gelu_out::call(self, approximate, out);
+}
+// aten::gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out) {
+    return at::_ops::gelu_out::call(self, approximate, out);
+}
+
+// aten::gelu_(Tensor(a!) self, *, str approximate='none') -> Tensor(a!)
+inline at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none") {
+    return at::_ops::gelu_::call(self, approximate);
+}
+
+// aten::gelu(Tensor self, *, str approximate='none') -> Tensor
+inline at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none") {
+    return at::_ops::gelu::call(self, approximate);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..3f860cdd20e4aa57aa8794ba4e9fb618f7a3dc7c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gelu_backward_ops.h>
+
+namespace at {
+
+
+// aten::gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none") {
+    return at::_ops::gelu_backward_grad_input::call(grad_output, self, approximate, grad_input);
+}
+// aten::gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & gelu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input) {
+    return at::_ops::gelu_backward_grad_input::call(grad_output, self, approximate, grad_input);
+}
+
+// aten::gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor
+inline at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none") {
+    return at::_ops::gelu_backward::call(grad_output, self, approximate);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fa915dc91bc9194e93fcf99f124570314d57201b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe5129821001bc6dfbfc55640e2e699b04fe1f83
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..cf3f261dcd2c9e65f308e42572ccfe7977b7dcdc
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..82b9c8e32c4956c128bd8d36504c57e5fe4bae1b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_gelu_backward : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6be3e6d3c0dc7b6e4e482a21ba649289591d2781
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..1bf6f31d7bde01bf3f6012e3b2d8e27955859938
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_native.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/gelu_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_gelu_backward_out_cpu : public at::meta::structured_gelu_backward {
+void impl(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_gelu_backward_out_cuda : public at::meta::structured_gelu_backward {
+void impl(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, const at::Tensor & grad_input);
+};
+TORCH_API at::Tensor gelu_backwards_nested(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor mkldnn_gelu_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate="none");
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..73fa8def35efec67b010677a9e2ad9429932ff79
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gelu_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::string_view, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gelu_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input);
+};
+
+struct TORCH_API gelu_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gelu_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..35310f85da65d35a053dfadd33d57d87ac8d5696
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none");
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3cdc3996fdb7468b985c7cde9f894433e4c7b616
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out);
+TORCH_API at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none");
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..60dac9a81337d7a39ab6b108aeef0d4f8a5e838e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out);
+TORCH_API at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none");
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..037c85eb81f55833914a8638f7a4851e4746538b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_gelu : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, c10::string_view approximate);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e2d9aaf40d6082fb9a1528304dd2b781e62685bf
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_outf(const at::Tensor & self, c10::string_view approximate, at::Tensor & out);
+TORCH_API at::Tensor & gelu_(at::Tensor & self, c10::string_view approximate="none");
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..e6e6df48c9a547695897ca91aedbc4ce1b77943b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_native.h
@@ -0,0 +1,32 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/gelu_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_gelu_out_cpu : public at::meta::structured_gelu {
+void impl(const at::Tensor & self, c10::string_view approximate, const at::Tensor & out);
+};
+struct TORCH_API structured_gelu_out_cuda : public at::meta::structured_gelu {
+void impl(const at::Tensor & self, c10::string_view approximate, const at::Tensor & out);
+};
+TORCH_API at::Tensor NestedTensor_gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & NestedTensor_gelu_(at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor mkldnn_gelu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor gelu_quantized_cpu(const at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor & gelu_quantized_cpu_(at::Tensor & self, c10::string_view approximate="none");
+TORCH_API at::Tensor gelu_quantized_cuda(const at::Tensor & self, c10::string_view approximate="none");
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..25f56bfe344862446eb769fb6aec1af1aac951b5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gelu_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gelu_out {
+  using schema = at::Tensor & (const at::Tensor &, c10::string_view, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gelu";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "gelu.out(Tensor self, *, str approximate='none', Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, c10::string_view approximate, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate, at::Tensor & out);
+};
+
+struct TORCH_API gelu_ {
+  using schema = at::Tensor & (at::Tensor &, c10::string_view);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gelu_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gelu_(Tensor(a!) self, *, str approximate='none') -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, c10::string_view approximate);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, c10::string_view approximate);
+};
+
+struct TORCH_API gelu {
+  using schema = at::Tensor (const at::Tensor &, c10::string_view);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gelu";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gelu(Tensor self, *, str approximate='none') -> Tensor";
+  static at::Tensor call(const at::Tensor & self, c10::string_view approximate);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view approximate);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric.h
new file mode 100644
index 0000000000000000000000000000000000000000..5706e2fe495f04fd9e42e9d26b051e018f6d305f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/geometric_ops.h>
+
+namespace at {
+
+
+// aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & geometric_out(at::Tensor & out, const at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt) {
+    return at::_ops::geometric_out::call(self, p, generator, out);
+}
+// aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & geometric_outf(const at::Tensor & self, double p, ::std::optional<at::Generator> generator, at::Tensor & out) {
+    return at::_ops::geometric_out::call(self, p, generator, out);
+}
+
+// aten::geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor
+inline at::Tensor geometric(const at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt) {
+    return at::_ops::geometric::call(self, p, generator);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7823e43b9a610546b1dee85303e896cacd481d69
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor geometric(const at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & geometric_out(at::Tensor & out, const at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & geometric_outf(const at::Tensor & self, double p, ::std::optional<at::Generator> generator, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..f0e4c91614cb3efd3276c809bf44f3cd17dca6fd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e740d27a63d345f277560ffce3b91692881de0c6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3339626b9d64d097a3439999ccb74ce2391a55f9
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_meta_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..693f412a1d1b902c644a89993ff6c22fa561de9d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor geometric(const at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & geometric_out(const at::Tensor & self, double p, ::std::optional<at::Generator> generator, at::Tensor & out);
+TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, ::std::optional<at::Generator> generator=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe714db661fa30c019a782bed34c851f2b888bfe
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geometric_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API geometric_ {
+  using schema = at::Tensor & (at::Tensor &, double, ::std::optional<at::Generator>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::geometric_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "geometric_(Tensor(a!) self, float p, *, Generator? generator=None) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, double p, ::std::optional<at::Generator> generator);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, ::std::optional<at::Generator> generator);
+};
+
+struct TORCH_API geometric_out {
+  using schema = at::Tensor & (const at::Tensor &, double, ::std::optional<at::Generator>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::geometric";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, double p, ::std::optional<at::Generator> generator, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional<at::Generator> generator, at::Tensor & out);
+};
+
+struct TORCH_API geometric {
+  using schema = at::Tensor (const at::Tensor &, double, ::std::optional<at::Generator>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::geometric";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, double p, ::std::optional<at::Generator> generator);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, ::std::optional<at::Generator> generator);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf.h
new file mode 100644
index 0000000000000000000000000000000000000000..02f8de5df78dcaa3503bd36a7c1d7660f3722570
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/geqrf_ops.h>
+
+namespace at {
+
+
+// aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)
+inline ::std::tuple<at::Tensor &,at::Tensor &> geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self) {
+    return at::_ops::geqrf_a::call(self, a, tau);
+}
+// aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)
+inline ::std::tuple<at::Tensor &,at::Tensor &> geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau) {
+    return at::_ops::geqrf_a::call(self, a, tau);
+}
+
+// aten::geqrf(Tensor self) -> (Tensor a, Tensor tau)
+inline ::std::tuple<at::Tensor,at::Tensor> geqrf(const at::Tensor & self) {
+    return at::_ops::geqrf::call(self);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2a6f18f26a9b422ba359fdbf1dbb9e6acfdb5e35
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> geqrf(const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..87d3f521d623b05e3ae74ba8e93887ccd05a1831
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> geqrf(const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c27fb0722080b67b07010e295dbf4dc566f90f59
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> geqrf(const at::Tensor & self);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> geqrf_out(const at::Tensor & self, at::Tensor & a, at::Tensor & tau);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ed1c2a4592f8cf086cd9acc73c30542dbff14a23
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/geqrf_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API geqrf_a {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::geqrf";
+  static constexpr const char* overload_name = "a";
+  static constexpr const char* schema_str = "geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, at::Tensor & a, at::Tensor & tau);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & a, at::Tensor & tau);
+};
+
+struct TORCH_API geqrf {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::geqrf";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "geqrf(Tensor self) -> (Tensor a, Tensor tau)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h
new file mode 100644
index 0000000000000000000000000000000000000000..f38cd0cbdf79a708aa9a02d5b710c1f8264e330a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/ger_ops.h>
+
+namespace at {
+
+
+// aten::ger(Tensor self, Tensor vec2) -> Tensor
+inline at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2) {
+    return at::_ops::ger::call(self, vec2);
+}
+
+// aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ger_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2) {
+    return at::_ops::ger_out::call(self, vec2, out);
+}
+// aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & ger_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) {
+    return at::_ops::ger_out::call(self, vec2, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1329ffbb662862ee4e443e5403305dafdc8a6ea6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2);
+TORCH_API at::Tensor & ger_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec2);
+TORCH_API at::Tensor & ger_outf(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..4bf3e9bf9232d0db33b01648021c1edf5bf1b8f2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor ger(const at::Tensor & self, const at::Tensor & vec2);
+TORCH_API at::Tensor & ger_out(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..f2705ad7b0110ea048ec94eff55d784845407e7b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/ger_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API ger {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ger";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "ger(Tensor self, Tensor vec2) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & vec2);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2);
+};
+
+struct TORCH_API ger_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::ger";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu.h
new file mode 100644
index 0000000000000000000000000000000000000000..4889e7196b589ceb76471267e1de5d749ded0934
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/glu_ops.h>
+
+namespace at {
+
+
+// aten::glu.out(Tensor self, int dim=-1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1) {
+    return at::_ops::glu_out::call(self, dim, out);
+}
+// aten::glu.out(Tensor self, int dim=-1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out) {
+    return at::_ops::glu_out::call(self, dim, out);
+}
+
+// aten::glu(Tensor self, int dim=-1) -> Tensor
+inline at::Tensor glu(const at::Tensor & self, int64_t dim=-1) {
+    return at::_ops::glu::call(self, dim);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..b7eabe805fe7d31d050e44023458812937847b82
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/glu_backward_ops.h>
+
+namespace at {
+
+
+// aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & glu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) {
+    return at::_ops::glu_backward_grad_input::call(grad_output, self, dim, grad_input);
+}
+// aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & glu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input) {
+    return at::_ops::glu_backward_grad_input::call(grad_output, self, dim, grad_input);
+}
+
+// aten::glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor
+inline at::Tensor glu_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) {
+    return at::_ops::glu_backward::call(grad_output, self, dim);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9788038044ff983a2cba8d6b941cd2ed1b54f252
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor glu_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5db9649cfbaf4f7a67d857d120ac866408b9bf1b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor glu_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp.h
new file mode 100644
index 0000000000000000000000000000000000000000..cf1fdf0d99f2345e4e4e00589420866b79283008
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/glu_backward_jvp_ops.h>
+
+namespace at {
+
+
+// aten::glu_backward_jvp(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim) -> Tensor
+inline at::Tensor glu_backward_jvp(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim) {
+    return at::_ops::glu_backward_jvp::call(grad_x, grad_glu, x, dgrad_glu, dx, dim);
+}
+
+// aten::glu_backward_jvp.out(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_backward_jvp_out(at::Tensor & out, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim) {
+    return at::_ops::glu_backward_jvp_out::call(grad_x, grad_glu, x, dgrad_glu, dx, dim, out);
+}
+// aten::glu_backward_jvp.out(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_backward_jvp_outf(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out) {
+    return at::_ops::glu_backward_jvp_out::call(grad_x, grad_glu, x, dgrad_glu, dx, dim, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9a95ffc2d2583aa3e6221cf2a7ecfecccf45d2e0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & glu_backward_jvp_out(at::Tensor & out, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+TORCH_API at::Tensor & glu_backward_jvp_outf(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9479ffb55eb00d262e157d60462b5921a9384e58
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor glu_backward_jvp(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..79b688b3a0200ae01cc96915615ea7d45e51cc8e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor glu_backward_jvp(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..2d28fdc1c9d8d076eeb1de2cf0def482f510c9e5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & glu_backward_jvp_out(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+TORCH_API at::Tensor glu_backward_jvp(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..46d965e9d1d62dfe9fa87ff313d5f9a22e92bbf2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_jvp_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API glu_backward_jvp {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_backward_jvp";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "glu_backward_jvp(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim);
+};
+
+struct TORCH_API glu_backward_jvp_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_backward_jvp";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "glu_backward_jvp.out(Tensor grad_x, Tensor grad_glu, Tensor x, Tensor dgrad_glu, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_x, const at::Tensor & grad_glu, const at::Tensor & x, const at::Tensor & dgrad_glu, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..bc02b7b5d204985332d22011e72f99444fc28d0e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_native.h
@@ -0,0 +1,24 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor glu_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_cpu_out(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+TORCH_API at::Tensor glu_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & glu_backward_cuda_out(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e6c0126d918cfb75b4fedda6dfca5dee62243b6d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API glu_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input);
+};
+
+struct TORCH_API glu_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a454a6da1ee244b5bedbaccdca79d05e7e36411d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..aefe9658557bff07f2d23b3d04eb4b93cefe33a5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..52e332cbfc5cc9156688923d780644a304475dda
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h
new file mode 100644
index 0000000000000000000000000000000000000000..12c1f7cb454e5997c6ffa4e968458785a5b09c73
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/glu_jvp_ops.h>
+
+namespace at {
+
+
+// aten::glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor
+inline at::Tensor glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) {
+    return at::_ops::glu_jvp::call(glu, x, dx, dim);
+}
+
+// aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_jvp_out(at::Tensor & out, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) {
+    return at::_ops::glu_jvp_out::call(glu, x, dx, dim, out);
+}
+// aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & glu_jvp_outf(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out) {
+    return at::_ops::glu_jvp_out::call(glu, x, dx, dim, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..dc7f486b3892cc0953fe21ef5d813a3c5330ea4b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & glu_jvp_out(at::Tensor & out, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+TORCH_API at::Tensor & glu_jvp_outf(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9abfc1d4fb5f5547f5e2ce35f8123c7c4c8de949
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ca9787cfdd0220309bfbe2d4ea679a6803440a94
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8f2f50f641c276ff767dd1c0171e5bf43a83615f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & glu_jvp_out(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+TORCH_API at::Tensor glu_jvp(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..459da89fab45e69d5d1e38b467776c883fe881a4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_jvp_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API glu_jvp {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_jvp";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor";
+  static at::Tensor call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim);
+};
+
+struct TORCH_API glu_jvp_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu_jvp";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..bda539ab05ab2d3af82678fed7c3c072af4cd723
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_glu : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, int64_t dim);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..dadf8681c1931693a99c1c95ef8be95981a724d5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1);
+TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..fd03fc6aef73edc0757fcb026f32d3aa116cfb09
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/glu_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_glu_out : public at::meta::structured_glu {
+void impl(const at::Tensor & self, int64_t dim, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..09f4ccb8cee52a665a5e1a83a70ba9e5da671a7f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/glu_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API glu_out {
+  using schema = at::Tensor & (const at::Tensor &, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "glu.out(Tensor self, int dim=-1, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t dim, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & out);
+};
+
+struct TORCH_API glu {
+  using schema = at::Tensor (const at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::glu";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "glu(Tensor self, int dim=-1) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient.h
new file mode 100644
index 0000000000000000000000000000000000000000..9b55d1a230197b9a1cfbd6e65aa9a9fa53588964
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient.h
@@ -0,0 +1,60 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gradient_ops.h>
+
+namespace at {
+
+
+// aten::gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, const ::std::optional<at::Scalar> & spacing=::std::nullopt, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1) {
+    return at::_ops::gradient_scalarint::call(self, spacing, dim, edge_order);
+}
+
+// aten::gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1) {
+    return at::_ops::gradient_scalararray::call(self, spacing, dim, edge_order);
+}
+
+// aten::gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1) {
+    return at::_ops::gradient_array::call(self, dim, edge_order);
+}
+
+// aten::gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1) {
+    return at::_ops::gradient_scalarrayint::call(self, spacing, dim, edge_order);
+}
+
+// aten::gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order=1) {
+    return at::_ops::gradient_scalarrayarray::call(self, spacing, dim, edge_order);
+}
+
+// aten::gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1) {
+    return at::_ops::gradient_tensorarrayint::call(self, spacing, dim, edge_order);
+}
+
+// aten::gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[]
+inline ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1) {
+    return at::_ops::gradient_tensorarray::call(self, spacing, dim, edge_order);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5824553346d1bbb91e526983e02c21dbb1256d17
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,29 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, const ::std::optional<at::Scalar> & spacing=::std::nullopt, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..7f5e00e0e2715a5b90d238b55b2450b97d607e6b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_native.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, const ::std::optional<at::Scalar> & spacing=::std::nullopt, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, ::std::optional<int64_t> dim=::std::nullopt, int64_t edge_order=1);
+TORCH_API ::std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..147cec29b2c4d8ece70ca1dcb18ba837aa2d7331
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gradient_ops.h
@@ -0,0 +1,94 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gradient_scalarint {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, const ::std::optional<at::Scalar> &, ::std::optional<int64_t>, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "scalarint";
+  static constexpr const char* schema_str = "gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, const ::std::optional<at::Scalar> & spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const ::std::optional<at::Scalar> & spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_scalararray {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, const at::Scalar &, at::IntArrayRef, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "scalararray";
+  static constexpr const char* schema_str = "gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_array {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::IntArrayRef, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "array";
+  static constexpr const char* schema_str = "gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_scalarrayint {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::ArrayRef<at::Scalar>, ::std::optional<int64_t>, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "scalarrayint";
+  static constexpr const char* schema_str = "gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_scalarrayarray {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::ArrayRef<at::Scalar>, at::IntArrayRef, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "scalarrayarray";
+  static constexpr const char* schema_str = "gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_tensorarrayint {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::TensorList, ::std::optional<int64_t>, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "tensorarrayint";
+  static constexpr const char* schema_str = "gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::TensorList spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, ::std::optional<int64_t> dim, int64_t edge_order);
+};
+
+struct TORCH_API gradient_tensorarray {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::TensorList, at::IntArrayRef, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gradient";
+  static constexpr const char* overload_name = "tensorarray";
+  static constexpr const char* schema_str = "gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater.h
new file mode 100644
index 0000000000000000000000000000000000000000..91240b92b4699ef7edec629eaa6771acc8b0739b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/greater_ops.h>
+
+namespace at {
+
+
+// aten::greater.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::greater_Scalar_out::call(self, other, out);
+}
+// aten::greater.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::greater_Scalar_out::call(self, other, out);
+}
+
+// aten::greater.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor greater(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::greater_Scalar::call(self, other);
+}
+
+// aten::greater.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::greater_Tensor_out::call(self, other, out);
+}
+// aten::greater.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::greater_Tensor_out::call(self, other, out);
+}
+
+// aten::greater.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor greater(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::greater_Tensor::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..87975e91d719d2773de635bf566799e4d315e9bb
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor greater(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor greater(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal.h
new file mode 100644
index 0000000000000000000000000000000000000000..380fc7afed08c79a284e6609596d058dd07fcfaa
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/greater_equal_ops.h>
+
+namespace at {
+
+
+// aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::greater_equal_Scalar_out::call(self, other, out);
+}
+// aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::greater_equal_Scalar_out::call(self, other, out);
+}
+
+// aten::greater_equal.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::greater_equal_Scalar::call(self, other);
+}
+
+// aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::greater_equal_Tensor_out::call(self, other, out);
+}
+// aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::greater_equal_Tensor_out::call(self, other, out);
+}
+
+// aten::greater_equal.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::greater_equal_Tensor::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..495dfe1972f3574b2ac568e16322b7be86ea482b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_equal_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_equal_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..001198a67530a3506e4f6cc2295c03abc598cd62
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor greater_equal(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_equal_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_equal_(at::Tensor & self, const at::Tensor & other);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..325f39baa1a41897d79cb8bc51219933b7346ce7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_equal_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API greater_equal_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+struct TORCH_API greater_equal_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "greater_equal.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API greater_equal_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API greater_equal_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "greater_equal.Tensor(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API greater_equal__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "greater_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API greater_equal__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_equal_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "greater_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..935f5f55a299b899c60095acf00b1671ab4d8392
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor greater(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & greater_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor greater(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & greater_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & greater_(at::Tensor & self, const at::Tensor & other);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..eb3324f8941523a68049acb9fbd055c0ea73211e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/greater_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API greater_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "greater.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+struct TORCH_API greater_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "greater.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API greater_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "greater.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API greater_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "greater.Tensor(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API greater__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "greater_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API greater__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::greater_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "greater_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler.h
new file mode 100644
index 0000000000000000000000000000000000000000..baabd9c565a8165290fbd67613cc3e7b6c69d875
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/grid_sampler_ops.h>
+
+namespace at {
+
+
+// aten::grid_sampler(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor
+inline at::Tensor grid_sampler(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) {
+    return at::_ops::grid_sampler::call(input, grid, interpolation_mode, padding_mode, align_corners);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d.h
new file mode 100644
index 0000000000000000000000000000000000000000..899b6a2c78281409fd2170b755b76e1c49eefdda
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/grid_sampler_2d_ops.h>
+
+namespace at {
+
+
+// aten::grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor
+inline at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) {
+    return at::_ops::grid_sampler_2d::call(input, grid, interpolation_mode, padding_mode, align_corners);
+}
+
+// aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & grid_sampler_2d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) {
+    return at::_ops::grid_sampler_2d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out);
+}
+// aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & grid_sampler_2d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) {
+    return at::_ops::grid_sampler_2d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..976d5ccb1440c47bd2c9375959d89edda99ad97a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/grid_sampler_2d_backward_ops.h>
+
+namespace at {
+
+
+// aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) {
+    return at::_ops::grid_sampler_2d_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask);
+}
+
+// aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) {
+    return at::_ops::grid_sampler_2d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1);
+}
+// aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) {
+    return at::_ops::grid_sampler_2d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fa4c5cda20b0fc5e44cbc8e9cc58f649c0e09e88
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6168dc34a416c3b96985903ab9777ed91c406fec
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..540de004e7a63a7d304da9636d58c94701a3d9cf
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..95ad7cb2e298723fcf7a2369731a4999ce66193a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_out(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6397bb6a0d9bba8ecf6170fac0bfe17b5ed1a6dd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API grid_sampler_2d_backward {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array<bool,2>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_2d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+};
+
+struct TORCH_API grid_sampler_2d_backward_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array<bool,2>, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_2d_backward";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1f87bc0f0a5b07c21e4a312fc00f1880f6b344e6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & grid_sampler_2d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+TORCH_API at::Tensor & grid_sampler_2d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d0a004abcf0d0559eea81053433c3dd147578455
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9298432c61f44b8489e96f9e28a028ef8f894d12
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..390c841110012ab2ac993e8131db088095d45929
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & grid_sampler_2d_out(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+TORCH_API at::Tensor grid_sampler_2d_cpu(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+TORCH_API at::Tensor grid_sampler_2d_cuda(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..94f4da9f0341faeb59e080eaf6cc4a2ae8169548
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_2d_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API grid_sampler_2d {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_2d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+};
+
+struct TORCH_API grid_sampler_2d_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_2d";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d.h
new file mode 100644
index 0000000000000000000000000000000000000000..cb7266ad38c30373a9612e6f20c75196da0060ce
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/grid_sampler_3d_ops.h>
+
+namespace at {
+
+
+// aten::grid_sampler_3d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor
+inline at::Tensor grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) {
+    return at::_ops::grid_sampler_3d::call(input, grid, interpolation_mode, padding_mode, align_corners);
+}
+
+// aten::grid_sampler_3d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & grid_sampler_3d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) {
+    return at::_ops::grid_sampler_3d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out);
+}
+// aten::grid_sampler_3d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & grid_sampler_3d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) {
+    return at::_ops::grid_sampler_3d_out::call(input, grid, interpolation_mode, padding_mode, align_corners, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..1b079531ac1bf3d8550743047e2d4e36d3bb07e4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/grid_sampler_3d_backward_ops.h>
+
+namespace at {
+
+
+// aten::grid_sampler_3d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) {
+    return at::_ops::grid_sampler_3d_backward::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask);
+}
+
+// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_3d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) {
+    return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1);
+}
+// aten::grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))
+inline ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) {
+    return at::_ops::grid_sampler_3d_backward_out::call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3d64163bacdb598ee2ab24c56280239a84594eb4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_3d_backward_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3ff02f0756280681b89748b14df667fd501ff374
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..343023d64d5d21d7536eef5954d62fd9a0240a35
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..01242af37c4b52ef853ceba522aa1c063969953a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_3d_backward_out(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_3d_backward_cpu(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> grid_sampler_3d_backward_cuda(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..10914124927b11cac7e97519adc5e188929ace62
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API grid_sampler_3d_backward {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array<bool,2>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_3d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "grid_sampler_3d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask);
+};
+
+struct TORCH_API grid_sampler_3d_backward_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, ::std::array<bool,2>, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_3d_backward";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "grid_sampler_3d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6455a6cee6b06135ac38ff201b2b5c6d06edda89
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & grid_sampler_3d_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+TORCH_API at::Tensor & grid_sampler_3d_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c8e065ba16645a2adbfaf5fdacc11a80d9dec72e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fea2fa20e7c3effa0579c14b4acae8706e8efde0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..b258ddcbf199e222adf9eee2bcf56c5ce374cd0a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & grid_sampler_3d_out(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+TORCH_API at::Tensor grid_sampler_3d_cpu(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+TORCH_API at::Tensor grid_sampler_3d_cuda(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..160194cc302310b56cb9aab863674eb4fcea7354
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_3d_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API grid_sampler_3d {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_3d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "grid_sampler_3d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+};
+
+struct TORCH_API grid_sampler_3d_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler_3d";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "grid_sampler_3d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..f8e33ad7e71615b649ca8f813500299b74e26cce
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor grid_sampler(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..169bf071bde7932bcfd7ca1f67a686869c4c472c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor grid_sampler(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..04833e001c9bedfe06a73cbcf3e4f15a1533cef2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/grid_sampler_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API grid_sampler {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::grid_sampler";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "grid_sampler(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm.h
new file mode 100644
index 0000000000000000000000000000000000000000..94bf20a0f278cb3d28093eda5e6a07e780d6e504
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/group_norm_ops.h>
+
+namespace at {
+
+
+// aten::group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor
+inline at::Tensor group_norm(const at::Tensor & input, int64_t num_groups, const ::std::optional<at::Tensor> & weight={}, const ::std::optional<at::Tensor> & bias={}, double eps=1e-05, bool cudnn_enabled=true) {
+    return at::_ops::group_norm::call(input, num_groups, weight, bias, eps, cudnn_enabled);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e5722d88243346058ae366b70e7f3aadbf9e8e18
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor group_norm(const at::Tensor & input, int64_t num_groups, const ::std::optional<at::Tensor> & weight={}, const ::std::optional<at::Tensor> & bias={}, double eps=1e-05, bool cudnn_enabled=true);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8448aa99ccc1289739137342a490cb4d1ec89247
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor group_norm(const at::Tensor & input, int64_t num_groups, const ::std::optional<at::Tensor> & weight={}, const ::std::optional<at::Tensor> & bias={}, double eps=1e-05, bool cudnn_enabled=true);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..88afcf31465e91d2bf2fcc79a973fffb94ab07e8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/group_norm_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API group_norm {
+  using schema = at::Tensor (const at::Tensor &, int64_t, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, double, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::group_norm";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, int64_t num_groups, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, double eps, bool cudnn_enabled);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t num_groups, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, double eps, bool cudnn_enabled);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru.h
new file mode 100644
index 0000000000000000000000000000000000000000..1f9e91d5d0bc78512b0ba47f9ec24a8c105f7b92
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru.h
@@ -0,0 +1,35 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gru_ops.h>
+
+namespace at {
+
+
+// aten::gru.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) {
+    return at::_ops::gru_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first);
+}
+
+// aten::gru.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) {
+    return at::_ops::gru_data::call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell.h
new file mode 100644
index 0000000000000000000000000000000000000000..0566f87fdc7f99a969093f3f74440d4806891949
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gru_cell_ops.h>
+
+namespace at {
+
+
+// aten::gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor
+inline at::Tensor gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional<at::Tensor> & b_ih={}, const ::std::optional<at::Tensor> & b_hh={}) {
+    return at::_ops::gru_cell::call(input, hx, w_ih, w_hh, b_ih, b_hh);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b7b9fecd092d677fe0098177366fbc4b2abe9131
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API at::Tensor gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional<at::Tensor> & b_ih={}, const ::std::optional<at::Tensor> & b_hh={});
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..4384a49b362c3a525b8421471dac1bf8626512a0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor gru_cell(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional<at::Tensor> & b_ih={}, const ::std::optional<at::Tensor> & b_hh={});
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..0d800106c399ed46da6d48f0297854995b112979
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_cell_ops.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gru_cell {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gru_cell";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional<at::Tensor> & b_ih, const ::std::optional<at::Tensor> & b_hh);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const ::std::optional<at::Tensor> & b_ih, const ::std::optional<at::Tensor> & b_hh);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_compositeimplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a07f99cb9739013998d3b32bd32c8a6429375006
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_compositeimplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeimplicitautograd {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..633e18b28d1ca08eb19a6daab72c524a315b65ff
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..02c515fce18e009b661bdf6f4f64237d4621109e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gru_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gru_input {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, bool, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gru";
+  static constexpr const char* overload_name = "input";
+  static constexpr const char* schema_str = "gru.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first);
+};
+
+struct TORCH_API gru_data {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, bool, int64_t, double, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gru";
+  static constexpr const char* overload_name = "data";
+  static constexpr const char* schema_str = "gru.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt.h
new file mode 100644
index 0000000000000000000000000000000000000000..42e004c8d0409f1245f341c9c871b4ebae0c478a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt.h
@@ -0,0 +1,53 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/gt_ops.h>
+
+namespace at {
+
+
+// aten::gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::gt_Scalar_out::call(self, other, out);
+}
+// aten::gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) {
+    return at::_ops::gt_Scalar_out::call(self, other, out);
+}
+
+// aten::gt.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor gt(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::gt_Scalar::call(self, other);
+}
+
+// aten::gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::gt_Tensor_out::call(self, other, out);
+}
+// aten::gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::gt_Tensor_out::call(self, other, out);
+}
+
+// aten::gt.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor gt(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::gt_Tensor::call(self, other);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ef43564ff7cfd42ff7b112355af8539fa26c1946
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..602d9653c04510f84157d99cab1a0365f518cbcf
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cpu_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5ff67ef575640c5baa83463aef7c3e4bb0904923
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_cuda_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..d7fd12cbd8c46f3186a4ee7af3712b0de287754b
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta.h
@@ -0,0 +1,32 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_gt_Scalar : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Scalar & other);
+};
+struct TORCH_API structured_gt_Tensor : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Tensor & other);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..359ba036e171128210e518de814c615484bca24d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_meta_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..50acfcd0d100bb2a5815c43815a71a5a2e0751e2
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_native.h
@@ -0,0 +1,31 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/gt_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_gt_Scalar_out : public at::meta::structured_gt_Scalar {
+void impl(const at::Tensor & self, const at::Scalar & other, const at::Tensor & out);
+};
+TORCH_API at::Tensor gt_scalar_nested(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor gt_quantized_cpu(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & gt_out_quantized_cpu(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+struct TORCH_API structured_gt_Tensor_out : public at::meta::structured_gt_Tensor {
+void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
+};
+TORCH_API at::Tensor gt_quantized_cpu(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & gt_out_quantized_cpu(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..d9069b98c3d16a2d8944e9e512ed5c4d167de773
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/gt_ops.h
@@ -0,0 +1,83 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API gt_Scalar_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt";
+  static constexpr const char* overload_name = "Scalar_out";
+  static constexpr const char* schema_str = "gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
+};
+
+struct TORCH_API gt_Scalar {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "gt.Scalar(Tensor self, Scalar other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API gt_Tensor_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+};
+
+struct TORCH_API gt_Tensor {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "gt.Tensor(Tensor self, Tensor other) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & other);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other);
+};
+
+struct TORCH_API gt__Scalar {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "gt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other);
+};
+
+struct TORCH_API gt__Tensor {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::gt_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "gt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & other);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window.h
new file mode 100644
index 0000000000000000000000000000000000000000..c73cb398e12efe83ba3467f067e318dcb7d0e552
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window.h
@@ -0,0 +1,97 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hamming_window_ops.h>
+
+namespace at {
+
+
+// aten::hamming_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, at::TensorOptions options={}) {
+    return at::_ops::hamming_window::call(window_length, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hamming_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hamming_window::call(window_length, dtype, layout, device, pin_memory);
+}
+
+// aten::hamming_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, at::TensorOptions options={}) {
+    return at::_ops::hamming_window_periodic::call(window_length, periodic, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hamming_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hamming_window_periodic::call(window_length, periodic, dtype, layout, device, pin_memory);
+}
+
+// aten::hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, at::TensorOptions options={}) {
+    return at::_ops::hamming_window_periodic_alpha::call(window_length, periodic, alpha, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hamming_window_periodic_alpha::call(window_length, periodic, alpha, dtype, layout, device, pin_memory);
+}
+
+// aten::hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, at::TensorOptions options={}) {
+    return at::_ops::hamming_window_periodic_alpha_beta::call(window_length, periodic, alpha, beta, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hamming_window_periodic_alpha_beta::call(window_length, periodic, alpha, beta, dtype, layout, device, pin_memory);
+}
+
+// aten::hamming_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length) {
+    return at::_ops::hamming_window_out::call(window_length, out);
+}
+// aten::hamming_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_outf(int64_t window_length, at::Tensor & out) {
+    return at::_ops::hamming_window_out::call(window_length, out);
+}
+
+// aten::hamming_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic) {
+    return at::_ops::hamming_window_periodic_out::call(window_length, periodic, out);
+}
+// aten::hamming_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, at::Tensor & out) {
+    return at::_ops::hamming_window_periodic_out::call(window_length, periodic, out);
+}
+
+// aten::hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha) {
+    return at::_ops::hamming_window_periodic_alpha_out::call(window_length, periodic, alpha, out);
+}
+// aten::hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, at::Tensor & out) {
+    return at::_ops::hamming_window_periodic_alpha_out::call(window_length, periodic, alpha, out);
+}
+
+// aten::hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha, double beta) {
+    return at::_ops::hamming_window_periodic_alpha_beta_out::call(window_length, periodic, alpha, beta, out);
+}
+// aten::hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out) {
+    return at::_ops::hamming_window_periodic_alpha_beta_out::call(window_length, periodic, alpha, beta, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..f1e715d831208133c25f8860a1541f289287ad62
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,38 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor hamming_window(int64_t window_length, at::TensorOptions options={});
+TORCH_API at::Tensor hamming_window(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length);
+TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, at::TensorOptions options={});
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic);
+TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, at::TensorOptions options={});
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha);
+TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, at::TensorOptions options={});
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hamming_window_out(at::Tensor & out, int64_t window_length, bool periodic, double alpha, double beta);
+TORCH_API at::Tensor & hamming_window_outf(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..271855322232c227716848d2fd1c6bdfd6e84e37
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_native.h
@@ -0,0 +1,28 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hamming_window(int64_t window_length, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hamming_window_out(int64_t window_length, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hamming_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hamming_window_periodic_alpha_out(int64_t window_length, bool periodic, double alpha, at::Tensor & out);
+TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hamming_window_periodic_alpha_beta_out(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..297dc6a1ce3738c4c30e41220a0523490ca89022
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hamming_window_ops.h
@@ -0,0 +1,105 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hamming_window {
+  using schema = at::Tensor (int64_t, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hamming_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hamming_window_periodic {
+  using schema = at::Tensor (int64_t, bool, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic";
+  static constexpr const char* schema_str = "hamming_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hamming_window_periodic_alpha {
+  using schema = at::Tensor (int64_t, bool, double, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic_alpha";
+  static constexpr const char* schema_str = "hamming_window.periodic_alpha(int window_length, bool periodic, float alpha, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, bool periodic, double alpha, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hamming_window_periodic_alpha_beta {
+  using schema = at::Tensor (int64_t, bool, double, double, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic_alpha_beta";
+  static constexpr const char* schema_str = "hamming_window.periodic_alpha_beta(int window_length, bool periodic, float alpha, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, bool periodic, double alpha, double beta, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, double beta, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hamming_window_out {
+  using schema = at::Tensor & (int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hamming_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out);
+};
+
+struct TORCH_API hamming_window_periodic_out {
+  using schema = at::Tensor & (int64_t, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic_out";
+  static constexpr const char* schema_str = "hamming_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, bool periodic, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out);
+};
+
+struct TORCH_API hamming_window_periodic_alpha_out {
+  using schema = at::Tensor & (int64_t, bool, double, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic_alpha_out";
+  static constexpr const char* schema_str = "hamming_window.periodic_alpha_out(int window_length, bool periodic, float alpha, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, bool periodic, double alpha, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, at::Tensor & out);
+};
+
+struct TORCH_API hamming_window_periodic_alpha_beta_out {
+  using schema = at::Tensor & (int64_t, bool, double, double, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hamming_window";
+  static constexpr const char* overload_name = "periodic_alpha_beta_out";
+  static constexpr const char* schema_str = "hamming_window.periodic_alpha_beta_out(int window_length, bool periodic, float alpha, float beta, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window.h
new file mode 100644
index 0000000000000000000000000000000000000000..c466b2886d018123002a33bb861dd80be69be2be
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window.h
@@ -0,0 +1,61 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hann_window_ops.h>
+
+namespace at {
+
+
+// aten::hann_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hann_window(int64_t window_length, at::TensorOptions options={}) {
+    return at::_ops::hann_window::call(window_length, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hann_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hann_window(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hann_window::call(window_length, dtype, layout, device, pin_memory);
+}
+
+// aten::hann_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hann_window(int64_t window_length, bool periodic, at::TensorOptions options={}) {
+    return at::_ops::hann_window_periodic::call(window_length, periodic, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::hann_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor hann_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::hann_window_periodic::call(window_length, periodic, dtype, layout, device, pin_memory);
+}
+
+// aten::hann_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length) {
+    return at::_ops::hann_window_out::call(window_length, out);
+}
+// aten::hann_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hann_window_outf(int64_t window_length, at::Tensor & out) {
+    return at::_ops::hann_window_out::call(window_length, out);
+}
+
+// aten::hann_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length, bool periodic) {
+    return at::_ops::hann_window_periodic_out::call(window_length, periodic, out);
+}
+// aten::hann_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hann_window_outf(int64_t window_length, bool periodic, at::Tensor & out) {
+    return at::_ops::hann_window_periodic_out::call(window_length, periodic, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8fcf424a82263685734bd2e9783f474e5c7f2f8c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,30 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor hann_window(int64_t window_length, at::TensorOptions options={});
+TORCH_API at::Tensor hann_window(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length);
+TORCH_API at::Tensor & hann_window_outf(int64_t window_length, at::Tensor & out);
+TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, at::TensorOptions options={});
+TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+TORCH_API at::Tensor & hann_window_out(at::Tensor & out, int64_t window_length, bool periodic);
+TORCH_API at::Tensor & hann_window_outf(int64_t window_length, bool periodic, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..fa91ceddc47270f02ff2ceff9da720097c7d1d3c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_native.h
@@ -0,0 +1,24 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hann_window(int64_t window_length, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hann_window_out(int64_t window_length, at::Tensor & out);
+TORCH_API at::Tensor hann_window(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype={}, ::std::optional<at::Layout> layout={}, ::std::optional<at::Device> device={}, ::std::optional<bool> pin_memory={});
+TORCH_API at::Tensor & hann_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..703fe2499a3856d9515faa08c94098dea0385031
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hann_window_ops.h
@@ -0,0 +1,61 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hann_window {
+  using schema = at::Tensor (int64_t, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hann_window";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hann_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hann_window_periodic {
+  using schema = at::Tensor (int64_t, bool, ::std::optional<at::ScalarType>, ::std::optional<at::Layout>, ::std::optional<at::Device>, ::std::optional<bool>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hann_window";
+  static constexpr const char* overload_name = "periodic";
+  static constexpr const char* schema_str = "hann_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API hann_window_out {
+  using schema = at::Tensor & (int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hann_window";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hann_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out);
+};
+
+struct TORCH_API hann_window_periodic_out {
+  using schema = at::Tensor & (int64_t, bool, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hann_window";
+  static constexpr const char* overload_name = "periodic_out";
+  static constexpr const char* schema_str = "hann_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t window_length, bool periodic, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.h
new file mode 100644
index 0000000000000000000000000000000000000000..037c6b0831737b153e936e83a66bd1ff3295db85
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardshrink_ops.h>
+
+namespace at {
+
+
+// aten::hardshrink.out(Tensor self, Scalar lambd=0.5, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5) {
+    return at::_ops::hardshrink_out::call(self, lambd, out);
+}
+// aten::hardshrink.out(Tensor self, Scalar lambd=0.5, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out) {
+    return at::_ops::hardshrink_out::call(self, lambd, out);
+}
+
+// aten::hardshrink(Tensor self, Scalar lambd=0.5) -> Tensor
+inline at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5) {
+    return at::_ops::hardshrink::call(self, lambd);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..ea3dcd641e9083c133bc2167cab89e2639457f9d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardshrink_backward_ops.h>
+
+namespace at {
+
+
+// aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) {
+    return at::_ops::hardshrink_backward_grad_input::call(grad_out, self, lambd, grad_input);
+}
+// aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) {
+    return at::_ops::hardshrink_backward_grad_input::call(grad_out, self, lambd, grad_input);
+}
+
+// aten::hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor
+inline at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) {
+    return at::_ops::hardshrink_backward::call(grad_out, self, lambd);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8dfe7a032a380e0ef452f5a30f6a187b07135744
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..62684b1ac058212095c6435e0c28ed1d72b32125
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ca4f68c6950cc5a8a594522ba278599177839b30
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..57f169686f2d28de275a69586b2b9c154d91acb0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_hardshrink_backward : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..819e120a26567a7bc6bb961cadca5b7e1efb3816
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+TORCH_API at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..ad67e62930d4138924c3f1a7c9e86caf084f4ecd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/hardshrink_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_hardshrink_backward_out : public at::meta::structured_hardshrink_backward {
+void impl(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..9753bd7884ef0dc507be78a630f6971f562bd54d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardshrink_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardshrink_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input);
+};
+
+struct TORCH_API hardshrink_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardshrink_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0ac5cfccd87dc62a9dd9584839b937bd4aab978d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..64ce3072ecbb371c1c166e61fb11567872f6913e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..125d4fe0aae09a885acec9c3dcae7b1a246a7ad3
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..c7765a90e43a93fe516c5bcb608968ade1199504
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_hardshrink : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self, const at::Scalar & lambd);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..45da88a4c4d95b747e5615ad26c0ae7c26534cb1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5);
+TORCH_API at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..dd66907d167f44ea1372dbbc8f5c395b38aa86db
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/hardshrink_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_hardshrink_out : public at::meta::structured_hardshrink {
+void impl(const at::Tensor & self, const at::Scalar & lambd, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ded5939b304d16d57af68359a5e4fb23f9c38cc7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardshrink_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardshrink_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardshrink";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hardshrink.out(Tensor self, Scalar lambd=0.5, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out);
+};
+
+struct TORCH_API hardshrink {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardshrink";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardshrink(Tensor self, Scalar lambd=0.5) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & lambd);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & lambd);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid.h
new file mode 100644
index 0000000000000000000000000000000000000000..77d13fa1dc9ad29f50239bf5d50fea65ad2fbf1e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardsigmoid_ops.h>
+
+namespace at {
+
+
+// aten::hardsigmoid.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::hardsigmoid_out::call(self, out);
+}
+// aten::hardsigmoid.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::hardsigmoid_out::call(self, out);
+}
+
+// aten::hardsigmoid(Tensor self) -> Tensor
+inline at::Tensor hardsigmoid(const at::Tensor & self) {
+    return at::_ops::hardsigmoid::call(self);
+}
+
+// aten::hardsigmoid_(Tensor(a!) self) -> Tensor(a!)
+inline at::Tensor & hardsigmoid_(at::Tensor & self) {
+    return at::_ops::hardsigmoid_::call(self);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..1d367ba15c0d86c0bb167d175c0c987fe7473bdd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardsigmoid_backward_ops.h>
+
+namespace at {
+
+
+// aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self) {
+    return at::_ops::hardsigmoid_backward_grad_input::call(grad_output, self, grad_input);
+}
+// aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) {
+    return at::_ops::hardsigmoid_backward_grad_input::call(grad_output, self, grad_input);
+}
+
+// aten::hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor
+inline at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self) {
+    return at::_ops::hardsigmoid_backward::call(grad_output, self);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..38e950a9e74183da370fda5496cec06e932a26d0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..071c9e930bf93ac1cf49abdea85fa0e551745093
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ddedaf4cb1de8e242b8313803308e3c73eb75a42
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..3851f1d07643db07b11b912f7aa8386e10d53ecd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_hardsigmoid_backward : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & grad_output, const at::Tensor & self);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4de83514317b1f429fce7c809a5db850a1f58859
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_meta_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..387902a87bbb0fc83e2e0eee66d98c9c3d7b11da
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/hardsigmoid_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_hardsigmoid_backward_out : public at::meta::structured_hardsigmoid_backward {
+void impl(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..638ea9e6d4c555910efd2fbd685f3ee30559c12a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardsigmoid_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardsigmoid_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input);
+};
+
+struct TORCH_API hardsigmoid_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardsigmoid_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4fbd4a144d95ad8c8fe8aa7b9fc496df7dde1b1e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor hardsigmoid(const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5b243a7a623184634d1aad1da0af8b690c70521a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardsigmoid(const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..642140c2e920127aa6d870cf48a07eef153b1213
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardsigmoid(const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..2adb1b7959e5e9097e388c0ea27506b7ffd47677
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta.h
@@ -0,0 +1,27 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeMetaFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/TensorIterator.h>
+#include <ATen/TensorMeta.h>
+#include <tuple>
+#include <vector>
+
+namespace at {
+namespace meta {
+
+struct TORCH_API structured_hardsigmoid : public TensorIteratorBase {
+    
+    
+    void meta(const at::Tensor & self);
+};
+
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b91f096e0a72beb6fc978452c7af98ffd27fd1fd
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor hardsigmoid(const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..69a25c78319abd9c45e9cd8c7680dd34d191766f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_native.h
@@ -0,0 +1,25 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+#include <ATen/ops/hardsigmoid_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_hardsigmoid_out : public at::meta::structured_hardsigmoid {
+void impl(const at::Tensor & self, const at::Tensor & out);
+};
+TORCH_API at::Tensor hardsigmoid_quantized_cpu(const at::Tensor & self);
+TORCH_API at::Tensor & hardsigmoid_out_quantized_cpu(const at::Tensor & self, at::Tensor & out);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..f77c73418190b123097730322c9adb48f71d1308
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardsigmoid_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardsigmoid_out {
+  using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardsigmoid";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hardsigmoid.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
+};
+
+struct TORCH_API hardsigmoid {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardsigmoid";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardsigmoid(Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+struct TORCH_API hardsigmoid_ {
+  using schema = at::Tensor & (at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardsigmoid_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardsigmoid_(Tensor(a!) self) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish.h
new file mode 100644
index 0000000000000000000000000000000000000000..db48503ecafbe301ad41cdcac3846c38a74b9669
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardswish_ops.h>
+
+namespace at {
+
+
+// aten::hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardswish_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::hardswish_out::call(self, out);
+}
+// aten::hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardswish_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::hardswish_out::call(self, out);
+}
+
+// aten::hardswish(Tensor self) -> Tensor
+inline at::Tensor hardswish(const at::Tensor & self) {
+    return at::_ops::hardswish::call(self);
+}
+
+// aten::hardswish_(Tensor(a!) self) -> Tensor(a!)
+inline at::Tensor & hardswish_(at::Tensor & self) {
+    return at::_ops::hardswish_::call(self);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..65d3357987502c73e8ab39babc5f318e57eff3dc
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardswish_backward_ops.h>
+
+namespace at {
+
+
+// aten::hardswish_backward(Tensor grad_output, Tensor self) -> Tensor
+inline at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self) {
+    return at::_ops::hardswish_backward::call(grad_output, self);
+}
+
+// aten::hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardswish_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self) {
+    return at::_ops::hardswish_backward_out::call(grad_output, self, out);
+}
+// aten::hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardswish_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::hardswish_backward_out::call(grad_output, self, out);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_compositeexplicitautograd_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5630a0560540fa2db05115e868a4eb560172d067
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_compositeexplicitautograd_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautograd {
+
+TORCH_API at::Tensor & hardswish_backward_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5bfedcad5b6c885e68c1510406d04f33bccdb66a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cpu_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fa6dab7b19b1b19e6c9f69bd2fe56334229a3aa7
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_cuda_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..959fa22250bebcc516c7fface2d0e9218132fa12
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor & hardswish_backward_out(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..d3e9826d018543e909dd3d33623f6f8e51fec9a5
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardswish_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardswish_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardswish_backward(Tensor grad_output, Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self);
+};
+
+struct TORCH_API hardswish_backward_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardswish_backward";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hardswish_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d4793bce95907be7bab651ba176c568b5ed02e1e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardswish(const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardswish_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0f29b0293645726c227b2264e4eaf866a1e179a4
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardswish(const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardswish_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6742cd451354901b1bf59404bcac68e1de9962a3
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_meta_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor & hardswish_(at::Tensor & self);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..32efe4cd7cf26bb2768bf5fa978bd650c24302f9
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_native.h
@@ -0,0 +1,23 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hardswish(const at::Tensor & self);
+TORCH_API at::Tensor & hardswish_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & hardswish_(at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..15484950a0ad64a825195010d374c88a87280a3d
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardswish_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardswish_out {
+  using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardswish";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
+};
+
+struct TORCH_API hardswish {
+  using schema = at::Tensor (const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardswish";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardswish(Tensor self) -> Tensor";
+  static at::Tensor call(const at::Tensor & self);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
+};
+
+struct TORCH_API hardswish_ {
+  using schema = at::Tensor & (at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardswish_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardswish_(Tensor(a!) self) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.h
new file mode 100644
index 0000000000000000000000000000000000000000..8c9971767b87d5cc8672885b78358f1d8ad51715
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh.h
@@ -0,0 +1,44 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardtanh_ops.h>
+
+namespace at {
+
+
+// aten::hardtanh.out(Tensor self, Scalar min_val=-1, Scalar max_val=1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) {
+    return at::_ops::hardtanh_out::call(self, min_val, max_val, out);
+}
+// aten::hardtanh.out(Tensor self, Scalar min_val=-1, Scalar max_val=1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out) {
+    return at::_ops::hardtanh_out::call(self, min_val, max_val, out);
+}
+
+// aten::hardtanh(Tensor self, Scalar min_val=-1, Scalar max_val=1) -> Tensor
+inline at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) {
+    return at::_ops::hardtanh::call(self, min_val, max_val);
+}
+
+// aten::hardtanh_(Tensor(a!) self, Scalar min_val=-1, Scalar max_val=1) -> Tensor(a!)
+inline at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1) {
+    return at::_ops::hardtanh_::call(self, min_val, max_val);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..f18bbe596dc87ac1b4146feaf9038a699a7e6b00
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hardtanh_backward_ops.h>
+
+namespace at {
+
+
+// aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) {
+    return at::_ops::hardtanh_backward_grad_input::call(grad_output, self, min_val, max_val, grad_input);
+}
+// aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input) {
+    return at::_ops::hardtanh_backward_grad_input::call(grad_output, self, min_val, max_val, grad_input);
+}
+
+// aten::hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor
+inline at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) {
+    return at::_ops::hardtanh_backward::call(grad_output, self, min_val, max_val);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..46aae89384310e93a51ad04c0626b6c782ad745c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cpu_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+TORCH_API at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+TORCH_API at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c17b850d85b8b28e488a54b8875aeaeac8e15023
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_cuda_dispatch.h
@@ -0,0 +1,25 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+TORCH_API at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+TORCH_API at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..462896c61f42b57b72b25f8a73fe5f0eaa4790b6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_native.h
@@ -0,0 +1,22 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+TORCH_API at::Tensor & hardtanh_backward_out(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..096a736ed0d53e29e00dfb03e249a4e6981830b6
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_backward_ops.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardtanh_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardtanh_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input);
+};
+
+struct TORCH_API hardtanh_backward {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardtanh_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..90e05ba52039c823736375263b44bd6106bddf98
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..38b0c66ba237f53279c6efc9faeb71ae75a4afd0
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..726e9613e9aedf34c3a673a556b41405e6a2829c
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_meta_dispatch.h
@@ -0,0 +1,23 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..408220c832c62e86e86e36aebfb89958fa8c2025
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_native.h
@@ -0,0 +1,26 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_out(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor hardtanh_quantized_cpu(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+TORCH_API at::Tensor & hardtanh_out_quantized_cpu(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+TORCH_API at::Tensor & hardtanh_quantized_cpu_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..8f8a948ce867e4490a57a04b16bbbf1c7948563a
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hardtanh_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API hardtanh_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardtanh";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "hardtanh.out(Tensor self, Scalar min_val=-1, Scalar max_val=1, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out);
+};
+
+struct TORCH_API hardtanh {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardtanh";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardtanh(Tensor self, Scalar min_val=-1, Scalar max_val=1) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+};
+
+struct TORCH_API hardtanh_ {
+  using schema = at::Tensor & (at::Tensor &, const at::Scalar &, const at::Scalar &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::hardtanh_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "hardtanh_(Tensor(a!) self, Scalar min_val=-1, Scalar max_val=1) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..39c520468b9d3671e6a5e847d0488e4d2a61635f
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_compositeexplicitautogradnonfunctional_dispatch.h
@@ -0,0 +1,24 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace compositeexplicitautogradnonfunctional {
+
+TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..89834dee1d41873ba12d2cb18b059c006bf75b4e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out);
+TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c28380986264e55a7c971fa47cc11537ce793250
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out);
+TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values);
+
+} // namespace cuda
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2e980bb6084f9335285247d1f3e3ea7c3d6ae624
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_meta_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace meta {
+
+TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values);
+TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out);
+TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values);
+
+} // namespace meta
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_ops.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..a94a49152aeb72f8283411169d401bad5db46b5e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/heaviside_ops.h
@@ -0,0 +1,50 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <tuple>
+#include <vector>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+namespace _ops {
+
+
+struct TORCH_API heaviside_out {
+  using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::heaviside";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, const at::Tensor & values, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & values, at::Tensor & out);
+};
+
+struct TORCH_API heaviside {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::heaviside";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "heaviside(Tensor self, Tensor values) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, const at::Tensor & values);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & values);
+};
+
+struct TORCH_API heaviside_ {
+  using schema = at::Tensor & (at::Tensor &, const at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::heaviside_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "heaviside_(Tensor(a!) self, Tensor values) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, const at::Tensor & values);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & values);
+};
+
+}} // namespace at::_ops
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss.h
new file mode 100644
index 0000000000000000000000000000000000000000..3cc7f671dc8c5dd18eff078076f428061258b382
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/hinge_embedding_loss_ops.h>
+
+namespace at {
+
+
+// aten::hinge_embedding_loss(Tensor self, Tensor target, float margin=1.0, int reduction=Mean) -> Tensor
+inline at::Tensor hinge_embedding_loss(const at::Tensor & self, const at::Tensor & target, double margin=1.0, int64_t reduction=at::Reduction::Mean) {
+    return at::_ops::hinge_embedding_loss::call(self, target, margin, reduction);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_native.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..80b70c1a1a4a27b896fe8e4446bd4895c70bfdb8
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/hinge_embedding_loss_native.h
@@ -0,0 +1,21 @@
+#pragma once
+
+// @generated by torchgen/gen.py from NativeFunction.h
+
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+#include <c10/core/QScheme.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <tuple>
+#include <vector>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor hinge_embedding_loss(const at::Tensor & self, const at::Tensor & target, double margin=1.0, int64_t reduction=at::Reduction::Mean);
+} // namespace native
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/histc.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/histc.h
new file mode 100644
index 0000000000000000000000000000000000000000..e4744841bba93e429f84064d60f7c979aa718631
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/histc.h
@@ -0,0 +1,39 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/histc_ops.h>
+
+namespace at {
+
+
+// aten::histc.out(Tensor self, int bins=100, Scalar min=0, Scalar max=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & histc_out(at::Tensor & out, const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0) {
+    return at::_ops::histc_out::call(self, bins, min, max, out);
+}
+// aten::histc.out(Tensor self, int bins=100, Scalar min=0, Scalar max=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & histc_outf(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, at::Tensor & out) {
+    return at::_ops::histc_out::call(self, bins, min, max, out);
+}
+
+// aten::histc(Tensor self, int bins=100, Scalar min=0, Scalar max=0) -> Tensor
+inline at::Tensor histc(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0) {
+    return at::_ops::histc::call(self, bins, min, max);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss.h
new file mode 100644
index 0000000000000000000000000000000000000000..159d9b7c143b2bf1b7dabdf89f2b06e939bf5833
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/l1_loss.h
@@ -0,0 +1,30 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Function.h
+
+#include <ATen/Context.h>
+#include <ATen/DeviceGuard.h>
+#include <ATen/TensorUtils.h>
+#include <ATen/TracerMode.h>
+#include <ATen/core/Generator.h>
+#include <ATen/core/Reduction.h>
+#include <ATen/core/Tensor.h>
+#include <c10/core/Scalar.h>
+#include <c10/core/Storage.h>
+#include <c10/core/TensorOptions.h>
+#include <c10/util/Deprecated.h>
+#include <optional>
+
+
+
+#include <ATen/ops/l1_loss_ops.h>
+
+namespace at {
+
+
+// aten::l1_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor
+inline at::Tensor l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) {
+    return at::_ops::l1_loss::call(self, target, reduction);
+}
+
+}
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cpu_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9a0f37286cf8a364a7ce77c54dfd2e9dc4352b8e
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cpu_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cpu {
+
+TORCH_API at::Tensor lgamma(const at::Tensor & self);
+TORCH_API at::Tensor & lgamma_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & lgamma_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & lgamma_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cuda_dispatch.h b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5895ca6f884253d6d07434b43e8276e7baf979a1
--- /dev/null
+++ b/env_gptq3/lib/python3.12/site-packages/torch/include/ATen/ops/lgamma_cuda_dispatch.h
@@ -0,0 +1,26 @@
+#pragma once
+// @generated by torchgen/gen.py from DispatchKeyFunction.h
+
+// NB: The implementing C++ file is RegisterDispatchKey.cpp
+
+// The only #includes we need are for custom classes that have defaults in the C++ API
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/Scalar.h>
+#include <ATen/core/Reduction.h>
+
+// Forward declarations of any types needed in the operator signatures.
+// We can't directly include these classes because it will cause circular include dependencies.
+// This file is included by TensorBody.h, which defines the Tensor class.
+#include <ATen/core/ATen_fwd.h>
+
+namespace at {
+
+namespace cuda {
+
+TORCH_API at::Tensor lgamma(const at::Tensor & self);
+TORCH_API at::Tensor & lgamma_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & lgamma_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & lgamma_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at