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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

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

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

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 {
+
+
+
+}

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

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

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

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 {
+
+
+
+}

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

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

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

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

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

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);
+  }
+}
+
+}

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

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

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

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

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

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

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

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);
+}
+
+}

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);
+  }
+}
+
+}

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

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

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

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

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

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

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

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

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);
+}
+
+}

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

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

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);
+}
+
+}

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

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

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

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

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

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

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);
+}
+
+}

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

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

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

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);
+}
+
+}

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

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

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

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);
+}
+
+}