diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..113a55068fb5dfb1592dddec7319c027206244fe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_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 to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional<int64_t> dense_dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..9363867968ab8d479b8c21c61449318d47658625
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 to_sparse_bsr {
+  using schema = at::Tensor (const at::Tensor &, at::IntArrayRef, ::std::optional<int64_t>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::to_sparse_bsr";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional<int64_t> dense_dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, ::std::optional<int64_t> dense_dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..497d56ea431c89721a8af7046cc4e06045fbc82a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_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 to_sparse(const at::Tensor & self, int64_t sparse_dim);
+TORCH_API at::Tensor to_sparse(const at::Tensor & self, ::std::optional<at::Layout> layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional<int64_t> dense_dim=::std::nullopt);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc.h
new file mode 100644
index 0000000000000000000000000000000000000000..e7ffe673d6cbc5d97edb5f5a98c8a2cc34eaff1d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc.h
@@ -0,0 +1,27 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/to_sparse_csc_ops.h>
+
+namespace at {
+
+
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fb276b6c73c907fcb1cacddeddb9a8f712eab17e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_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 to_sparse_csc(const at::Tensor & self, ::std::optional<int64_t> dense_dim=::std::nullopt);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..4d70f49333a0dbc3c0caadb0dbee43b8d2104e73
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_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 to_sparse_csc(const at::Tensor & self, ::std::optional<int64_t> dense_dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..92a4ce4b34bb4044bbf58c8ac8c4d1cdba48552d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csc_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 to_sparse_csc {
+  using schema = at::Tensor (const at::Tensor &, ::std::optional<int64_t>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::to_sparse_csc";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, ::std::optional<int64_t> dense_dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<int64_t> dense_dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr.h
new file mode 100644
index 0000000000000000000000000000000000000000..50d67286a075dd3bd582e600858e11c266e34502
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr.h
@@ -0,0 +1,27 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/to_sparse_csr_ops.h>
+
+namespace at {
+
+
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4be401666a1d610ea7b20ff0f5e4108c1ac28448
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_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 to_sparse_csr(const at::Tensor & self, ::std::optional<int64_t> dense_dim=::std::nullopt);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8584e9beb8632230facb2b31ae9b1352014d9fb2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_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 to_sparse_csr(const at::Tensor & self, ::std::optional<int64_t> dense_dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..f981515afc597aebbe3fd5de092c20dfd4dc0672
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_csr_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 to_sparse_csr {
+  using schema = at::Tensor (const at::Tensor &, ::std::optional<int64_t>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::to_sparse_csr";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, ::std::optional<int64_t> dense_dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<int64_t> dense_dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..ae45fb4d72460b100e16be3a71c8a0de830bcd13
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_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 to_sparse(const at::Tensor & self, int64_t sparse_dim);
+TORCH_API at::Tensor to_sparse(const at::Tensor & self, ::std::optional<at::Layout> layout=::std::nullopt, at::OptionalIntArrayRef blocksize=::std::nullopt, ::std::optional<int64_t> dense_dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..1bff1e9368b9f97f57bc0536a59201653e3fa0ef
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 to_sparse_sparse_dim {
+  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::to_sparse";
+  static constexpr const char* overload_name = "sparse_dim";
+  static constexpr const char* schema_str = "to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t sparse_dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sparse_dim);
+};
+
+struct TORCH_API to_sparse {
+  using schema = at::Tensor (const at::Tensor &, ::std::optional<at::Layout>, at::OptionalIntArrayRef, ::std::optional<int64_t>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::to_sparse";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, ::std::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, ::std::optional<int64_t> dense_dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, ::std::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, ::std::optional<int64_t> dense_dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk.h
new file mode 100644
index 0000000000000000000000000000000000000000..fa4058ca61c31bcbffc4ec982b94cb1e334fa036
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/topk_ops.h>
+
+namespace at {
+
+
+// aten::topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
+inline ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+  }
+}
+
+// aten::topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
+inline ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+  }
+}
+
+// aten::topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
+inline ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+  }
+}
+
+// aten::topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
+inline ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices) {
+    return at::_ops::topk_values::call(self, k, dim, largest, sorted, values, indices);
+  }
+}
+
+// aten::topk(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
+inline ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk::call(self, k, dim, largest, sorted);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk::call(self, k, dim, largest, sorted);
+  }
+}
+
+// aten::topk(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
+inline ::std::tuple<at::Tensor,at::Tensor> topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk::call(self, k, dim, largest, sorted);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true) {
+    return at::_ops::topk::call(self, k, dim, largest, sorted);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe9167f80f33edb9dc1d897e0a2053a6eee6deee
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_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 ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ce1ef1ebe2d41f868691fb044a5514cee9baf660
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cpu_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 cpu {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3b4c4f5d5e18220c58c72d8c5b8947d0a9022c8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_cuda_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 cuda {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..96b3345f38d41a62e4b49b8c7d8e65dff34b66ba
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_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_topk : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..484d95c32872e5d10ead57b5aea9ed548c53c272
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_meta_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 meta {
+
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk_symint(const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::SymInt k, int64_t dim=-1, bool largest=true, bool sorted=true);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> topk_symint_outf(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..f808898ae57d9f374dcd7820c0eddea3b2cb4f8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_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>
+#include <ATen/ops/topk_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_topk_out_cpu : public at::meta::structured_topk {
+void impl(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, const at::Tensor & values, const at::Tensor & indices);
+};
+struct TORCH_API structured_topk_out_cuda : public at::meta::structured_topk {
+void impl(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, const at::Tensor & values, const at::Tensor & indices);
+};
+TORCH_API ::std::tuple<at::Tensor,at::Tensor> topk_quantized_cpu(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6896fe5484da691b54e750eaea57c793ba67bcb2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/topk_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 topk_values {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, c10::SymInt, int64_t, bool, bool, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::topk";
+  static constexpr const char* overload_name = "values";
+  static constexpr const char* schema_str = "topk.values(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices);
+};
+
+struct TORCH_API topk {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, c10::SymInt, int64_t, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::topk";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "topk(Tensor self, SymInt k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt k, int64_t dim, bool largest, bool sorted);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace.h
new file mode 100644
index 0000000000000000000000000000000000000000..ef88ac602237b549b5b91e5b486702b59eea5f7c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/trace_ops.h>
+
+namespace at {
+
+
+// aten::trace(Tensor self) -> Tensor
+inline at::Tensor trace(const at::Tensor & self) {
+    return at::_ops::trace::call(self);
+}
+
+// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & trace_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::trace_out::call(self, out);
+}
+// aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & trace_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::trace_out::call(self, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..bcf971a4b7601d340f97b40fd4c060803b41801e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward.h
@@ -0,0 +1,48 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/trace_backward_ops.h>
+
+namespace at {
+
+
+// aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor
+inline at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) {
+    return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes));
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor trace_backward(const at::Tensor & grad, at::IntArrayRef sizes) {
+    return at::_ops::trace_backward::call(grad, c10::fromIntArrayRefSlow(sizes));
+  }
+}
+
+// aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor
+inline at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes) {
+    return at::_ops::trace_backward::call(grad, sizes);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor trace_backward(const at::Tensor & grad, c10::SymIntArrayRef sizes) {
+    return at::_ops::trace_backward::call(grad, sizes);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5e95242aa2af6716eb71736e1bc4211e34276502
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_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 trace_backward(const at::Tensor & grad, at::IntArrayRef sizes);
+TORCH_API at::Tensor trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..fb8066ac50c9c6ee8d2282caf1c8502259e1a29a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 trace_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef sizes);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ee949543966e7c0adbb97d749c1bf65bfb984bcf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_backward_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 trace_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::trace_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "trace_backward(Tensor grad, SymInt[] sizes) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad, c10::SymIntArrayRef sizes);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef sizes);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..108adcdabf633c78fa8191faadf2edea6a4fd1b2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 & trace_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & trace_outf(const at::Tensor & self, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1d87e5101da56c8087d383f7ba76981d8c2284f6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 trace(const at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7ca8fd616d3310fc59bb75cb6e39a14252390bf4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 trace(const at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..2c1ff07047bc553741cbc90511ba7a9f518aa24a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_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 & trace_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor trace_cpu(const at::Tensor & self);
+TORCH_API at::Tensor trace_cuda(const at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6271f1aa9f7dfadf8ac32008b90c47ba395cc0d1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trace_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 trace {
+  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::trace";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "trace(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 trace_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::trace";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "trace.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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose.h
new file mode 100644
index 0000000000000000000000000000000000000000..63a47154d965681f421add3f57710d55d336b072
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose.h
@@ -0,0 +1,36 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/transpose_ops.h>
+
+namespace at {
+
+
+// aten::transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a)
+inline at::Tensor transpose(const at::Tensor & self, int64_t dim0, int64_t dim1) {
+    return at::_ops::transpose_int::call(self, dim0, dim1);
+}
+
+// aten::transpose.Dimname(Tensor(a) self, Dimname dim0, Dimname dim1) -> Tensor(a)
+inline at::Tensor transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1) {
+    return at::_ops::transpose_Dimname::call(self, dim0, dim1);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..cc30daf79f5429d8e8f7bcaa1bb562b08d7f484d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_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 transpose(const at::Tensor & self, int64_t dim0, int64_t dim1);
+TORCH_API at::Tensor & transpose_(at::Tensor & self, int64_t dim0, int64_t dim1);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..30fe07181bba8cd6093401257cb5664f86e9ca6d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_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 transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy.h
new file mode 100644
index 0000000000000000000000000000000000000000..b1e644fd53eef41c089c151a1cf2ec0b19719af0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/transpose_copy_ops.h>
+
+namespace at {
+
+
+// aten::transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor
+inline at::Tensor transpose_copy(const at::Tensor & self, int64_t dim0, int64_t dim1) {
+    return at::_ops::transpose_copy_int::call(self, dim0, dim1);
+}
+
+// aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & transpose_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim0, int64_t dim1) {
+    return at::_ops::transpose_copy_int_out::call(self, dim0, dim1, out);
+}
+// aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & transpose_copy_outf(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out) {
+    return at::_ops::transpose_copy_int_out::call(self, dim0, dim1, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..973e68ce6c1f7b0de1d60b7ee7aa7aba025e215f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_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 & transpose_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim0, int64_t dim1);
+TORCH_API at::Tensor & transpose_copy_outf(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..f6b25fb8f14bba9b852a8d277939ae225a89085d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_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 transpose_copy(const at::Tensor & self, int64_t dim0, int64_t dim1);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..9601aed21044fda2adacc5d5b0b53436e690ee8c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_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 & transpose_copy_int_out(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out);
+TORCH_API at::Tensor transpose_copy_int(const at::Tensor & self, int64_t dim0, int64_t dim1);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..924f1fe8b6b4b0801036e3570e5c4449a81e0cc4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_copy_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 transpose_copy_int {
+  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::transpose_copy";
+  static constexpr const char* overload_name = "int";
+  static constexpr const char* schema_str = "transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1);
+};
+
+struct TORCH_API transpose_copy_int_out {
+  using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::transpose_copy";
+  static constexpr const char* overload_name = "int_out";
+  static constexpr const char* schema_str = "transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..e72f7a8b1ec1cc415a40ae4e276b60140b332325
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_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 transpose(const at::Tensor & self, int64_t dim0, int64_t dim1);
+TORCH_API at::Tensor transpose_nested(const at::Tensor & self, int64_t dim0, int64_t dim1);
+TORCH_API at::Tensor & transpose_(at::Tensor & self, int64_t dim0, int64_t dim1);
+TORCH_API at::Tensor transpose(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..4d22ee1aba5b5b914a7f1de14fd7ab0dacfc8668
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/transpose_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 transpose_int {
+  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::transpose";
+  static constexpr const char* overload_name = "int";
+  static constexpr const char* schema_str = "transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a)";
+  static at::Tensor call(const at::Tensor & self, int64_t dim0, int64_t dim1);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1);
+};
+
+struct TORCH_API transpose_Dimname {
+  using schema = at::Tensor (const at::Tensor &, at::Dimname, at::Dimname);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::transpose";
+  static constexpr const char* overload_name = "Dimname";
+  static constexpr const char* schema_str = "transpose.Dimname(Tensor(a) self, Dimname dim0, Dimname dim1) -> Tensor(a)";
+  static at::Tensor call(const at::Tensor & self, at::Dimname dim0, at::Dimname dim1);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim0, at::Dimname dim1);
+};
+
+struct TORCH_API transpose_ {
+  using schema = at::Tensor & (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::transpose_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "transpose_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, int64_t dim0, int64_t dim1);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim0, int64_t dim1);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid.h
new file mode 100644
index 0000000000000000000000000000000000000000..1a048687dea488c2e6610970556dd1204b202844
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid.h
@@ -0,0 +1,36 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/trapezoid_ops.h>
+
+namespace at {
+
+
+// aten::trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor
+inline at::Tensor trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1) {
+    return at::_ops::trapezoid_x::call(y, x, dim);
+}
+
+// aten::trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor
+inline at::Tensor trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-1) {
+    return at::_ops::trapezoid_dx::call(y, dx, dim);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c2f7f8765e3b6e9c56a306dc9f9e6c57fea6f874
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_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 trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1);
+TORCH_API at::Tensor trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-1);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..741b94b3cdd90d6a2026ca513137bf8bc11b532e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_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 trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1);
+TORCH_API at::Tensor trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-1);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..9aead712d02e50f0deb57581748e73925dc994a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapezoid_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 trapezoid_x {
+  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::trapezoid";
+  static constexpr const char* overload_name = "x";
+  static constexpr const char* schema_str = "trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor";
+  static at::Tensor call(const at::Tensor & y, const at::Tensor & x, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim);
+};
+
+struct TORCH_API trapezoid_dx {
+  using schema = at::Tensor (const at::Tensor &, const at::Scalar &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::trapezoid";
+  static constexpr const char* overload_name = "dx";
+  static constexpr const char* schema_str = "trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor";
+  static at::Tensor call(const at::Tensor & y, const at::Scalar & dx, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Scalar & dx, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz.h
new file mode 100644
index 0000000000000000000000000000000000000000..23514b8468634686abc201162ea6d4c6d3461a53
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz.h
@@ -0,0 +1,36 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/trapz_ops.h>
+
+namespace at {
+
+
+// aten::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor
+inline at::Tensor trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1) {
+    return at::_ops::trapz_x::call(y, x, dim);
+}
+
+// aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor
+inline at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1) {
+    return at::_ops::trapz_dx::call(y, dx, dim);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4dfe5056e4d41771e59fa82ad47cdd68456127f1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_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 trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1);
+TORCH_API at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..9dc40b45cecc91a6bef3bc064a6c6ed7f482829d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_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 trapz(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1);
+TORCH_API at::Tensor trapz(const at::Tensor & y, double dx=1, int64_t dim=-1);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..37e5b5db6e927b33a175b9f11454a51ec81ff87d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trapz_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 trapz_x {
+  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::trapz";
+  static constexpr const char* overload_name = "x";
+  static constexpr const char* schema_str = "trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor";
+  static at::Tensor call(const at::Tensor & y, const at::Tensor & x, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim);
+};
+
+struct TORCH_API trapz_dx {
+  using schema = at::Tensor (const at::Tensor &, double, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::trapz";
+  static constexpr const char* overload_name = "dx";
+  static constexpr const char* schema_str = "trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor";
+  static at::Tensor call(const at::Tensor & y, double dx, int64_t dim);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, double dx, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve.h
new file mode 100644
index 0000000000000000000000000000000000000000..425e7d9b2dbb010ce3d785b46cee4c3493513876
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/triangular_solve_ops.h>
+
+namespace at {
+
+
+// aten::triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient)
+inline ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false) {
+    return at::_ops::triangular_solve_X::call(self, A, upper, transpose, unitriangular, X, M);
+}
+// aten::triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient)
+inline ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M) {
+    return at::_ops::triangular_solve_X::call(self, A, upper, transpose, unitriangular, X, M);
+}
+
+// aten::triangular_solve(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False) -> (Tensor solution, Tensor cloned_coefficient)
+inline ::std::tuple<at::Tensor,at::Tensor> triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false) {
+    return at::_ops::triangular_solve::call(self, A, upper, transpose, unitriangular);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6e2669da969287c79c9ecca69399b692a3d2ca1b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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> triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4ea6b3f2c2acb5adf3e3b72e192265ff8d11ccd1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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> triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..bf2f57766b0c156aae72d26d376d7d22733ddba8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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> triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..5137d51532afc8365083ad0596b5f05d86bae30b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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_triangular_solve : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..615866269f1ff66aae727d7e4c392bf1d2c18a05
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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> triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..df0ede9e827d73c1319f98c5f3bc88c3bf4a919d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_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/triangular_solve_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_triangular_solve_out : public at::meta::structured_triangular_solve {
+void impl(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, const at::Tensor & X, const at::Tensor & M);
+};
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> triangular_solve_out_sparse_csr_cuda(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..715b1e52ba15c2fad9b07f040de489d283ab2f4d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triangular_solve_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 triangular_solve_X {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &> (const at::Tensor &, const at::Tensor &, bool, bool, bool, at::Tensor &, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::triangular_solve";
+  static constexpr const char* overload_name = "X";
+  static constexpr const char* schema_str = "triangular_solve.X(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False, *, Tensor(a!) X, Tensor(b!) M) -> (Tensor(a!) solution, Tensor(b!) cloned_coefficient)";
+  static ::std::tuple<at::Tensor &,at::Tensor &> call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+  static ::std::tuple<at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M);
+};
+
+struct TORCH_API triangular_solve {
+  using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, const at::Tensor &, bool, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::triangular_solve";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "triangular_solve(Tensor self, Tensor A, bool upper=True, bool transpose=False, bool unitriangular=False) -> (Tensor solution, Tensor cloned_coefficient)";
+  static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular);
+  static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril.h
new file mode 100644
index 0000000000000000000000000000000000000000..5588e3f96bc4942eb3e983f992291f58ed4f78a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/tril_ops.h>
+
+namespace at {
+
+
+// aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0) {
+    return at::_ops::tril_out::call(self, diagonal, out);
+}
+// aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out) {
+    return at::_ops::tril_out::call(self, diagonal, out);
+}
+
+// aten::tril(Tensor self, int diagonal=0) -> Tensor
+inline at::Tensor tril(const at::Tensor & self, int64_t diagonal=0) {
+    return at::_ops::tril::call(self, diagonal);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3dee6f46b9ab4f6ebaa7afcc0d22a98cd66d42d4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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 tril(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1b9e1fe036a0b8c9e09aa1050bf4c192cb9c7742
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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 tril(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0fbfeb0c4047681ade10cf61c1408749b6fdece2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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 tril(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices.h
new file mode 100644
index 0000000000000000000000000000000000000000..10f93236447fc36b09a55e6ab23e3a97d7491921
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices.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 <string_view>
+
+
+
+#include <ATen/ops/tril_indices_ops.h>
+
+namespace at {
+
+
+// aten::tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong) {
+    return at::_ops::tril_indices::call(row, col, offset, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::tril_indices::call(row, col, offset, dtype, layout, device, pin_memory);
+}
+
+// aten::tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & tril_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0) {
+    return at::_ops::tril_indices_out::call(row, col, offset, out);
+}
+// aten::tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & tril_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out) {
+    return at::_ops::tril_indices_out::call(row, col, offset, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..72827b1e7a2cc9c1c4d695035fb622f310f29cdf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_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 & tril_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0);
+TORCH_API at::Tensor & tril_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e000b65aa077989b915be4c733b3c34b82f3691e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_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 tril_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong);
+TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset, ::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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..22378108e53f1463b36bbc19037c9a63e23a396e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_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 at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong);
+TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..9a46e9bb9856e20879034a78364f466718d45b8d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_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 & tril_indices_out(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+TORCH_API at::Tensor tril_indices_cpu(int64_t row, int64_t col, int64_t offset=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 tril_indices_cuda(int64_t row, int64_t col, int64_t offset=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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e2a6ddcb7ee873b44d727f0e0889facde2d68030
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_indices_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 tril_indices {
+  using schema = at::Tensor (int64_t, int64_t, 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::tril_indices";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t row, int64_t col, int64_t offset, ::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 row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API tril_indices_out {
+  using schema = at::Tensor & (int64_t, int64_t, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::tril_indices";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..c9481b1a9daca5dffbcab72d4c1c12b3473bca82
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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_tril : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, int64_t diagonal);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..73546783d411935e2414458e84da3d473d05c509
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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 tril(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..a1dea6f0207fbe2ed9ddf9490f6c2d6d0b1ae616
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_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/tril_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_tril_cpu : public at::meta::structured_tril {
+void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out);
+};
+struct TORCH_API structured_tril_cuda : public at::meta::structured_tril {
+void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..435cfe9ad2e786116c7f0e1d87131bd9abb39b96
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/tril_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 tril_ {
+  using schema = at::Tensor & (at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::tril_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "tril_(Tensor(a!) self, int diagonal=0) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, int64_t diagonal);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t diagonal);
+};
+
+struct TORCH_API tril_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::tril";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+};
+
+struct TORCH_API tril {
+  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::tril";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "tril(Tensor self, int diagonal=0) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t diagonal);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss.h
new file mode 100644
index 0000000000000000000000000000000000000000..a07082a69773fc8b3d098ae8eb1268709be3f53e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss.h
@@ -0,0 +1,31 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/triplet_margin_loss_ops.h>
+
+namespace at {
+
+
+// aten::triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor
+inline at::Tensor triplet_margin_loss(const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin=1.0, double p=2, double eps=1e-06, bool swap=false, int64_t reduction=at::Reduction::Mean) {
+    return at::_ops::triplet_margin_loss::call(anchor, positive, negative, margin, p, eps, swap, reduction);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1e55bb6fc7c2369c4bd2fd380be128d99dc61be2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_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 triplet_margin_loss(const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin=1.0, double p=2, double eps=1e-06, bool swap=false, int64_t reduction=at::Reduction::Mean);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..30854f311cf7b5301a0a7caf128497707e230b77
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_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 triplet_margin_loss(const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin=1.0, double p=2, double eps=1e-06, bool swap=false, int64_t reduction=at::Reduction::Mean);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..48da4587fe8cd48199ec0f087f8f323545a2edb4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 triplet_margin_loss {
+  using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, double, double, bool, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::triplet_margin_loss";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor";
+  static at::Tensor call(const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin, double p, double eps, bool swap, int64_t reduction);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin, double p, double eps, bool swap, int64_t reduction);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu.h
new file mode 100644
index 0000000000000000000000000000000000000000..56b75e8887789648d33dd0e9d562f077a284c53b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/triu_ops.h>
+
+namespace at {
+
+
+// aten::triu.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0) {
+    return at::_ops::triu_out::call(self, diagonal, out);
+}
+// aten::triu.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out) {
+    return at::_ops::triu_out::call(self, diagonal, out);
+}
+
+// aten::triu(Tensor self, int diagonal=0) -> Tensor
+inline at::Tensor triu(const at::Tensor & self, int64_t diagonal=0) {
+    return at::_ops::triu::call(self, diagonal);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..dac4e757fbccaf75d7094e5e88e8faefffa0b689
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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 triu(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..51606a56d17333d1fdb437f094b8a46119bca58b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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 triu(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3a1d23e298a1571c122ee3400c39e54d17f55167
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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 triu(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices.h
new file mode 100644
index 0000000000000000000000000000000000000000..ec199eb082adfd30a15392c5f1ad062657e385d9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices.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 <string_view>
+
+
+
+#include <ATen/ops/triu_indices_ops.h>
+
+namespace at {
+
+
+// aten::triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong) {
+    return at::_ops::triu_indices::call(row, col, offset, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
+}
+// aten::triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
+inline at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
+    return at::_ops::triu_indices::call(row, col, offset, dtype, layout, device, pin_memory);
+}
+
+// aten::triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & triu_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0) {
+    return at::_ops::triu_indices_out::call(row, col, offset, out);
+}
+// aten::triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & triu_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out) {
+    return at::_ops::triu_indices_out::call(row, col, offset, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4f8b922fd1a2d4b97b8322328461c2b5dd528dcc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_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 & triu_indices_out(at::Tensor & out, int64_t row, int64_t col, int64_t offset=0);
+TORCH_API at::Tensor & triu_indices_outf(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..aedc8efc7e51b841a7ed0630efd72e353da1e0e4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_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 triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong);
+TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6841e751ead8d06f66cd8d282bd1185d08524126
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_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 at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong);
+TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..5086cc91f95039dfda0ea4f8a02db62176a33fee
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_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 & triu_indices_out(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+TORCH_API at::Tensor triu_indices_cpu(int64_t row, int64_t col, int64_t offset=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 triu_indices_cuda(int64_t row, int64_t col, int64_t offset=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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..ae0e860bb40503f62694d4c03e00e2b84168dbc1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_indices_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 triu_indices {
+  using schema = at::Tensor (int64_t, int64_t, 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::triu_indices";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor";
+  static at::Tensor call(int64_t row, int64_t col, int64_t offset, ::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 row, int64_t col, int64_t offset, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
+};
+
+struct TORCH_API triu_indices_out {
+  using schema = at::Tensor & (int64_t, int64_t, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::triu_indices";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..76f3358ed578f149a0495a64bdcaf53f0bfe2fbd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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_triu : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, int64_t diagonal);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..287d5d336a5a40a60bb1cf54a0174cd2c3296b39
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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 triu(const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0);
+TORCH_API at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..630d3b0de6ba95926b77a7037d2509424afe2084
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_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/triu_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_triu_cpu : public at::meta::structured_triu {
+void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out);
+};
+struct TORCH_API structured_triu_cuda : public at::meta::structured_triu {
+void impl(const at::Tensor & self, int64_t diagonal, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..4282a1cf4c1520cc606d4923f85b95d846dfe29b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/triu_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 triu_ {
+  using schema = at::Tensor & (at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::triu_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "triu_(Tensor(a!) self, int diagonal=0) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, int64_t diagonal);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t diagonal);
+};
+
+struct TORCH_API triu_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::triu";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "triu.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal, at::Tensor & out);
+};
+
+struct TORCH_API triu {
+  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::triu";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "triu(Tensor self, int diagonal=0) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t diagonal);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide.h
new file mode 100644
index 0000000000000000000000000000000000000000..e7725e5b01a00257d678b6b978a213b49e40a9ab
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide.h
@@ -0,0 +1,45 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/true_divide_ops.h>
+
+namespace at {
+
+
+// aten::true_divide.Tensor(Tensor self, Tensor other) -> Tensor
+inline at::Tensor true_divide(const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::true_divide_Tensor::call(self, other);
+}
+
+// aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & true_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) {
+    return at::_ops::true_divide_out::call(self, other, out);
+}
+// aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & true_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) {
+    return at::_ops::true_divide_out::call(self, other, out);
+}
+
+// aten::true_divide.Scalar(Tensor self, Scalar other) -> Tensor
+inline at::Tensor true_divide(const at::Tensor & self, const at::Scalar & other) {
+    return at::_ops::true_divide_Scalar::call(self, other);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3672187aeb576cf669fa4e8ceecd45a5dbec356f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_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 true_divide(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & true_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & true_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor true_divide(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Scalar & other);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c12e36d69f97bf66028207ec67e9b77fd4074f57
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_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>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor true_divide(const at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor & true_divide_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
+TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Tensor & other);
+TORCH_API at::Tensor true_divide(const at::Tensor & self, const at::Scalar & other);
+TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Scalar & other);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..0a40802eeb747ce5d0f2046f81e4d69b60b5510e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/true_divide_ops.h
@@ -0,0 +1,73 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 true_divide_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::true_divide";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "true_divide.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 true_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::true_divide_";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "true_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 true_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::true_divide";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "true_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 true_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::true_divide";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "true_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 true_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::true_divide_";
+  static constexpr const char* overload_name = "Scalar";
+  static constexpr const char* schema_str = "true_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);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h
new file mode 100644
index 0000000000000000000000000000000000000000..33b2dcdd19f4224c3333b4174d969c6ee995d914
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc.h
@@ -0,0 +1,45 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/trunc_ops.h>
+
+namespace at {
+
+
+// aten::trunc(Tensor self) -> Tensor
+inline at::Tensor trunc(const at::Tensor & self) {
+    return at::_ops::trunc::call(self);
+}
+
+// aten::trunc_(Tensor(a!) self) -> Tensor(a!)
+inline at::Tensor & trunc_(at::Tensor & self) {
+    return at::_ops::trunc_::call(self);
+}
+
+// aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self) {
+    return at::_ops::trunc_out::call(self, out);
+}
+// aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out) {
+    return at::_ops::trunc_out::call(self, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..88d74afe665d89c2cf18bc0207ac89ce202f6892
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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 trunc(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_(at::Tensor & self);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a165c17de22fdf03517f50674497d7f52dcbd1f5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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 trunc(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & trunc_(at::Tensor & self);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..81f92307c4aead7aa1f466dd68962c87a2383794
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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 trunc(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & trunc_(at::Tensor & self);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..98f6d65f2ca38dea5def738b8781b60714bdb137
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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_trunc : public TensorIteratorBase {
+
+
+    void meta(const at::Tensor & self);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c36aad0d9191c31e729785b461ceb6e2293b7774
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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 trunc(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self);
+TORCH_API at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & trunc_(at::Tensor & self);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..b6714af114464354e693cf2715e10941f8ed5bd6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_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/trunc_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_trunc_out : public at::meta::structured_trunc {
+void impl(const at::Tensor & self, const at::Tensor & out);
+};
+TORCH_API at::Tensor trunc_sparse(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_sparse_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & trunc_sparse_(at::Tensor & self);
+TORCH_API at::Tensor trunc_sparse_csr(const at::Tensor & self);
+TORCH_API at::Tensor & trunc_sparse_csr_out(const at::Tensor & self, at::Tensor & out);
+TORCH_API at::Tensor & trunc_sparse_csr_(at::Tensor & self);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..f0dff5821e6544d81c835670d487a86d9e57309a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/trunc_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 trunc {
+  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::trunc";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "trunc(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 trunc_ {
+  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::trunc_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "trunc_(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 trunc_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::trunc";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "trunc.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/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as.h
new file mode 100644
index 0000000000000000000000000000000000000000..fe73c6fab388c6bc1c6d4bcc09007ad1ae0a288a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as.h
@@ -0,0 +1,27 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/type_as_ops.h>
+
+namespace at {
+
+
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7c3f58b82ca0ad2b82bb4589277ab1d4711729c7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_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 type_as(const at::Tensor & self, const at::Tensor & other);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..3bd6e42629e633015935c62aa33e3fffdd6a457b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_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 type_as(const at::Tensor & self, const at::Tensor & other);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6b23c5d749a47c6c0d494ffa95ddacb00795b88b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/type_as_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 type_as {
+  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::type_as";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "type_as(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);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind.h
new file mode 100644
index 0000000000000000000000000000000000000000..6d69e53d6b2215cb7f27e447939337dcaa95b3f2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind.h
@@ -0,0 +1,36 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unbind_ops.h>
+
+namespace at {
+
+
+// aten::unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[]
+inline ::std::vector<at::Tensor> unbind(const at::Tensor & self, int64_t dim=0) {
+    return at::_ops::unbind_int::call(self, dim);
+}
+
+// aten::unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[]
+inline ::std::vector<at::Tensor> unbind(const at::Tensor & self, at::Dimname dim) {
+    return at::_ops::unbind_Dimname::call(self, dim);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..771af8c02bbbf3a0da35a7f8128c1630af6c12e0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_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::vector<at::Tensor> unbind(const at::Tensor & self, int64_t dim=0);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a43b0dc24081fedc1f04edac2e4b7b521fd40f34
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_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::vector<at::Tensor> unbind(const at::Tensor & self, at::Dimname dim);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.h
new file mode 100644
index 0000000000000000000000000000000000000000..70b9be3c50c5a6355e33646065f2f467634d1ab7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unbind_copy_ops.h>
+
+namespace at {
+
+
+// aten::unbind_copy.int(Tensor self, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unbind_copy(const at::Tensor & self, int64_t dim=0) {
+    return at::_ops::unbind_copy_int::call(self, dim);
+}
+
+// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unbind_copy_out(at::TensorList out, const at::Tensor & self, int64_t dim=0) {
+    return at::_ops::unbind_copy_int_out::call(self, dim, out);
+}
+// aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unbind_copy_outf(const at::Tensor & self, int64_t dim, at::TensorList out) {
+    return at::_ops::unbind_copy_int_out::call(self, dim, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..66be9d3fabf684b97acf382b385ba54d205dec8e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_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 void unbind_copy_out(at::TensorList out, const at::Tensor & self, int64_t dim=0);
+TORCH_API void unbind_copy_outf(const at::Tensor & self, int64_t dim, at::TensorList out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..51983d8d2a7c11aabef3b42cfc868dd86797bd62
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_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::vector<at::Tensor> unbind_copy(const at::Tensor & self, int64_t dim=0);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..3c0668551664fab77506a4e89fcf45a8a55fecd6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_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 void unbind_copy_int_out(const at::Tensor & self, int64_t dim, at::TensorList out);
+TORCH_API ::std::vector<at::Tensor> unbind_copy_int(const at::Tensor & self, int64_t dim=0);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..8bd97f14bac438ef50be873b4edf6f1b4f00ddd6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_copy_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unbind_copy_int {
+  using schema = ::std::vector<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::unbind_copy";
+  static constexpr const char* overload_name = "int";
+  static constexpr const char* schema_str = "unbind_copy.int(Tensor self, int dim=0) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, int64_t dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim);
+};
+
+struct TORCH_API unbind_copy_int_out {
+  using schema = void (const at::Tensor &, int64_t, at::TensorList);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unbind_copy";
+  static constexpr const char* overload_name = "int_out";
+  static constexpr const char* schema_str = "unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> ()";
+  static void call(const at::Tensor & self, int64_t dim, at::TensorList out);
+  static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::TensorList out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..0ede026e9553cd66daa88b1d6fc57d0f8375f250
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_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::vector<at::Tensor> unbind(const at::Tensor & self, int64_t dim=0);
+TORCH_API ::std::vector<at::Tensor> NestedTensor_unbind(const at::Tensor & self, int64_t dim=0);
+TORCH_API ::std::vector<at::Tensor> unbind(const at::Tensor & self, at::Dimname dim);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..1eff47bcc859aabb6d859df7a813fe4ceca08d96
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unbind_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unbind_int {
+  using schema = ::std::vector<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::unbind";
+  static constexpr const char* overload_name = "int";
+  static constexpr const char* schema_str = "unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, int64_t dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim);
+};
+
+struct TORCH_API unbind_Dimname {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::Dimname);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unbind";
+  static constexpr const char* overload_name = "Dimname";
+  static constexpr const char* schema_str = "unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, at::Dimname dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten.h
new file mode 100644
index 0000000000000000000000000000000000000000..cea0410d2eb35b45df1fa2392470b737373ecca4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten.h
@@ -0,0 +1,70 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unflatten_ops.h>
+
+namespace at {
+
+
+// aten::unflatten.int(Tensor(a) self, int dim, SymInt[] sizes) -> Tensor(a)
+inline at::Tensor unflatten(const at::Tensor & self, int64_t dim, at::IntArrayRef sizes) {
+    return at::_ops::unflatten_int::call(self, dim, c10::fromIntArrayRefSlow(sizes));
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor unflatten(const at::Tensor & self, int64_t dim, at::IntArrayRef sizes) {
+    return at::_ops::unflatten_int::call(self, dim, c10::fromIntArrayRefSlow(sizes));
+  }
+}
+
+// aten::unflatten.int(Tensor(a) self, int dim, SymInt[] sizes) -> Tensor(a)
+inline at::Tensor unflatten_symint(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes) {
+    return at::_ops::unflatten_int::call(self, dim, sizes);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor unflatten(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes) {
+    return at::_ops::unflatten_int::call(self, dim, sizes);
+  }
+}
+
+// aten::unflatten.Dimname(Tensor(a) self, Dimname dim, SymInt[] sizes, Dimname[] names) -> Tensor(a)
+inline at::Tensor unflatten(const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names) {
+    return at::_ops::unflatten_Dimname::call(self, dim, c10::fromIntArrayRefSlow(sizes), names);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor unflatten(const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names) {
+    return at::_ops::unflatten_Dimname::call(self, dim, c10::fromIntArrayRefSlow(sizes), names);
+  }
+}
+
+// aten::unflatten.Dimname(Tensor(a) self, Dimname dim, SymInt[] sizes, Dimname[] names) -> Tensor(a)
+inline at::Tensor unflatten_symint(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names) {
+    return at::_ops::unflatten_Dimname::call(self, dim, sizes, names);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor unflatten(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names) {
+    return at::_ops::unflatten_Dimname::call(self, dim, sizes, names);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..983504911a84558096fc5ecb3562aa910cb7b6f3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_compositeimplicitautograd_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 compositeimplicitautograd {
+
+TORCH_API at::Tensor unflatten(const at::Tensor & self, int64_t dim, at::IntArrayRef sizes);
+TORCH_API at::Tensor unflatten_symint(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes);
+TORCH_API at::Tensor unflatten(const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names);
+TORCH_API at::Tensor unflatten_symint(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors.h
new file mode 100644
index 0000000000000000000000000000000000000000..c45faa71d08e553fc174a2bad8434f502aca9919
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors.h
@@ -0,0 +1,31 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unflatten_dense_tensors_ops.h>
+
+namespace at {
+
+
+// aten::unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[]
+inline ::std::vector<at::Tensor> unflatten_dense_tensors(const at::Tensor & flat, at::TensorList tensors) {
+    return at::_ops::unflatten_dense_tensors::call(flat, tensors);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7e4f17fae2975f8b39749708e7ec0fdb386a5b1d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_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::vector<at::Tensor> unflatten_dense_tensors(const at::Tensor & flat, at::TensorList tensors);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..286c395c698d4d559c6316eb2fef957093304e7d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_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::vector<at::Tensor> unflatten_dense_tensors(const at::Tensor & flat, at::TensorList tensors);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..1d31b8d56a73d5c4cb0d99f9678a29911585a92d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unflatten_dense_tensors {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, at::TensorList);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unflatten_dense_tensors";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & flat, at::TensorList tensors);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & flat, at::TensorList tensors);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8bcb61bf9222dbb724b12d8263408f3fcb1adad6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_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 unflatten_symint(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes);
+TORCH_API at::Tensor unflatten_dimname_symint(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e9482c5ade6d3840f8d7b29bd531c7b158bc15b4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unflatten_int {
+  using schema = at::Tensor (const at::Tensor &, int64_t, c10::SymIntArrayRef);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unflatten";
+  static constexpr const char* overload_name = "int";
+  static constexpr const char* schema_str = "unflatten.int(Tensor(a) self, int dim, SymInt[] sizes) -> Tensor(a)";
+  static at::Tensor call(const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymIntArrayRef sizes);
+};
+
+struct TORCH_API unflatten_Dimname {
+  using schema = at::Tensor (const at::Tensor &, at::Dimname, c10::SymIntArrayRef, at::DimnameList);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unflatten";
+  static constexpr const char* overload_name = "Dimname";
+  static constexpr const char* schema_str = "unflatten.Dimname(Tensor(a) self, Dimname dim, SymInt[] sizes, Dimname[] names) -> Tensor(a)";
+  static at::Tensor call(const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::SymIntArrayRef sizes, at::DimnameList names);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold.h
new file mode 100644
index 0000000000000000000000000000000000000000..5daf9fff48c239a61b660c76233b8f68b52587d2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold.h
@@ -0,0 +1,27 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unfold_ops.h>
+
+namespace at {
+
+
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..1ddf28fbda7eebfed2eaf0fdaaaf49eb6be8090f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unfold_backward_ops.h>
+
+namespace at {
+
+
+// aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor
+inline at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step);
+  }
+}
+
+// aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor
+inline at::Tensor unfold_backward_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward::call(grad_in, input_sizes, dim, size, step);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor unfold_backward(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward::call(grad_in, input_sizes, dim, size, step);
+  }
+}
+
+// aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out);
+  }
+}
+
+// aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) {
+    return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) {
+    return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out);
+  }
+}
+
+// aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_backward_symint_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) {
+    return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out);
+  }
+}
+
+// aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_backward_symint_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) {
+    return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) {
+    return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ae4c086404ab3421c8655897022b565b2b8781a0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_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 & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+TORCH_API at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out);
+TORCH_API at::Tensor & unfold_backward_symint_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+TORCH_API at::Tensor & unfold_backward_symint_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7df0e250ab0bf736eaf102a677f00bb04a10ba15
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_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 unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+TORCH_API at::Tensor unfold_backward_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1cc60e3df1507abb4cbd9e14fec6e484540eb44e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_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 at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+TORCH_API at::Tensor unfold_backward_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c0f54ba6f4458e7d5171d53431f2da54147d70f6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_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 & unfold_backward_out_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out);
+TORCH_API at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..2ae2e6ad0badcd02ae1ee88b998a45ffce0ed12c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_backward_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unfold_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, 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::unfold_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step);
+};
+
+struct TORCH_API unfold_backward_out {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, int64_t, int64_t, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unfold_backward";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy.h
new file mode 100644
index 0000000000000000000000000000000000000000..c411e5072c427a902ef0a3b34cf3b29d5706535a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unfold_copy_ops.h>
+
+namespace at {
+
+
+// aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor
+inline at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) {
+    return at::_ops::unfold_copy::call(self, dimension, size, step);
+}
+
+// aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) {
+    return at::_ops::unfold_copy_out::call(self, dimension, size, step, out);
+}
+// aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unfold_copy_outf(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out) {
+    return at::_ops::unfold_copy_out::call(self, dimension, size, step, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3d2b2d72d1002bb2d6cbc98e11f3d9e0c87eb29c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_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 & unfold_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+TORCH_API at::Tensor & unfold_copy_outf(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..83b8cc4e62b2f1f40aa4004d123027ae1222bdfc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_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 unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c2c88cc905fb12a37e99be0c1fbb05fcdfa662e5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_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 & unfold_copy_out(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out);
+TORCH_API at::Tensor unfold_copy(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..3c8a532a14a68721db4e24f95bc5ac7aa3dfcb0f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_copy_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unfold_copy {
+  using schema = at::Tensor (const at::Tensor &, 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::unfold_copy";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+};
+
+struct TORCH_API unfold_copy_out {
+  using schema = at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unfold_copy";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b6940f845cd2ba9d0300001907e23ab542bf56d3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..79ef868b9e7808ad0c0a83e9dc210cdf1d39c8ed
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..568495b7acbb85a6c03bdacc70da5259f14368ef
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..3c442664bdeadb62319c74c64667bbfa03fb37e1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_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 unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..96672fe9ecf45ef4787a885ac0863181dbd6bc73
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unfold {
+  using schema = at::Tensor (const at::Tensor &, 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::unfold";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unfold(Tensor(a) self, int dimension, int size, int step) -> Tensor(a)";
+  static at::Tensor call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.h
new file mode 100644
index 0000000000000000000000000000000000000000..b143fa5e0a83ee17c3ba07f3d19fe1025d44df03
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/uniform_ops.h>
+
+namespace at {
+
+
+// aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & uniform_out(at::Tensor & out, const at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt) {
+    return at::_ops::uniform_out::call(self, from, to, generator, out);
+}
+// aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & uniform_outf(const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator, at::Tensor & out) {
+    return at::_ops::uniform_out::call(self, from, to, generator, out);
+}
+
+// aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor
+inline at::Tensor uniform(const at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt) {
+    return at::_ops::uniform::call(self, from, to, generator);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d320c6372d59bb94bf150f396d6636172a26ea6d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_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 uniform(const at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & uniform_out(at::Tensor & out, const at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & uniform_outf(const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e17a1e82433565be67befe802a9d2b24d073a821
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_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 & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7b003b202de45f0a2e30782cd1394df41b18bfb2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_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 & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..45d14193bf0691b0560665a18ef806eef408d909
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_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 & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..f2d831295d7ca7babdc51a8b918284605b832410
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_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 uniform(const at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & uniform_out(const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator, at::Tensor & out);
+TORCH_API at::Tensor & uniform_(at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+TORCH_API at::Tensor & uniform_meta_(at::Tensor & self, double from=0, double to=1, ::std::optional<at::Generator> generator=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..082f1234207a6b5fa0c44a4a684f1fc6a0c1e105
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/uniform_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 uniform_ {
+  using schema = at::Tensor & (at::Tensor &, double, double, ::std::optional<at::Generator>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::uniform_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "uniform_(Tensor(a!) self, float from=0, float to=1, *, Generator? generator=None) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator);
+};
+
+struct TORCH_API uniform_out {
+  using schema = at::Tensor & (const at::Tensor &, double, 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::uniform";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator, at::Tensor & out);
+};
+
+struct TORCH_API uniform {
+  using schema = at::Tensor (const at::Tensor &, double, double, ::std::optional<at::Generator>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::uniform";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double from, double to, ::std::optional<at::Generator> generator);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive.h
new file mode 100644
index 0000000000000000000000000000000000000000..34f0b2ed04b1ec6545bf9895a8ab9883040e81f4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unique_consecutive_ops.h>
+
+namespace at {
+
+
+// aten::unique_consecutive(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None) -> (Tensor, Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt) {
+    return at::_ops::unique_consecutive::call(self, return_inverse, return_counts, dim);
+}
+
+// aten::unique_consecutive.out(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_consecutive_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt) {
+    return at::_ops::unique_consecutive_out::call(self, return_inverse, return_counts, dim, out0, out1, out2);
+}
+// aten::unique_consecutive.out(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_consecutive_outf(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) {
+    return at::_ops::unique_consecutive_out::call(self, return_inverse, return_counts, dim, out0, out1, out2);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..39c82074467bed3a40b5cc9749e35f175f3b9e53
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_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 &,at::Tensor &> unique_consecutive_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_consecutive_outf(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..267dd270495973e3309eec8506ee0831c455dab3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_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,at::Tensor> unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..485a121dcbf04b8d22a7b1f977d5d38144408ecd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_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,at::Tensor> unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..1211192e69dc094621d39f628113176afba0f9d6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_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 &,at::Tensor &> unique_consecutive_out(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_consecutive_cpu(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_consecutive_cuda(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, ::std::optional<int64_t> dim=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..e6ff5973555ca2a292cab8aa421f32fc0bf4b4eb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_consecutive_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unique_consecutive {
+  using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor> (const at::Tensor &, bool, bool, ::std::optional<int64_t>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unique_consecutive";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unique_consecutive(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None) -> (Tensor, Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> call(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim);
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim);
+};
+
+struct TORCH_API unique_consecutive_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> (const at::Tensor &, bool, bool, ::std::optional<int64_t>, 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::unique_consecutive";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unique_consecutive.out(Tensor self, bool return_inverse=False, bool return_counts=False, int? dim=None, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> call(const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool return_inverse, bool return_counts, ::std::optional<int64_t> dim, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim.h
new file mode 100644
index 0000000000000000000000000000000000000000..0c179f50ed1fcf572fbc448a417c79b543667485
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unique_dim_ops.h>
+
+namespace at {
+
+
+// aten::unique_dim(Tensor self, int dim, bool sorted=True, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false) {
+    return at::_ops::unique_dim::call(self, dim, sorted, return_inverse, return_counts);
+}
+
+// aten::unique_dim.out(Tensor self, int dim, bool sorted=True, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false) {
+    return at::_ops::unique_dim_out::call(self, dim, sorted, return_inverse, return_counts, out0, out1, out2);
+}
+// aten::unique_dim.out(Tensor self, int dim, bool sorted=True, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_outf(const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) {
+    return at::_ops::unique_dim_out::call(self, dim, sorted, return_inverse, return_counts, out0, out1, out2);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..cfd1ca3d1de705406ebb785410716dc9ea861d9d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_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 &,at::Tensor &> unique_dim_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_outf(const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive.h
new file mode 100644
index 0000000000000000000000000000000000000000..8ad10fbb48bd225325c7102c7ec02b8904b0a71d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unique_dim_consecutive_ops.h>
+
+namespace at {
+
+
+// aten::unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)
+inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_consecutive(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false) {
+    return at::_ops::unique_dim_consecutive::call(self, dim, return_inverse, return_counts);
+}
+
+// aten::unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_consecutive_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false) {
+    return at::_ops::unique_dim_consecutive_out::call(self, dim, return_inverse, return_counts, out0, out1, out2);
+}
+// aten::unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))
+inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_consecutive_outf(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) {
+    return at::_ops::unique_dim_consecutive_out::call(self, dim, return_inverse, return_counts, out0, out1, out2);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8ac20e4a3b77b9b5e2ff35de21e45b84ea0c24c1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_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 &,at::Tensor &> unique_dim_consecutive_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false);
+TORCH_API ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_consecutive_outf(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..100f6b30a01dd648ea02d67d20b3ffd20a7e25e7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_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,at::Tensor> unique_dim_consecutive(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..490355337a43062f3a94e191f301819104d09f22
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_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,at::Tensor> unique_dim_consecutive(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..499281b18be8a63da9d64d23d4bd8d2fc97c59ff
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_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 &,at::Tensor &> unique_dim_consecutive_out(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_consecutive_cpu(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_consecutive_cuda(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..53dcf6988f66df590c6bf5802b8f4f23f94f80a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_consecutive_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unique_dim_consecutive {
+  using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor> (const at::Tensor &, int64_t, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unique_dim_consecutive";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> call(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts);
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts);
+};
+
+struct TORCH_API unique_dim_consecutive_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> (const at::Tensor &, int64_t, bool, bool, 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::unique_dim_consecutive";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> call(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e737debc10d916e66acc6a9e83aeb467bba118b2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_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,at::Tensor> unique_dim(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..7b15fb6cf8e47283065235db5c564afaa8810043
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_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,at::Tensor> unique_dim(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..6a2391f1d6d820792bad0f2f1f9915667c017645
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_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 &,at::Tensor &> unique_dim_out(const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_cpu(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false);
+TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_cuda(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..6b3c784a9a955d592b50b116ca3cd3175def570b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unique_dim_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unique_dim {
+  using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor> (const at::Tensor &, int64_t, bool, bool, bool);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unique_dim";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unique_dim(Tensor self, int dim, bool sorted=True, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)";
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> call(const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts);
+  static ::std::tuple<at::Tensor,at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts);
+};
+
+struct TORCH_API unique_dim_out {
+  using schema = ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> (const at::Tensor &, int64_t, bool, bool, bool, 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::unique_dim";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unique_dim.out(Tensor self, int dim, bool sorted=True, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))";
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> call(const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+  static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool sorted, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk.h
new file mode 100644
index 0000000000000000000000000000000000000000..9de1d50cc0655e796b9ca3977ece9265dc2f0688
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk.h
@@ -0,0 +1,31 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unsafe_chunk_ops.h>
+
+namespace at {
+
+
+// aten::unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0) {
+    return at::_ops::unsafe_chunk::call(self, chunks, dim);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..ead0429070f1744dca3fdce954e8dc2ab07d1eb0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_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::vector<at::Tensor> unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..788911841b79beeb919586941d98ce0260789494
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_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::vector<at::Tensor> unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..aead55dd3dd81c76a9e9eea377366e2d976398f8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_chunk_ops.h
@@ -0,0 +1,29 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unsafe_chunk {
+  using schema = ::std::vector<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::unsafe_chunk";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, int64_t chunks, int64_t dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t chunks, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split.h
new file mode 100644
index 0000000000000000000000000000000000000000..993c594a84195262fc6a95dfed57fd8f25ebe516
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unsafe_split_ops.h>
+
+namespace at {
+
+
+// aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unsafe_split(const at::Tensor & self, int64_t split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor::call(self, split_size, dim);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  ::std::vector<at::Tensor> unsafe_split(const at::Tensor & self, int64_t split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor::call(self, split_size, dim);
+  }
+}
+
+// aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unsafe_split_symint(const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor::call(self, split_size, dim);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  ::std::vector<at::Tensor> unsafe_split(const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor::call(self, split_size, dim);
+  }
+}
+
+// aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_out(at::TensorList out, const at::Tensor & self, int64_t split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  void unsafe_split_out(at::TensorList out, const at::Tensor & self, int64_t split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+  }
+}
+
+// aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_outf(const at::Tensor & self, int64_t split_size, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  void unsafe_split_outf(const at::Tensor & self, int64_t split_size, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+  }
+}
+
+// aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_symint_out(at::TensorList out, const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  void unsafe_split_out(at::TensorList out, const at::Tensor & self, c10::SymInt split_size, int64_t dim=0) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+  }
+}
+
+// aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_symint_outf(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  void unsafe_split_outf(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_Tensor_out::call(self, split_size, dim, out);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d153a4ac2f8b3fbaab972c6b98d258fec8900331
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_compositeexplicitautograd_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 compositeexplicitautograd {
+
+TORCH_API ::std::vector<at::Tensor> unsafe_split(const at::Tensor & self, int64_t split_size, int64_t dim=0);
+TORCH_API ::std::vector<at::Tensor> unsafe_split_symint(const at::Tensor & self, c10::SymInt split_size, int64_t dim=0);
+TORCH_API void unsafe_split_out(at::TensorList out, const at::Tensor & self, int64_t split_size, int64_t dim=0);
+TORCH_API void unsafe_split_outf(const at::Tensor & self, int64_t split_size, int64_t dim, at::TensorList out);
+TORCH_API void unsafe_split_symint_out(at::TensorList out, const at::Tensor & self, c10::SymInt split_size, int64_t dim=0);
+TORCH_API void unsafe_split_symint_outf(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..2aeae6dca18266a9cdcb8b50d6bb748ca3a1fb35
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_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::vector<at::Tensor> unsafe_split(const at::Tensor & self, int64_t split_size, int64_t dim=0);
+TORCH_API void unsafe_split_Tensor_out_symint(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..dbc37ca1130e34f290ee5746efc19ad013cbf3bf
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unsafe_split_Tensor {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, c10::SymInt, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unsafe_split";
+  static constexpr const char* overload_name = "Tensor";
+  static constexpr const char* schema_str = "unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, c10::SymInt split_size, int64_t dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim);
+};
+
+struct TORCH_API unsafe_split_Tensor_out {
+  using schema = void (const at::Tensor &, c10::SymInt, int64_t, at::TensorList);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unsafe_split";
+  static constexpr const char* overload_name = "Tensor_out";
+  static constexpr const char* schema_str = "unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> ()";
+  static void call(const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out);
+  static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim, at::TensorList out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h
new file mode 100644
index 0000000000000000000000000000000000000000..b052446b39e16d20c2dd6f9a54bd7b6c7d2918c9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unsafe_split_with_sizes_ops.h>
+
+namespace at {
+
+
+// aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes::call(self, c10::fromIntArrayRefSlow(split_sizes), dim);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  ::std::vector<at::Tensor> unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes::call(self, c10::fromIntArrayRefSlow(split_sizes), dim);
+  }
+}
+
+// aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]
+inline ::std::vector<at::Tensor> unsafe_split_with_sizes_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes::call(self, split_sizes, dim);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  ::std::vector<at::Tensor> unsafe_split_with_sizes(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes::call(self, split_sizes, dim);
+  }
+}
+
+// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out);
+  }
+}
+
+// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_with_sizes_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  void unsafe_split_with_sizes_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, c10::fromIntArrayRefSlow(split_sizes), dim, out);
+  }
+}
+
+// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_with_sizes_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out);
+  }
+}
+
+// aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()
+inline void unsafe_split_with_sizes_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  void unsafe_split_with_sizes_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) {
+    return at::_ops::unsafe_split_with_sizes_out::call(self, split_sizes, dim, out);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6f7c9db51ef65c0c349c512fa6c77e2c74d68ed1
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_compositeexplicitautograd_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 compositeexplicitautograd {
+
+TORCH_API ::std::vector<at::Tensor> unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0);
+TORCH_API ::std::vector<at::Tensor> unsafe_split_with_sizes_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0);
+TORCH_API void unsafe_split_with_sizes_out(at::TensorList out, const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0);
+TORCH_API void unsafe_split_with_sizes_outf(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim, at::TensorList out);
+TORCH_API void unsafe_split_with_sizes_symint_out(at::TensorList out, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim=0);
+TORCH_API void unsafe_split_with_sizes_symint_outf(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..8b753a5053ff82950361378e77c992b4bf42bab2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_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::vector<at::Tensor> unsafe_split_with_sizes(const at::Tensor & self, at::IntArrayRef split_sizes, int64_t dim=0);
+TORCH_API void unsafe_split_with_sizes_out_symint(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..19afe71d87ec1b5cd4db24e12f4025671c1d7cdb
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsafe_split_with_sizes_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unsafe_split_with_sizes {
+  using schema = ::std::vector<at::Tensor> (const at::Tensor &, c10::SymIntArrayRef, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unsafe_split_with_sizes";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]";
+  static ::std::vector<at::Tensor> call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim);
+  static ::std::vector<at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim);
+};
+
+struct TORCH_API unsafe_split_with_sizes_out {
+  using schema = void (const at::Tensor &, c10::SymIntArrayRef, int64_t, at::TensorList);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unsafe_split_with_sizes";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()";
+  static void call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out);
+  static void redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.h
new file mode 100644
index 0000000000000000000000000000000000000000..f2a9bb02ebed21c7219d3de49d1c3ed2e07e7c33
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze.h
@@ -0,0 +1,31 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unsqueeze_ops.h>
+
+namespace at {
+
+
+// aten::unsqueeze(Tensor(a) self, int dim) -> Tensor(a)
+inline at::Tensor unsqueeze(const at::Tensor & self, int64_t dim) {
+    return at::_ops::unsqueeze::call(self, dim);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0fcea185ba7b6577fa61e1a23b084f5a0ebe6dc6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_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 unsqueeze(const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & unsqueeze_(at::Tensor & self, int64_t dim);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy.h
new file mode 100644
index 0000000000000000000000000000000000000000..3b372eeb3d6c67d61b94d68acffdf5c88ee90dbe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy.h
@@ -0,0 +1,40 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/unsqueeze_copy_ops.h>
+
+namespace at {
+
+
+// aten::unsqueeze_copy(Tensor self, int dim) -> Tensor
+inline at::Tensor unsqueeze_copy(const at::Tensor & self, int64_t dim) {
+    return at::_ops::unsqueeze_copy::call(self, dim);
+}
+
+// aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unsqueeze_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim) {
+    return at::_ops::unsqueeze_copy_out::call(self, dim, out);
+}
+// aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & unsqueeze_copy_outf(const at::Tensor & self, int64_t dim, at::Tensor & out) {
+    return at::_ops::unsqueeze_copy_out::call(self, dim, out);
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1792b2da9fcb5c12b812b19eba1a0ec119781413
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_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 & unsqueeze_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & unsqueeze_copy_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1cca8aab39827c6524f4742bb07c0c9a378848b0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_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 unsqueeze_copy(const at::Tensor & self, int64_t dim);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..45b4240bf5f32ad22773c96e4a3ed01febf8e02e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_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 & unsqueeze_copy_out(const at::Tensor & self, int64_t dim, at::Tensor & out);
+TORCH_API at::Tensor unsqueeze_copy(const at::Tensor & self, int64_t dim);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..3f77f0660458a05a4c755b1d9c4edc48719d4404
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unsqueeze_copy {
+  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::unsqueeze_copy";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unsqueeze_copy(Tensor self, int dim) -> 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);
+};
+
+struct TORCH_API unsqueeze_copy_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::unsqueeze_copy";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "unsqueeze_copy.out(Tensor self, int dim, *, 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);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..a68b7e371dbd706c3e33477cee531ce0b5b40221
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_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>
+
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor unsqueeze(const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor unsqueeze_nested(const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor unsqueeze_sparse(const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor unsqueeze_quantized(const at::Tensor & self, int64_t dim);
+TORCH_API at::Tensor & unsqueeze_(at::Tensor & self, int64_t dim);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..43ff20db479f8c52d8c07bd5ad1a882b4ec2d894
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 unsqueeze {
+  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::unsqueeze";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unsqueeze(Tensor(a) self, int dim) -> Tensor(a)";
+  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);
+};
+
+struct TORCH_API unsqueeze_ {
+  using schema = at::Tensor & (at::Tensor &, int64_t);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::unsqueeze_";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "unsqueeze_(Tensor(a!) self, int dim) -> Tensor(a!)";
+  static at::Tensor & call(at::Tensor & self, int64_t dim);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d.h
new file mode 100644
index 0000000000000000000000000000000000000000..1d821e0221ef2488cc689f592e00c42682cb7b85
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d.h
@@ -0,0 +1,114 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_bicubic2d_ops.h>
+
+namespace at {
+
+
+// aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bicubic2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bicubic2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_bicubic2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bicubic2d_vec::call(input, output_size, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bicubic2d_vec::call(input, output_size, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_bicubic2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bicubic2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bicubic2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bicubic2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bicubic2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bicubic2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bicubic2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bicubic2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bicubic2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w);
+  }
+}
+
+// aten::upsample_bicubic2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d::call(self, output_size, align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bicubic2d(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d::call(self, output_size, align_corners, scales_h, scales_w);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..ad1ee462d12ed92b5d32d1a6b043022c7c9fadb7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_bicubic2d_backward_ops.h>
+
+namespace at {
+
+
+// aten::upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bicubic2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bicubic2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w);
+  }
+}
+
+// aten::upsample_bicubic2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bicubic2d_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..16da4dddacebefb525c6b5e397cb0c679348e2bc
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_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 upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..992dd566bc7bc0d9f04c42d19b862eaeb275d52b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9c0b3875745736ab57ba36f7528095156ccf7585
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..77cbd7c26cdb5a8c2344023a232e81864b25f441
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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_upsample_bicubic2d_backward : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5c7631d959379b79e62aab544b2303a8fab5fdb5
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_meta_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 meta {
+
+TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..9232b313ef51ad00e0dfe56d4fab1f94ab2ccb9a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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/upsample_bicubic2d_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_upsample_bicubic2d_backward_out_cpu : public at::meta::structured_upsample_bicubic2d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_upsample_bicubic2d_backward_out_cuda : public at::meta::structured_upsample_bicubic2d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..8107ea89e95b9576885632203fdf257cb02743d0
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_backward_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_bicubic2d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bicubic2d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "upsample_bicubic2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+};
+
+struct TORCH_API upsample_bicubic2d_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bicubic2d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_bicubic2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..1ffe7c05d8f72f36d0dba85a34c664ee42a2e3d6
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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 upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5851937d23e51f53094862f9cedaf329bc832675
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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 upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..b23dd0ad436db725f2a42f3e2f8a8f3a3cf97dd7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..9fd6424235f370d0201706626414b1b13bf92116
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..c6c3444c3ac074bc7c1e835377c6286337725b60
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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_upsample_bicubic2d : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..62d48b676ab4eee38f2f0ea3dc695a4c8fbb3f05
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_meta_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 meta {
+
+TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bicubic2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bicubic2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..b242af63eaae01fc3272a3eb66cc0acf5c85b532
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_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>
+#include <ATen/ops/upsample_bicubic2d_meta.h>
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+struct TORCH_API structured_upsample_bicubic2d_out_cpu : public at::meta::structured_upsample_bicubic2d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & out);
+};
+struct TORCH_API structured_upsample_bicubic2d_out_cuda : public at::meta::structured_upsample_bicubic2d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..30ff15140dc3ac50fcd0efabc755cb778e7d0c4a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bicubic2d_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_bicubic2d_vec {
+  using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional<at::ArrayRef<double>>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bicubic2d";
+  static constexpr const char* overload_name = "vec";
+  static constexpr const char* schema_str = "upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+};
+
+struct TORCH_API upsample_bicubic2d_out {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bicubic2d";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "upsample_bicubic2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+};
+
+struct TORCH_API upsample_bicubic2d {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bicubic2d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_bicubic2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d.h
new file mode 100644
index 0000000000000000000000000000000000000000..77fa5fe10be7aa59a2f73a09057887789295effe
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d.h
@@ -0,0 +1,158 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_bilinear2d_ops.h>
+
+namespace at {
+
+
+// aten::upsample_bilinear2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_bilinear2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_bilinear2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec::call(input, output_size, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bilinear2d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec::call(input, output_size, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_out::call(self, output_size, align_corners, scales_h, scales_w, out);
+  }
+}
+
+// aten::upsample_bilinear2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales_h, scales_w);
+  }
+}
+
+// aten::upsample_bilinear2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d::call(self, output_size, align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bilinear2d(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d::call(self, output_size, align_corners, scales_h, scales_w);
+  }
+}
+
+// aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors, out);
+  }
+}
+
+// aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors, out);
+  }
+}
+
+// aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size, align_corners, scale_factors, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size, align_corners, scale_factors, out);
+  }
+}
+
+// aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size, align_corners, scale_factors, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out) {
+    return at::_ops::upsample_bilinear2d_vec_out::call(input, output_size, align_corners, scale_factors, out);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..6d6eddd9681675c986b1e10f8728b04505efc04c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_bilinear2d_backward_ops.h>
+
+namespace at {
+
+
+// aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_bilinear2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input) {
+    return at::_ops::upsample_bilinear2d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input);
+  }
+}
+
+// aten::upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales_h, scales_w);
+  }
+}
+
+// aten::upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor
+inline at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt) {
+    return at::_ops::upsample_bilinear2d_backward::call(grad_output, output_size, input_size, align_corners, scales_h, scales_w);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..536ad148b79600c4c66af966688b68707f788cea
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_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 upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4e153303d59c0276bec51570be7e9d74869d71d8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e4acae6da3f40c38cae62fa37a8e1fbd76c2cee8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..b381a715fc6276c8d76f5d1cfcbfba32a865ed19
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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_upsample_bilinear2d_backward : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..36241b0998bb205ed76e8aec9cf811cc48df1162
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_meta_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 meta {
+
+TORCH_API at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..464203bad925381ca42b4925be2d2acd88d7ea0f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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/upsample_bilinear2d_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_upsample_bilinear2d_backward_out_cpu : public at::meta::structured_upsample_bilinear2d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_upsample_bilinear2d_backward_out_cuda : public at::meta::structured_upsample_bilinear2d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..23059628235a1bbbdb8bae41817a164b9226dc1b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_backward_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_bilinear2d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & grad_input);
+};
+
+struct TORCH_API upsample_bilinear2d_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeexplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeexplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..40c4cd3d9aaf06042e47171aa7bc3510d68f8f2c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out);
+
+} // namespace compositeexplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..0799f171959c6300582acbf1e1574b793eaaf34f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c554723846bfe5e9321d68bc3e16297445a291f8
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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 upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..f2a932bc5a695bb616182eaccfd8dc98a602b6ba
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..69461603fb7e765f8a0edabaf363bf5149da6f65
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..9316105bbed9957faedbe2d9e49394d00b817a77
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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_upsample_bilinear2d : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..5ac6d48d792628539a827a53616b233e50de5c19
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_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 meta {
+
+TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..cfaeac343d469f2f1c3f484aeaa1c8ddc754754d
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_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/upsample_bilinear2d_meta.h>
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor & upsample_bilinear2d_vec_out_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out);
+struct TORCH_API structured_upsample_bilinear2d_out_cpu : public at::meta::structured_upsample_bilinear2d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & out);
+};
+struct TORCH_API structured_upsample_bilinear2d_out_cuda : public at::meta::structured_upsample_bilinear2d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, const at::Tensor & out);
+};
+TORCH_API at::Tensor upsample_bilinear2d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h=::std::nullopt, ::std::optional<double> scales_w=::std::nullopt);
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..5b3e4dabc22cdd8c7e04e29a2dadf82b78d0222a
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_ops.h
@@ -0,0 +1,62 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_bilinear2d_vec {
+  using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional<at::ArrayRef<double>>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d";
+  static constexpr const char* overload_name = "vec";
+  static constexpr const char* schema_str = "upsample_bilinear2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+};
+
+struct TORCH_API upsample_bilinear2d_out {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "upsample_bilinear2d.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w, at::Tensor & out);
+};
+
+struct TORCH_API upsample_bilinear2d {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_bilinear2d(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales_h, ::std::optional<double> scales_w);
+};
+
+struct TORCH_API upsample_bilinear2d_vec_out {
+  using schema = at::Tensor & (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional<at::ArrayRef<double>>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_bilinear2d";
+  static constexpr const char* overload_name = "vec_out";
+  static constexpr const char* schema_str = "upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors, at::Tensor & out);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d.h
new file mode 100644
index 0000000000000000000000000000000000000000..2ed3729b22634221f0b47015c8909d62e148397e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d.h
@@ -0,0 +1,114 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_linear1d_ops.h>
+
+namespace at {
+
+
+// aten::upsample_linear1d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_linear1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_linear1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_linear1d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_linear1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_linear1d_vec::call(input, output_size, align_corners, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_linear1d_vec::call(input, output_size, align_corners, scale_factors);
+  }
+}
+
+// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out);
+  }
+}
+
+// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_linear1d_out::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales, out);
+  }
+}
+
+// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out);
+  }
+}
+
+// aten::upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_linear1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_linear1d_out::call(self, output_size, align_corners, scales, out);
+  }
+}
+
+// aten::upsample_linear1d(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None) -> Tensor
+inline at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d::call(self, c10::fromIntArrayRefSlow(output_size), align_corners, scales);
+  }
+}
+
+// aten::upsample_linear1d(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None) -> Tensor
+inline at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d::call(self, output_size, align_corners, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_linear1d(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d::call(self, output_size, align_corners, scales);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..82acc2141f966f53a7d82acd084dfb5a229b6efd
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_linear1d_backward_ops.h>
+
+namespace at {
+
+
+// aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales, grad_input);
+  }
+}
+
+// aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales, grad_input);
+  }
+}
+
+// aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales, grad_input);
+  }
+}
+
+// aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_linear1d_backward_grad_input::call(grad_output, output_size, input_size, align_corners, scales, grad_input);
+  }
+}
+
+// aten::upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor
+inline at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), align_corners, scales);
+  }
+}
+
+// aten::upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor
+inline at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward::call(grad_output, output_size, input_size, align_corners, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_linear1d_backward::call(grad_output, output_size, input_size, align_corners, scales);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..cba02f4ef660188d87be3c9e1e0b851db31af365
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_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 upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..358bde45b61020eca95f706a0115d27ead433a1c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..a7cfb3fe4ab165242a91b9448bc5501c60ef45b2
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..efccf62d711736eb15dccf21a46b6f6c7cf90925
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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_upsample_linear1d_backward : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..6e3ead5c0a8396806c54f852d8b6659f7307a129
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_meta_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 meta {
+
+TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..7d5194edd437f4a797c274299cf54af745f1d49c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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/upsample_linear1d_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_upsample_linear1d_backward_out_cpu : public at::meta::structured_upsample_linear1d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_upsample_linear1d_backward_out_cuda : public at::meta::structured_upsample_linear1d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, bool align_corners, ::std::optional<double> scales, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..64a8d7b64fea4dd72b6fcdae466e243d7b08c7a7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_backward_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_linear1d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_linear1d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales, at::Tensor & grad_input);
+};
+
+struct TORCH_API upsample_linear1d_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_linear1d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, ::std::optional<double> scales);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..d190c903ba8e22cf2984ce43d954c7b741bddf67
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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 upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..64362c9433849e1832bbbbdd11465a4c9edb1ace
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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 upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..59853c019aaa861c659b5d0c2356dc22017b8d69
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+TORCH_API at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..8b4e694d15735e753858f120a81483940287526e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+TORCH_API at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..4eea3663396ce45198d8091d2574d2bafb04cfd3
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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_upsample_linear1d : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..c9db4ba170ee972bc09ba190ba5732ae6ac22c8b
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_meta_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 meta {
+
+TORCH_API at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_linear1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+TORCH_API at::Tensor & upsample_linear1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_linear1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..c413a2b881a99980203f6827ddc498d2fb48ece9
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_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>
+#include <ATen/ops/upsample_linear1d_meta.h>
+
+namespace at {
+namespace native {
+TORCH_API at::Tensor upsample_linear1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+struct TORCH_API structured_upsample_linear1d_out_cpu : public at::meta::structured_upsample_linear1d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales, const at::Tensor & out);
+};
+struct TORCH_API structured_upsample_linear1d_out_cuda : public at::meta::structured_upsample_linear1d {
+void impl(const at::Tensor & self, at::ArrayRef<int64_t> output_size, bool align_corners, ::std::optional<double> scales, const at::Tensor & out);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..2c51c3f7b56e9353add2f5fbaa8c6d90816df22e
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_linear1d_ops.h
@@ -0,0 +1,51 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_linear1d_vec {
+  using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, bool, ::std::optional<at::ArrayRef<double>>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_linear1d";
+  static constexpr const char* overload_name = "vec";
+  static constexpr const char* schema_str = "upsample_linear1d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor";
+  static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, ::std::optional<at::ArrayRef<double>> scale_factors);
+};
+
+struct TORCH_API upsample_linear1d_out {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_linear1d";
+  static constexpr const char* overload_name = "out";
+  static constexpr const char* schema_str = "upsample_linear1d.out(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales, at::Tensor & out);
+};
+
+struct TORCH_API upsample_linear1d {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, bool, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_linear1d";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_linear1d(Tensor self, SymInt[1] output_size, bool align_corners, float? scales=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, ::std::optional<double> scales);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d.h
new file mode 100644
index 0000000000000000000000000000000000000000..81ac6d7afd9c993f3889f26d2f6da5a0496b9b74
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d.h
@@ -0,0 +1,114 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_nearest1d_ops.h>
+
+namespace at {
+
+
+// aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_nearest1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_nearest1d_vec::call(input, output_size.has_value() ? ::std::make_optional(c10::fromIntArrayRefSlow(*output_size)) : ::std::nullopt, scale_factors);
+  }
+}
+
+// aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor
+inline at::Tensor upsample_nearest1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_nearest1d_vec::call(input, output_size, scale_factors);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_nearest1d(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors) {
+    return at::_ops::upsample_nearest1d_vec::call(input, output_size, scale_factors);
+  }
+}
+
+// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out);
+  }
+}
+
+// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_nearest1d_out::call(self, c10::fromIntArrayRefSlow(output_size), scales, out);
+  }
+}
+
+// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out);
+  }
+}
+
+// aten::upsample_nearest1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out) {
+    return at::_ops::upsample_nearest1d_out::call(self, output_size, scales, out);
+  }
+}
+
+// aten::upsample_nearest1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor
+inline at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d::call(self, c10::fromIntArrayRefSlow(output_size), scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d::call(self, c10::fromIntArrayRefSlow(output_size), scales);
+  }
+}
+
+// aten::upsample_nearest1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor
+inline at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d::call(self, output_size, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_nearest1d(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d::call(self, output_size, scales);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward.h
new file mode 100644
index 0000000000000000000000000000000000000000..7baa8f1db5fa21e7277245369a5ee381d7977795
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward.h
@@ -0,0 +1,92 @@
+#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 <string_view>
+
+
+
+#include <ATen/ops/upsample_nearest1d_backward_ops.h>
+
+namespace at {
+
+
+// aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales, grad_input);
+  }
+}
+
+// aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales, grad_input);
+  }
+}
+
+// aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, output_size, input_size, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, output_size, input_size, scales, grad_input);
+  }
+}
+
+// aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)
+inline at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, output_size, input_size, scales, grad_input);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input) {
+    return at::_ops::upsample_nearest1d_backward_grad_input::call(grad_output, output_size, input_size, scales, grad_input);
+  }
+}
+
+// aten::upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor
+inline at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, int64_t>>>
+  at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward::call(grad_output, c10::fromIntArrayRefSlow(output_size), c10::fromIntArrayRefSlow(input_size), scales);
+  }
+}
+
+// aten::upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor
+inline at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward::call(grad_output, output_size, input_size, scales);
+}
+namespace symint {
+  template <typename T, typename = std::enable_if_t<std::is_same_v<T, c10::SymInt>>>
+  at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt) {
+    return at::_ops::upsample_nearest1d_backward::call(grad_output, output_size, input_size, scales);
+  }
+}
+
+}
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..4ea664f3c1403ff9bc1422ed865f97165ae4a461
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_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 upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..841421c492d004ea9786f6e908415dc5ec1558e7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace cpu
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cuda_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cuda_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..3abf0e46b6abb69f195a51eafcfe1f25f3891814
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_cuda_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 cuda {
+
+TORCH_API at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace cuda
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta.h
new file mode 100644
index 0000000000000000000000000000000000000000..df0c68bd67752116e896255b40a3fa16b8a9b41c
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_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_upsample_nearest1d_backward : public at::impl::MetaBase {
+
+
+    void meta(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, ::std::optional<double> scales);
+};
+
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..2cf8b84150f16c1893a76b7432a07e1710b18925
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_meta_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 meta {
+
+TORCH_API at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+
+} // namespace meta
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_native.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_native.h
new file mode 100644
index 0000000000000000000000000000000000000000..3f9e935f7067ae16062a452a09b79fd90483ba99
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_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/upsample_nearest1d_backward_meta.h>
+
+namespace at {
+namespace native {
+struct TORCH_API structured_upsample_nearest1d_backward_out_cpu : public at::meta::structured_upsample_nearest1d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, ::std::optional<double> scales, const at::Tensor & grad_input);
+};
+struct TORCH_API structured_upsample_nearest1d_backward_out_cuda : public at::meta::structured_upsample_nearest1d_backward {
+void impl(const at::Tensor & grad_output, at::ArrayRef<int64_t> output_size, at::ArrayRef<int64_t> input_size, ::std::optional<double> scales, const at::Tensor & grad_input);
+};
+} // namespace native
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_ops.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_ops.h
new file mode 100644
index 0000000000000000000000000000000000000000..a8224fcd4c4808b1c5de6bf5a80a7a77747b54f7
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_backward_ops.h
@@ -0,0 +1,40 @@
+#pragma once
+
+// @generated by torchgen/gen.py from Operator.h
+
+#include <string_view>
+#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 upsample_nearest1d_backward_grad_input {
+  using schema = at::Tensor & (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional<double>, at::Tensor &);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_nearest1d_backward";
+  static constexpr const char* overload_name = "grad_input";
+  static constexpr const char* schema_str = "upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)";
+  static at::Tensor & call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+  static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales, at::Tensor & grad_input);
+};
+
+struct TORCH_API upsample_nearest1d_backward {
+  using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::SymIntArrayRef, ::std::optional<double>);
+  using ptr_schema = schema*;
+  // See Note [static constexpr char* members for windows NVCC]
+  static constexpr const char* name = "aten::upsample_nearest1d_backward";
+  static constexpr const char* overload_name = "";
+  static constexpr const char* schema_str = "upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor";
+  static at::Tensor call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales);
+  static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, ::std::optional<double> scales);
+};
+
+}} // namespace at::_ops
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_compositeexplicitautogradnonfunctional_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_compositeexplicitautogradnonfunctional_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..e4107b971754f92e7791e97bc0ba311f90bb817f
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_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 upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+
+} // namespace compositeexplicitautogradnonfunctional
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_compositeimplicitautograd_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_compositeimplicitautograd_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..47f7ce375d97755dcd05bf29504e5d8a9e4b4715
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_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 upsample_nearest1d(const at::Tensor & input, at::OptionalIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors);
+TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, ::std::optional<at::ArrayRef<double>> scale_factors);
+
+} // namespace compositeimplicitautograd
+} // namespace at
diff --git a/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_cpu_dispatch.h b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_cpu_dispatch.h
new file mode 100644
index 0000000000000000000000000000000000000000..32733249fff8d3385b3580105c14005bcf5378a4
--- /dev/null
+++ b/code/LaDi-RL-old-qwen-cod/LaDi-RL-old-qwen-cod/venv/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest1d_cpu_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 cpu {
+
+TORCH_API at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor upsample_nearest1d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out);
+TORCH_API at::Tensor & upsample_nearest1d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales=::std::nullopt);
+TORCH_API at::Tensor & upsample_nearest1d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, ::std::optional<double> scales, at::Tensor & out);
+
+} // namespace cpu
+} // namespace at