diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9efc821dba9a76be10add00499ad55bb92e4de4f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cast_Int_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor _cast_Int(const at::Tensor & self, bool non_blocking=false); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar.h new file mode 100644 index 0000000000000000000000000000000000000000..c6d0c2e5c0c268ba04233896f6a25f66d9f9acca --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foobar.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor +inline at::Tensor _foobar(const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true) { + return at::_ops::_foobar::call(self, arg1, arg2, arg3); +} + +// aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _foobar_out(at::Tensor & out, const at::Tensor & self, bool arg1=true, bool arg2=true, bool arg3=true) { + return at::_ops::_foobar_out::call(self, arg1, arg2, arg3, out); +} +// aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _foobar_outf(const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out) { + return at::_ops::_foobar_out::call(self, arg1, arg2, arg3, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0e23be16a45c5d84168a701937942fb4fcc7a3f9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_addcmul_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars, at::TensorList out); +TORCH_API void _foreach_addcmul_out(at::TensorList out, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars); +TORCH_API void _foreach_addcmul_outf(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce50d61345e05742017d1a337c68bf56dcaffd22 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_log1p_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_log1p(at::TensorList self); +TORCH_API void _foreach_log1p_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..63a1e65400988f524f074cdd9feb05414d5aeb6d --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sqrt_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::vector _foreach_sqrt(at::TensorList self); +TORCH_API void _foreach_sqrt_(at::TensorList self); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_solve_ex_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ee7ea5a01eb8336cbaf13750113e5ca765694922 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_linalg_solve_ex_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API ::std::tuple _linalg_solve_ex(const at::Tensor & A, const at::Tensor & B, bool left=true, bool check_errors=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_lu_with_info_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_lu_with_info_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4b13bfb06dc09ef4026591cf3e270c644f84fc5f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_lu_with_info_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple _lu_with_info(const at::Tensor & self, bool pivot=true, bool check_errors=true); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_sum_backward_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_sum_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ca7754b6390232be7b4de7a501900444b5cc6000 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_sum_backward_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _nested_sum_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, at::OptionalIntArrayRef, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_nested_sum_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_nested_sum_backward(Tensor grad, Tensor self, int[1]? dim, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_available.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_available.h new file mode 100644 index 0000000000000000000000000000000000000000..0485b5af5c98c28b01f599503eaf60a887ed7d9f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_nnpack_available.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_nnpack_available() -> bool +inline bool _nnpack_available() { + return at::_ops::_nnpack_available::call(); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55979861091995b7b5596733fb19734b35940645 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_pin_memory_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _pin_memory(const at::Tensor & self, c10::optional device=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_prelu_kernel.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_prelu_kernel.h new file mode 100644 index 0000000000000000000000000000000000000000..e5f34405328ec6b3f720e1eeda0bd36beb7235e8 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_prelu_kernel.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor +inline at::Tensor _prelu_kernel(const at::Tensor & self, const at::Tensor & weight) { + return at::_ops::_prelu_kernel::call(self, weight); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..742f7c5521f190e08a1e46a03d2e862b52f09837 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_reshape_alias_copy(Tensor self, SymInt[] size, SymInt[] stride) -> Tensor +inline at::Tensor _reshape_alias_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); +} +namespace symint { + template ::value>> + at::Tensor _reshape_alias_copy(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride)); + } +} + +// aten::_reshape_alias_copy(Tensor self, SymInt[] size, SymInt[] stride) -> Tensor +inline at::Tensor _reshape_alias_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, size, stride); +} +namespace symint { + template ::value>> + at::Tensor _reshape_alias_copy(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy::call(self, size, stride); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, c10::fromIntArrayRefSlow(size), c10::fromIntArrayRefSlow(stride), out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); + } +} + +// aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _reshape_alias_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); +} +namespace symint { + template ::value>> + at::Tensor & _reshape_alias_copy_outf(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { + return at::_ops::_reshape_alias_copy_out::call(self, size, stride, out); + } +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy_native.h new file mode 100644 index 0000000000000000000000000000000000000000..95609e7045991abb311e7965a2f20700b9914745 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_reshape_alias_copy_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _reshape_alias_copy_out_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out); +TORCH_API at::Tensor _reshape_alias_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fbb20fb0b8d714d2aa1891998a5f95ff243c46db --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_coo_tensor_with_dims_meta_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, at::TensorOptions options); +TORCH_API at::Tensor _sparse_coo_tensor_with_dims(int64_t sparse_dim, int64_t dense_dim, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..12344f8e996d845a269b83e45926aef4b540b189 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_csc_tensor_unsafe_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _sparse_csc_tensor_unsafe { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_csc_tensor_unsafe") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data_native.h new file mode 100644 index 0000000000000000000000000000000000000000..ecddb0aa954bcdc11fed80bfd89b7b149c86605e --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_log_softmax_backward_data_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _sparse_log_softmax_backward_data_out(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor log_softmax_backward_sparse_cpu(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +TORCH_API at::Tensor log_softmax_backward_sparse_cuda(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5ea2afa19db4a68848d774e2609704ad8f4f8c3a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_standard_gamma_grad_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _standard_gamma_grad { + 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_standard_gamma_grad") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_standard_gamma_grad(Tensor self, Tensor output) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & output); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & output); +}; + +struct TORCH_API _standard_gamma_grad_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_standard_gamma_grad") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & output, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & output, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h new file mode 100644 index 0000000000000000000000000000000000000000..cd4650111a9eea1cff0904ae491ec028bea79e60 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_cpu.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_to_cpu(Tensor[] tensors) -> Tensor[] +inline ::std::vector _to_cpu(at::TensorList tensors) { + return at::_ops::_to_cpu::call(tensors); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention.h new file mode 100644 index 0000000000000000000000000000000000000000..82479771bfda0ba9f6951d4f7a4f2741ad28398b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_triton_scaled_dot_attention.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor +inline at::Tensor _triton_scaled_dot_attention(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p=0.0) { + return at::_ops::_triton_scaled_dot_attention::call(q, k, v, dropout_p); +} + +// aten::_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _triton_scaled_dot_attention_out(at::Tensor & out, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p=0.0) { + return at::_ops::_triton_scaled_dot_attention_out::call(q, k, v, dropout_p, out); +} +// aten::_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _triton_scaled_dot_attention_outf(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out) { + return at::_ops::_triton_scaled_dot_attention_out::call(q, k, v, dropout_p, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c7f0d66ef91591d7a9866a3e9376b9640ac72299 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor _upsample_nearest_exact1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales=c10::nullopt); +TORCH_API at::Tensor _upsample_nearest_exact1d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales=c10::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a9e414c5d502dd94436968afd7f8ed962e861fea --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor _weight_int4pack_mm(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/alpha_dropout.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/alpha_dropout.h new file mode 100644 index 0000000000000000000000000000000000000000..da10433328e4884e932cd56a7b4a7d994a35ab8b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/alpha_dropout.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor +inline at::Tensor alpha_dropout(const at::Tensor & input, double p, bool train) { + return at::_ops::alpha_dropout::call(input, p, train); +} + +// aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) +inline at::Tensor & alpha_dropout_(at::Tensor & self, double p, bool train) { + return at::_ops::alpha_dropout_::call(self, p, train); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4c6c7b83803311ab6bcc21a33e9f7c68749a147f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool2d_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor avg_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); +TORCH_API at::Tensor & avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); +TORCH_API at::Tensor & avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..296de3ba59fcda0f234375d5d77fe9999fb17340 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_elemt_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API batch_norm_backward_elemt { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::batch_norm_backward_elemt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "batch_norm_backward_elemt(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor sum_dy, Tensor sum_dy_xmu, Tensor count) -> Tensor") + static at::Tensor call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & sum_dy, const at::Tensor & sum_dy_xmu, const at::Tensor & count); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & sum_dy, const at::Tensor & sum_dy_xmu, const at::Tensor & count); +}; + +struct TORCH_API batch_norm_backward_elemt_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::batch_norm_backward_elemt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "batch_norm_backward_elemt.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor sum_dy, Tensor sum_dy_xmu, Tensor count, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & sum_dy, const at::Tensor & sum_dy_xmu, const at::Tensor & count, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & sum_dy, const at::Tensor & sum_dy_xmu, const at::Tensor & count, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bincount_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bincount_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..28f7c0c33e7bef7d2c88687fcd10f7664ad3a3a8 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bincount_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API bincount { + using schema = at::Tensor (const at::Tensor &, const c10::optional &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bincount") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor") + static at::Tensor call(const at::Tensor & self, const c10::optional & weights, int64_t minlength); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional & weights, int64_t minlength); +}; + +struct TORCH_API bincount_out { + using schema = at::Tensor & (const at::Tensor &, const c10::optional &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::bincount") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const c10::optional & weights, int64_t minlength, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional & weights, int64_t minlength, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..410ba97addc361f48364faef9bf8a941cb873adf --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_and_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor bitwise_and(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_and_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..50ba9301cd2b5859c188f7ec83a51e890606381c --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_left_shift_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..72111bbe0846ea0e7288a5336cb112884989d501 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/col_indices_copy_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API col_indices_copy { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::col_indices_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "col_indices_copy(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 col_indices_copy_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::col_indices_copy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/conv_tbc_backward_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/conv_tbc_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cded0a4df325fa85f4f1e531457969b68ebee5ae --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/conv_tbc_backward_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::tuple conv_tbc_backward(const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ba8000d5154050959c0bfa3a44ed9bf00ec09e2d --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..5e018c22f13f5629534c8c13405fc971d02d3358 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cudnn_batch_norm_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API cudnn_batch_norm { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); +}; + +struct TORCH_API cudnn_batch_norm_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::cudnn_batch_norm") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2f0b5bba7d5a68ebdeb3dd6e152c3925dc43b843 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/empty_strided_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={}); +TORCH_API at::Tensor empty_strided_symint(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/erfinv_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/erfinv_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d71197656c6806785d1c030b38e73836284620f6 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/erfinv_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor erfinv(const at::Tensor & self); +TORCH_API at::Tensor & erfinv_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & erfinv_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & erfinv_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..50596d03fe06e591ed571a513c02821724a16b2f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fake_quantize_per_channel_affine_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API fake_quantize_per_channel_affine { + using schema = at::Tensor (const at::Tensor &, const 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::fake_quantize_per_channel_affine") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2704b39f184b620509594d67052fd03f9fd20663 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fmin_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/hspmm.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/hspmm.h new file mode 100644 index 0000000000000000000000000000000000000000..90d058110c9fac32d089ba905acf632afeed7d03 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/hspmm.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hspmm_out(at::Tensor & out, const at::Tensor & mat1, const at::Tensor & mat2) { + return at::_ops::hspmm_out::call(mat1, mat2, out); +} +// aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & hspmm_outf(const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out) { + return at::_ops::hspmm_out::call(mat1, mat2, out); +} + +// aten::hspmm(Tensor mat1, Tensor mat2) -> Tensor +inline at::Tensor hspmm(const at::Tensor & mat1, const at::Tensor & mat2) { + return at::_ops::hspmm::call(mat1, mat2); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..993156e810d1e7fb1576fda00cf1855602473f28 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor igamma(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & igamma_(at::Tensor & self, const at::Tensor & other); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/index_copy_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/index_copy_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f3c852ed8eb41ef9a3d24690b0d41a599430fa45 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/index_copy_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor index_copy(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); +TORCH_API at::Tensor & index_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); +TORCH_API at::Tensor & index_copy_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, at::Tensor & out); +TORCH_API at::Tensor & index_copy_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_complex_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_complex_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cdf22795b74ea5f92f7e7537359496892c31350d --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_complex_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API is_complex { + using schema = bool (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::is_complex") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "is_complex(Tensor self) -> bool") + static bool call(const at::Tensor & self); + static bool redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isfinite_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isfinite_native.h new file mode 100644 index 0000000000000000000000000000000000000000..77e78ebb75a7e6a5b1503f38afb14c3f125ca5c1 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isfinite_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor isfinite(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isposinf.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isposinf.h new file mode 100644 index 0000000000000000000000000000000000000000..b5cef9a951653312a7132a301bc3c1c739b3cb54 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isposinf.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::isposinf(Tensor self) -> Tensor +inline at::Tensor isposinf(const at::Tensor & self) { + return at::_ops::isposinf::call(self); +} + +// aten::isposinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isposinf_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::isposinf_out::call(self, out); +} +// aten::isposinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & isposinf_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::isposinf_out::call(self, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_meta.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..cba3937b64f415653cf2d10b42b176cf3c588a00 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cholesky_ex_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_linalg_cholesky_ex : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, bool upper, bool check_errors); +}; + +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e4195c83ac435051d55bf92aa4880bbf801ff50 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_linalg_ldl_solve_out : public at::meta::structured_linalg_ldl_solve { +void impl(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..fe92df1a38926e7f15fb0f2ab606326f16eef5cd --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vecdot_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_vecdot { + 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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_vecdot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor") + static at::Tensor call(const at::Tensor & x, const at::Tensor & y, int64_t dim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim); +}; + +struct TORCH_API linalg_vecdot_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_vecdot") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..73b2093682d30e1a09ec58993423866c7e9da272 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps=c10::nullopt) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} +// aten::logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & logit_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps, at::Tensor & grad_input) { + return at::_ops::logit_backward_grad_input::call(grad_output, self, eps, grad_input); +} + +// aten::logit_backward(Tensor grad_output, Tensor self, float? eps=None) -> Tensor +inline at::Tensor logit_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps=c10::nullopt) { + return at::_ops::logit_backward::call(grad_output, self, eps); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lt_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lt_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..dce5c55d8f7891f3aeef763d7b5e78339a82b305 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lt_ops.h @@ -0,0 +1,83 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API lt_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +struct TORCH_API lt_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.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 lt_Tensor_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API lt_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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt.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 lt__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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API lt__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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lt_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mean_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mean_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..03dc4796d5397f93dfb0b1ba5342e1354d85d3bc --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mean_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & mean_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..97ba66be13334962a36cdeca8e6ab55d628b5527 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_depthwise_convolution_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); +TORCH_API at::Tensor miopen_depthwise_convolution_symint(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, bool benchmark, bool deterministic); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..792a59b34ff28a468c404afee2d7e5182b9e8921 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/multilabel_margin_loss_forward_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple multilabel_margin_loss_forward_cpu(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out_cpu(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +TORCH_API ::std::tuple multilabel_margin_loss_forward_cuda(const at::Tensor & self, const at::Tensor & target, int64_t reduction); +TORCH_API ::std::tuple multilabel_margin_loss_forward_out_cuda(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/positive_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/positive_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..232d47390e7f5ed442111d9b47707734b1700c47 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/positive_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor positive(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b71980858bfa1643e5b5919b9e26db8ec3c20b4c --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantile_ops.h @@ -0,0 +1,61 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API quantile { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantile") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & q, c10::optional dim, bool keepdim, c10::string_view interpolation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, c10::optional dim, bool keepdim, c10::string_view interpolation); +}; + +struct TORCH_API quantile_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantile") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & q, c10::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, c10::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +}; + +struct TORCH_API quantile_scalar { + using schema = at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantile") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor") + static at::Tensor call(const at::Tensor & self, double q, c10::optional dim, bool keepdim, c10::string_view interpolation); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, c10::optional dim, bool keepdim, c10::string_view interpolation); +}; + +struct TORCH_API quantile_scalar_out { + using schema = at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::quantile") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, double q, c10::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, c10::optional dim, bool keepdim, c10::string_view interpolation, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..35d3d537a32d03d6b22f44e19663d1d8dffbf2f6 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_compositeexplicitautograd_dispatch.h @@ -0,0 +1,50 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional names); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional names); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional generator, c10::optional names); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional generator, c10::optional names); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor rand(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size); +TORCH_API at::Tensor & rand_outf(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & rand_symint_out(at::Tensor & out, c10::SymIntArrayRef size); +TORCH_API at::Tensor & rand_symint_outf(c10::SymIntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor rand(at::IntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor rand_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..2f6b2087e9e002fec4aa7bf25e557bf712285287 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rand_ops.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API rand_names { + using schema = at::Tensor (c10::SymIntArrayRef, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API rand_generator_with_names { + using schema = at::Tensor (c10::SymIntArrayRef, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_with_names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional generator, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API rand { + using schema = at::Tensor (c10::SymIntArrayRef, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API rand_generator { + using schema = at::Tensor (c10::SymIntArrayRef, c10::optional, c10::optional, c10::optional, c10::optional, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") + static at::Tensor call(c10::SymIntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +}; + +struct TORCH_API rand_out { + using schema = at::Tensor & (c10::SymIntArrayRef, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out); +}; + +struct TORCH_API rand_generator_out { + using schema = at::Tensor & (c10::SymIntArrayRef, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, c10::optional generator, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional generator, at::Tensor & out); +}; + +struct TORCH_API rand_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, c10::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional names, at::Tensor & out); +}; + +struct TORCH_API rand_generator_with_names_out { + using schema = at::Tensor & (c10::SymIntArrayRef, c10::optional, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rand") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "generator_with_names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f2e65de4a991db4c1132b8c85307311a0a013f1e --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/reflection_pad3d_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor reflection_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); +TORCH_API at::Tensor reflection_pad3d_backward_symint(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/relu_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/relu_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..988962be84621ddfdc769578f98acca0309baa29 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/relu_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor relu(const at::Tensor & self); +TORCH_API at::Tensor & relu_(at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_native.h new file mode 100644 index 0000000000000000000000000000000000000000..b835ffabf6b50062b766847ec3363cb6b834063b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/replication_pad2d_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_replication_pad2d_out_cpu : public at::meta::structured_replication_pad2d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +struct TORCH_API structured_replication_pad2d_out_cuda : public at::meta::structured_replication_pad2d { +void impl(const at::Tensor & self, at::ArrayRef padding, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3e04092b76efe4dd6d012aad0c34c21519a6f36f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor rsqrt(const at::Tensor & self); +TORCH_API at::Tensor & rsqrt_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_meta.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..b36933aa0bf9f0ed465c5ddcf75cd04a6cb2386d --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rsqrt_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_rsqrt : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..04728d6bcfe9a0bc4eda540d65d977c8417fe1a9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sigmoid_backward_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d984b785b39e00e01c138705ffe39f9471d8a5f9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor silu_backward(const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); +TORCH_API at::Tensor & silu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..944e3349c01b42cf0231df775cb6a16705eb2488 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/silu_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor silu(const at::Tensor & self); +TORCH_API at::Tensor & silu_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & silu_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & silu_(at::Tensor & self); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/slice_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/slice_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6a5c3d5e0820c3a87e650f43e485a25bb6a59113 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/slice_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor slice(const at::Tensor & self, int64_t dim=0, c10::optional start=c10::nullopt, c10::optional end=c10::nullopt, int64_t step=1); +TORCH_API at::Tensor slice_symint(const at::Tensor & self, int64_t dim=0, c10::optional start=c10::nullopt, c10::optional end=c10::nullopt, c10::SymInt step=1); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/softmax_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..5321c8a3892631097788b0cbe470645a5ebcd8f0 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/softmax_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Tensor softmax(const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor softmax(const at::Tensor & self, at::Dimname dim, c10::optional dtype=c10::nullopt); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..285bf9da62f17d1404681e45e4c2dba3d071bf46 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_chebyshev_polynomial_v_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor special_chebyshev_polynomial_v(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_out(at::Tensor & out, const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_outf(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_chebyshev_polynomial_v(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_out(at::Tensor & out, const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_chebyshev_polynomial_v_outf(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d522b79316f1bcd91870e6e8d8ee651a9e559b20 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_erf_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor special_erf(const at::Tensor & self); +TORCH_API at::Tensor & special_erf_out(const at::Tensor & self, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..781f7c8eec6e8616c5d5a5ef445067e586d79220 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_hermite_polynomial_he_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_hermite_polynomial_he(const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & n); +TORCH_API at::Tensor & special_hermite_polynomial_he_outf(const at::Tensor & x, const at::Tensor & n, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7504ffc7a966306c574a6fd629595cacfe293b7b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_i1_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor special_i1(const at::Tensor & self); +TORCH_API at::Tensor & special_i1_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_i1_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..762468cc36c1b0a638121264dff2ad182c799c89 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor special_modified_bessel_i0(const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i0_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_modified_bessel_i0_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h new file mode 100644 index 0000000000000000000000000000000000000000..04478ef2bc0dde3cbee259990137bee646965c97 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_shifted_chebyshev_polynomial_t_native.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_special_shifted_chebyshev_polynomial_t_out : public at::meta::structured_special_shifted_chebyshev_polynomial_t { +void impl(const at::Tensor & x, const at::Tensor & n, const at::Tensor & out); +}; +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Scalar & x, const at::Tensor & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(const at::Scalar & x, const at::Tensor & n, at::Tensor & out); +TORCH_API at::Tensor special_shifted_chebyshev_polynomial_t(const at::Tensor & x, const at::Scalar & n); +TORCH_API at::Tensor & special_shifted_chebyshev_polynomial_t_out(const at::Tensor & x, const at::Scalar & n, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..44634d72c4541d512729ac492766758ccfc3c657 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_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 +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API c10::SymInt sym_size(const at::Tensor & self, int64_t dim); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..87b98db1bb8b19465105df22d7ceea633b7ee7f8 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_size_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API sym_size_int { + using schema = c10::SymInt (const at::Tensor &, int64_t); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::sym_size") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sym_size.int(Tensor self, int dim) -> SymInt") + static c10::SymInt call(const at::Tensor & self, int64_t dim); + static c10::SymInt redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9828d6c5f78695d549761100739ffba887929ae5 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sym_storage_offset_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API c10::SymInt sym_storage_offset(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..599359b395b6b8ca6a5a34ed3fdce643d947d812 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/triplet_margin_loss_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +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_STR_INL_EXCEPT_WIN_CUDA(name, "aten::triplet_margin_loss") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(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/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/view_copy.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/view_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..ecc673f8b0f560c43aa1a53a79f91aa9ad26b4fc --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/view_copy.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::view_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor view_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy::call(self, c10::fromIntArrayRefSlow(size)); +} +namespace symint { + template ::value>> + at::Tensor view_copy(const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy::call(self, c10::fromIntArrayRefSlow(size)); + } +} + +// aten::view_copy(Tensor self, SymInt[] size) -> Tensor +inline at::Tensor view_copy_symint(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy::call(self, size); +} +namespace symint { + template ::value>> + at::Tensor view_copy(const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy::call(self, size); + } +} + +// aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor +inline at::Tensor view_copy(const at::Tensor & self, at::ScalarType dtype) { + return at::_ops::view_copy_dtype::call(self, dtype); +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef size) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & view_copy_outf(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy_out::call(self, size, out); +} +namespace symint { + template ::value>> + at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef size) { + return at::_ops::view_copy_out::call(self, size, out); + } +} + +// aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_symint_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, size, out); +} +namespace symint { + template ::value>> + at::Tensor & view_copy_outf(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::view_copy_out::call(self, size, out); + } +} + +// aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_out(at::Tensor & out, const at::Tensor & self, at::ScalarType dtype) { + return at::_ops::view_copy_dtype_out::call(self, dtype, out); +} +// aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & view_copy_outf(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out) { + return at::_ops::view_copy_dtype_out::call(self, dtype, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros.h new file mode 100644 index 0000000000000000000000000000000000000000..d0db85c1045296152b4f81e19ec11427575ae27c --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros.h @@ -0,0 +1,131 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}) { + return at::_ops::zeros_names::call(size, names, optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::zeros_names::call(size, names, dtype, layout, device, pin_memory); +} + +// aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::zeros::call(c10::fromIntArrayRefSlow(size), optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor zeros(at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::zeros::call(c10::fromIntArrayRefSlow(size), optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::zeros::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor zeros(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::zeros::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory); + } +} + +// aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::zeros::call(size, optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +namespace symint { + template ::value>> + at::Tensor zeros(c10::SymIntArrayRef size, at::TensorOptions options={}) { + return at::_ops::zeros::call(size, optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); + } +} + +// aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor zeros_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::zeros::call(size, dtype, layout, device, pin_memory); +} +namespace symint { + template ::value>> + at::Tensor zeros(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::zeros::call(size, dtype, layout, device, pin_memory); + } +} + +// aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::zeros_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & zeros_out(at::Tensor & out, at::IntArrayRef size) { + return at::_ops::zeros_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::zeros_out::call(c10::fromIntArrayRefSlow(size), out); +} +namespace symint { + template ::value>> + at::Tensor & zeros_outf(at::IntArrayRef size, at::Tensor & out) { + return at::_ops::zeros_out::call(c10::fromIntArrayRefSlow(size), out); + } +} + +// aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_symint_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::zeros_out::call(size, out); +} +namespace symint { + template ::value>> + at::Tensor & zeros_out(at::Tensor & out, c10::SymIntArrayRef size) { + return at::_ops::zeros_out::call(size, out); + } +} + +// aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::zeros_out::call(size, out); +} +namespace symint { + template ::value>> + at::Tensor & zeros_outf(c10::SymIntArrayRef size, at::Tensor & out) { + return at::_ops::zeros_out::call(size, out); + } +} + +// aten::zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_out(at::Tensor & out, at::IntArrayRef size, c10::optional names) { + return at::_ops::zeros_names_out::call(size, names, out); +} +// aten::zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & zeros_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out) { + return at::_ops::zeros_names_out::call(size, names, out); +} + +}