diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..417443594d4582a7dc37d0dad5f0177fef4763bc --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_backward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7fe191bf0037a7db4435ac2356e1255f73e5fb1a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_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 _convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled); +TORCH_API at::Tensor _convolution_symint(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..077b8a4c0201b0dea8408721ad478b9e649ab18b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_convolution_ops.h @@ -0,0 +1,50 @@ +#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 _convolution { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, bool, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); +}; + +struct TORCH_API _convolution_deprecated { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, at::IntArrayRef, c10::SymInt, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "deprecated") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, int[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled); +}; + +struct TORCH_API _convolution_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, bool, c10::SymIntArrayRef, c10::SymInt, bool, bool, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_convolution") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[] stride, SymInt[] padding, SymInt[] dilation, bool transposed, SymInt[] output_padding, SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, c10::SymInt groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..388b8cb303415041b671f78022462b9458e98921 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_cudnn_rnn_backward_cuda_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); +TORCH_API ::std::tuple> _cudnn_rnn_backward_symint(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.h new file mode 100644 index 0000000000000000000000000000000000000000..7bf898f357700ef80e299ebe55f261a8f8cabe91 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_atan.h @@ -0,0 +1,44 @@ +#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::_foreach_atan(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_atan(at::TensorList self) { + return at::_ops::_foreach_atan::call(self); +} + +// aten::_foreach_atan_(Tensor(a!)[] self) -> () +inline void _foreach_atan_(at::TensorList self) { + return at::_ops::_foreach_atan_::call(self); +} + +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_atan_out::call(self, out); +} +// aten::_foreach_atan.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_atan_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_atan_out::call(self, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.h new file mode 100644 index 0000000000000000000000000000000000000000..7a8d8def174aa87365e9a5dfdc70e9e126a2c3c7 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_erf.h @@ -0,0 +1,44 @@ +#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::_foreach_erf(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_erf(at::TensorList self) { + return at::_ops::_foreach_erf::call(self); +} + +// aten::_foreach_erf_(Tensor(a!)[] self) -> () +inline void _foreach_erf_(at::TensorList self) { + return at::_ops::_foreach_erf_::call(self); +} + +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_erf_out::call(self, out); +} +// aten::_foreach_erf.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_erf_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_erf_out::call(self, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.h new file mode 100644 index 0000000000000000000000000000000000000000..48fcbeb0ca9ba1d9ab20817def4d1241a454d1f7 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_trunc.h @@ -0,0 +1,44 @@ +#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::_foreach_trunc(Tensor[] self) -> Tensor[] +inline ::std::vector _foreach_trunc(at::TensorList self) { + return at::_ops::_foreach_trunc::call(self); +} + +// aten::_foreach_trunc_(Tensor(a!)[] self) -> () +inline void _foreach_trunc_(at::TensorList self) { + return at::_ops::_foreach_trunc_::call(self); +} + +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_out(at::TensorList out, at::TensorList self) { + return at::_ops::_foreach_trunc_out::call(self, out); +} +// aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () +inline void _foreach_trunc_outf(at::TensorList self, at::TensorList out) { + return at::_ops::_foreach_trunc_out::call(self, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..6f1c0550e19e7b03a65e40c75144d9c241905423 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_fw_primal_copy.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::_fw_primal_copy(Tensor self, int level) -> Tensor +inline at::Tensor _fw_primal_copy(const at::Tensor & self, int64_t level) { + return at::_ops::_fw_primal_copy::call(self, level); +} + +// aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fw_primal_copy_out(at::Tensor & out, const at::Tensor & self, int64_t level) { + return at::_ops::_fw_primal_copy_out::call(self, level, out); +} +// aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _fw_primal_copy_outf(const at::Tensor & self, int64_t level, at::Tensor & out) { + return at::_ops::_fw_primal_copy_out::call(self, level, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c0aa6efd611de34e123d9c35c584939772a1c39a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_grid_sampler_2d_cpu_fallback_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 _grid_sampler_2d_cpu_fallback(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +TORCH_API at::Tensor & _grid_sampler_2d_cpu_fallback_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +TORCH_API at::Tensor & _grid_sampler_2d_cpu_fallback_outf(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.h new file mode 100644 index 0000000000000000000000000000000000000000..82a3a2eb6349b384eb91d2d3d627a40f77e92efe --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dual_copy.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::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor +inline at::Tensor _make_dual_copy(const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy::call(primal, tangent, level); +} + +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_out(at::Tensor & out, const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, out); +} +// aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _make_dual_copy_outf(const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out) { + return at::_ops::_make_dual_copy_out::call(primal, tangent, level, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..2ce01c401096a81e9158ffdd48a6424fdf3c287a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_masked_softmax_backward_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 _masked_softmax_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional dim=c10::nullopt); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h new file mode 100644 index 0000000000000000000000000000000000000000..84d3bb65e1473400f73ac1c5b51e84502df7df90 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_compressed_tensor_unsafe.h @@ -0,0 +1,34 @@ +#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::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::TensorOptions options={}) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt()); +} +// aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor +inline at::Tensor _sparse_compressed_tensor_unsafe(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory) { + return at::_ops::_sparse_compressed_tensor_unsafe::call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0609d66ba69a1dc17f652917842244fa39dfaae9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_mm_reduce_impl_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 _sparse_mm_reduce_impl_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & other, c10::string_view reduce); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ada52eef057dfebe7bf8e6c4491d8f1fad7236cb --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sparse_matmul_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 & _sparse_sparse_matmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & _sparse_sparse_matmul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_native.h new file mode 100644 index 0000000000000000000000000000000000000000..a40b83487868746413074479be59a95ab4547014 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_semi_structured_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 _to_sparse_semi_structured(const at::Tensor & dense); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..eac1eebc8b77596888aed824c2c7735a1ef1257a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_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_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d7b0310b745941fa1a5c73c8ea1d2c6a839036ff --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..b9030ece45af4f36d4cdfeba0a86dbc431446981 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_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_bilinear2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor _upsample_bilinear2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..df7d1d6cddbf5821c5c16a5eb9cfeeef0bc93250 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_nearest_exact1d_ops.h @@ -0,0 +1,50 @@ +#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 _upsample_nearest_exact1d_vec { + using schema = at::Tensor (const at::Tensor &, at::OptionalSymIntArrayRef, c10::optional>); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_upsample_nearest_exact1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "vec") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor") + static at::Tensor call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional> scale_factors); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional> scale_factors); +}; + +struct TORCH_API _upsample_nearest_exact1d_out { + using schema = at::Tensor & (const 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::_upsample_nearest_exact1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_upsample_nearest_exact1d.out(Tensor self, SymInt[1] output_size, float? scales=None, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales, at::Tensor & out); +}; + +struct TORCH_API _upsample_nearest_exact1d { + using schema = at::Tensor (const at::Tensor &, c10::SymIntArrayRef, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_upsample_nearest_exact1d") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_upsample_nearest_exact1d(Tensor self, SymInt[1] output_size, float? scales=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ad6d5abfc71a8e55a98d0cd4c1da6ce999413a71 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_use_cudnn_ctc_loss_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 bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank); +TORCH_API bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface.h new file mode 100644 index 0000000000000000000000000000000000000000..f64c6ff2844685285187c0904ae29ee5e5774fdc --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface.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::_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor) +inline ::std::tuple _weight_norm_interface(const at::Tensor & v, const at::Tensor & g, int64_t dim=0) { + return at::_ops::_weight_norm_interface::call(v, g, dim); +} + +// aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_out(at::Tensor & out0, at::Tensor & out1, const at::Tensor & v, const at::Tensor & g, int64_t dim=0) { + return at::_ops::_weight_norm_interface_out::call(v, g, dim, out0, out1); +} +// aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) +inline ::std::tuple _weight_norm_interface_outf(const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1) { + return at::_ops::_weight_norm_interface_out::call(v, g, dim, out0, out1); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/add_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/add_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7f3c55cb2f5f46b050551785a22d87c9defa66f4 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/add_native.h @@ -0,0 +1,43 @@ +#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_ufunc_add_CPU : public at::meta::structured_add_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, const at::Tensor & out); +}; +struct TORCH_API structured_ufunc_add_CUDA : public at::meta::structured_add_Tensor { +void impl(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, const at::Tensor & out); +}; +TORCH_API at::Tensor NestedTensor_add_Tensor(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & NestedTensor_add__Tensor(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor add_sparse(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_out_sparse_cpu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & add_sparse_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_out_sparse_cuda(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor add_sparse_csr(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_out_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & add_sparse_csr_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_out_sparse_csr_cuda(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor mkldnn_add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & mkldnn_add_out(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & mkldnn_add_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor add_zerotensor(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor add(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +TORCH_API at::Tensor & add_Scalar_out(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out); +TORCH_API at::Tensor & add_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax_meta.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..74438d94d66c2f5675528ccb2bec006caec8100c --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/aminmax_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_aminmax : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, c10::optional dim, bool keepdim); +}; + +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/argmax_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/argmax_native.h new file mode 100644 index 0000000000000000000000000000000000000000..55e450a3e083a977325a7d266aa65cb168b41c08 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/argmax_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_argmax_out : public at::meta::structured_argmax { +void impl(const at::Tensor & self, c10::optional dim, bool keepdim, const at::Tensor & out); +}; +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce13f819850165905c013490f5a14d45db0f0ccd --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/as_strided_scatter_compositeexplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 & as_strided_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset=c10::nullopt); +TORCH_API at::Tensor & as_strided_scatter_outf(const at::Tensor & self, const at::Tensor & src, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset, at::Tensor & out); +TORCH_API at::Tensor & as_strided_scatter_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset=c10::nullopt); +TORCH_API at::Tensor & as_strided_scatter_symint_outf(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional storage_offset, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..3abf2e8d9d832f19026e66aa85d8a2d7de40c8d3 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/bmm_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 bmm(const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); +TORCH_API at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosh.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosh.h new file mode 100644 index 0000000000000000000000000000000000000000..dc6b6090d3cc17cf738bc88d060c95569c9ba53e --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosh.h @@ -0,0 +1,44 @@ +#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::cosh(Tensor self) -> Tensor +inline at::Tensor cosh(const at::Tensor & self) { + return at::_ops::cosh::call(self); +} + +// aten::cosh_(Tensor(a!) self) -> Tensor(a!) +inline at::Tensor & cosh_(at::Tensor & self) { + return at::_ops::cosh_::call(self); +} + +// aten::cosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cosh_out(at::Tensor & out, const at::Tensor & self) { + return at::_ops::cosh_out::call(self, out); +} +// aten::cosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & cosh_outf(const at::Tensor & self, at::Tensor & out) { + return at::_ops::cosh_out::call(self, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosine_embedding_loss_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosine_embedding_loss_native.h new file mode 100644 index 0000000000000000000000000000000000000000..51f2da4418505e61128802642a05415b785a85b3 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/cosine_embedding_loss_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 cosine_embedding_loss(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin=0.0, int64_t reduction=at::Reduction::Mean); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag.h new file mode 100644 index 0000000000000000000000000000000000000000..f9a55d4e2a4a1c05e7d7728acf7511d76d395f69 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_bag.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::embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false) { + return at::_ops::embedding_bag::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset); +} + +// aten::embedding_bag.padding_idx(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, bool include_last_offset, int? padding_idx) -> (Tensor, Tensor, Tensor, Tensor) +inline ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional & per_sample_weights, bool include_last_offset, c10::optional padding_idx) { + return at::_ops::embedding_bag_padding_idx::call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_sparse_backward_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_sparse_backward_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce2ea61127e9199526ff5c41eb2a8a81e3b3a743 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/embedding_sparse_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 at::Tensor embedding_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.h new file mode 100644 index 0000000000000000000000000000000000000000..79355ce82797f98045df7f70d9e3ff5c4d15d2d4 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fft2.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::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft2(const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm); + } +} + +// aten::fft_fft2(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor +inline at::Tensor fft_fft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2::call(self, s, dim, norm); +} +namespace symint { + template ::value>> + at::Tensor fft_fft2(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2::call(self, s, dim, norm); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s.has_value() ? c10::make_optional(c10::fromIntArrayRefSlow(*s)) : c10::nullopt, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_symint_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_out(at::Tensor & out, const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); + } +} + +// aten::fft_fft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & fft_fft2_symint_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); +} +namespace symint { + template ::value>> + at::Tensor & fft_fft2_outf(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out) { + return at::_ops::fft_fft2_out::call(self, s, dim, norm, out); + } +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftshift.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftshift.h new file mode 100644 index 0000000000000000000000000000000000000000..c240a576e0a7254ba82adca9f7b2db7338ecebc0 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_fftshift.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::fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor +inline at::Tensor fft_fftshift(const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt) { + return at::_ops::fft_fftshift::call(self, dim); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_native.h new file mode 100644 index 0000000000000000000000000000000000000000..d13601d25caf076199907e7f50db97e8a1e7c0d3 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfft2_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 fft_rfft2_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::IntArrayRef dim={-2,-1}, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_rfft2_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::IntArrayRef dim, c10::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fill_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fill_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6b8dd4e8a5906ce0be42b0b49045176c038b60ff --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/fill_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 & fill_(at::Tensor & self, const at::Scalar & value); +TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Tensor & value); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_native.h new file mode 100644 index 0000000000000000000000000000000000000000..5c791e5971c54d1d17a39872f541ec8a3d525730 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/flipud_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 flipud(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..add8e67dd2cfc29ef7a6533c46619132417d4aac --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 floor(const at::Tensor & self); +TORCH_API at::Tensor & floor_(at::Tensor & self); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_meta.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..9a2f2f50375054d9bb9b9cd3e788aca274174fa7 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/floor_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_floor : 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/full_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/full_native.h new file mode 100644 index 0000000000000000000000000000000000000000..739b3c73785cfa4df42ce8c601cda035851682ee --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/full_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 at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional names, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & full_names_out(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & full_out(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/gather_meta.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/gather_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..937017142f0e35ac3aed2ee764d67f49c14619c4 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/gather_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_gather : public at::impl::MetaBase { + + + void meta(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad); +}; + +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..63c9f8cfa49edd9df9ceea4ea2dc24f23119aaba --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/grid_sampler_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#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 grid_sampler { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, int64_t, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::grid_sampler") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "grid_sampler(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..f6a35eabdf4b0273ee49d686ae0fa2620639b073 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/igamma_ops.h @@ -0,0 +1,50 @@ +#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 igamma_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::igamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igamma.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 igamma { + 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::igamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igamma(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 igamma_ { + 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::igamma_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "igamma_(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/index_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/index_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a80ef847bc4414776202fc85a10bcc0c2fc0e091 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/index_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 index(const at::Tensor & self, const c10::List> & indices); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..786e95ec05c3bf81f1dde43e57d5c68da12ff625 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_coalesced_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_coalesced { + 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_coalesced") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "is_coalesced(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/is_nonzero_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_nonzero_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4aa71bb97dee0b3a15c86c3638ecd8c5ce03dd79 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/is_nonzero_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 bool is_nonzero(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fcbf2a10d38a8181774357e3d3d92e2bb508f8c9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/isin_compositeexplicitautogradnonfunctional_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 compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); +TORCH_API at::Tensor isin(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..dd7918ccbd17e4bb3da31aa151876c624007634f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/leaky_relu_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_leaky_relu_out : public at::meta::structured_leaky_relu { +void impl(const at::Tensor & self, const at::Scalar & negative_slope, const at::Tensor & out); +}; +TORCH_API at::Tensor leaky_relu_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); +TORCH_API at::Tensor & leaky_relu_out_quantized_cpu(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); +TORCH_API at::Tensor & leaky_relu_quantized_cpu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..b127f01036d92fc97c5ebb6ea56d3952c237d3ae --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/lerp_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 lerp__Scalar { + using schema = at::Tensor & (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::lerp_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp_.Scalar(Tensor(a!) self, Tensor end, Scalar weight) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +}; + +struct TORCH_API lerp__Tensor { + using schema = at::Tensor & (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::lerp_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp_.Tensor(Tensor(a!) self, Tensor end, Tensor weight) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +}; + +struct TORCH_API lerp_Scalar_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp.Scalar_out(Tensor self, Tensor end, Scalar weight, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); +}; + +struct TORCH_API lerp_Tensor_out { + using schema = at::Tensor & (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::lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp.Tensor_out(Tensor self, Tensor end, Tensor weight, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); +}; + +struct TORCH_API lerp_Scalar { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp.Scalar(Tensor self, Tensor end, Scalar weight) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); +}; + +struct TORCH_API lerp_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::lerp") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "lerp.Tensor(Tensor self, Tensor end, Tensor weight) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond.h new file mode 100644 index 0000000000000000000000000000000000000000..e9b3618b7a3e2c1fa2e1b9df2b728789e397d5cd --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_cond.h @@ -0,0 +1,53 @@ +#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::linalg_cond(Tensor self, Scalar? p=None) -> Tensor +inline at::Tensor linalg_cond(const at::Tensor & self, const c10::optional & p=c10::nullopt) { + return at::_ops::linalg_cond::call(self, p); +} + +// aten::linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, const c10::optional & p=c10::nullopt) { + return at::_ops::linalg_cond_out::call(self, p, out); +} +// aten::linalg_cond.out(Tensor self, Scalar? p=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_outf(const at::Tensor & self, const c10::optional & p, at::Tensor & out) { + return at::_ops::linalg_cond_out::call(self, p, out); +} + +// aten::linalg_cond.p_str(Tensor self, str p) -> Tensor +inline at::Tensor linalg_cond(const at::Tensor & self, c10::string_view p) { + return at::_ops::linalg_cond_p_str::call(self, p); +} + +// aten::linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_out(at::Tensor & out, const at::Tensor & self, c10::string_view p) { + return at::_ops::linalg_cond_p_str_out::call(self, p, out); +} +// aten::linalg_cond.p_str_out(Tensor self, str p, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & linalg_cond_outf(const at::Tensor & self, c10::string_view p, at::Tensor & out) { + return at::_ops::linalg_cond_p_str_out::call(self, p, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_native.h new file mode 100644 index 0000000000000000000000000000000000000000..0bae829e9ce8532c642233056505a7ed4f91d66a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_backward_weights_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 ::std::tuple mkldnn_linear_backward_weights_out(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple mkldnn_linear_backward_weights(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_native.h new file mode 100644 index 0000000000000000000000000000000000000000..be62a413cc163ddd7d66ab3b72ac0915bafba504 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_linear_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 & mkldnn_linear_out(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::Tensor & out); +TORCH_API at::Tensor mkldnn_linear(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias={}); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8eee96e8c6150b72f9cad8299d0b182612559880 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_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 ::std::tuple mkldnn_rnn_layer_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +TORCH_API ::std::tuple mkldnn_rnn_layer_outf(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..780cef22d8a893fbddc59ba98278afd7d9db45ae --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/narrow_compositeimplicitautograd_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length); +TORCH_API at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length); +TORCH_API at::Tensor narrow_symint(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aaebcf52053ef71d650c39eac04057f1f79d1ea9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/native_layer_norm_backward_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, const c10::optional & bias, ::std::array output_mask); +TORCH_API ::std::tuple native_layer_norm_backward_symint(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, const c10::optional & bias, ::std::array output_mask); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/pdist.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/pdist.h new file mode 100644 index 0000000000000000000000000000000000000000..c0e5aa2371dad3c37b776125294f06df6e97ea12 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/pdist.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::pdist(Tensor self, float p=2) -> Tensor +inline at::Tensor pdist(const at::Tensor & self, double p=2) { + return at::_ops::pdist::call(self, p); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_nll_loss_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_nll_loss_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..9536452bfa967eb81258460171bcb32e068f927f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/poisson_nll_loss_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 poisson_nll_loss(const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/qr.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/qr.h new file mode 100644 index 0000000000000000000000000000000000000000..fa830fb615a3e104da7a1e98b41f7ee9706ac4f5 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/qr.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::qr.Q(Tensor self, bool some=True, *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) +inline ::std::tuple qr_out(at::Tensor & Q, at::Tensor & R, const at::Tensor & self, bool some=true) { + return at::_ops::qr_Q::call(self, some, Q, R); +} +// aten::qr.Q(Tensor self, bool some=True, *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) +inline ::std::tuple qr_outf(const at::Tensor & self, bool some, at::Tensor & Q, at::Tensor & R) { + return at::_ops::qr_Q::call(self, some, Q, R); +} + +// aten::qr(Tensor self, bool some=True) -> (Tensor Q, Tensor R) +inline ::std::tuple qr(const at::Tensor & self, bool some=true) { + return at::_ops::qr::call(self, some); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_cpu_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a49cea555f322ad11dbe5ac72db7a173d446f07e --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantize_per_tensor_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 quantize_per_tensor(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); +TORCH_API at::Tensor quantize_per_tensor(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); +TORCH_API ::std::vector quantize_per_tensor(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype); + +} // namespace cpu +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool2d.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool2d.h new file mode 100644 index 0000000000000000000000000000000000000000..13cce5d369e0491b0864e92855701fff2cbdc348 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/quantized_max_pool2d.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::quantized_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor +inline at::Tensor quantized_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::quantized_max_pool2d::call(self, kernel_size, stride, padding, dilation, ceil_mode); +} + +// aten::quantized_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantized_max_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false) { + return at::_ops::quantized_max_pool2d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} +// aten::quantized_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & quantized_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { + return at::_ops::quantized_max_pool2d_out::call(self, kernel_size, stride, padding, dilation, ceil_mode, out); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/randn_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/randn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ca843b40a3a2e1f879cd5d3eb2a5d48632faed7a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/randn_compositeexplicitautograd_dispatch.h @@ -0,0 +1,46 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: 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 randn(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, c10::optional generator, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn_symint(c10::SymIntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, c10::optional names); +TORCH_API at::Tensor & randn_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional names); +TORCH_API at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor randn(at::IntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn(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 randn_symint(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor randn_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 & randn_out(at::Tensor & out, at::IntArrayRef size, c10::optional generator, c10::optional names); +TORCH_API at::Tensor & randn_outf(at::IntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor & randn_symint_out(at::Tensor & out, c10::SymIntArrayRef size, c10::optional generator, c10::optional names); +TORCH_API at::Tensor & randn_symint_outf(c10::SymIntArrayRef size, c10::optional generator, c10::optional names, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_relu_cell_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_relu_cell_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..0bf099eb614d36598e6cb568a6a6440c5dcba927 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/rnn_relu_cell_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 rnn_relu_cell { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::rnn_relu_cell") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "rnn_relu_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor") + static at::Tensor call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional & b_ih, const c10::optional & b_hh); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional & b_ih, const c10::optional & b_hh); +}; + +}} // namespace at::_ops diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f9f4522c159a31a7738da8a98282b609341b0da8 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/scatter_cuda_dispatch.h @@ -0,0 +1,38 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); +TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); +TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out); +TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sign_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sign_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..e93ccf0367d83c3eeae71196b1fa051992eba8da --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/sign_ops.h @@ -0,0 +1,50 @@ +#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 sign { + 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::sign") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign(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 sign_ { + using schema = 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::sign_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign_(Tensor(a!) self) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self); +}; + +struct TORCH_API sign_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::sign") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "sign.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/softplus_backward.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/softplus_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..fc5fdfa8ff84b659ac6c895274c7439a0e2da020 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/softplus_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::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softplus_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { + return at::_ops::softplus_backward_grad_input::call(grad_output, self, beta, threshold, grad_input); +} +// aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) +inline at::Tensor & softplus_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input) { + return at::_ops::softplus_backward_grad_input::call(grad_output, self, beta, threshold, grad_input); +} + +// aten::softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor +inline at::Tensor softplus_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { + return at::_ops::softplus_backward::call(grad_output, self, beta, threshold); +} + +} diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_ops.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..a46c656a48a1972ec94af694b5779be129ca206b --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_digamma_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 special_digamma { + 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::special_digamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_digamma(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 special_digamma_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::special_digamma") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_digamma.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/special_erfinv_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_erfinv_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f013747c084c3db2399f9e117554b5319bebca87 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_erfinv_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 special_erfinv(const at::Tensor & self); +TORCH_API at::Tensor & special_erfinv_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & special_erfinv_outf(const at::Tensor & self, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammainc_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammainc_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70bb81f7df0e8a24bd9c9d620ce902eda845e1f5 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_gammainc_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 special_gammainc(const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_gammainc_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); +TORCH_API at::Tensor & special_gammainc_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_round_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_round_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..932694c6006acc11d4147ba9f864d6588e44b887 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/special_round_compositeimplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 special_round(const at::Tensor & self, int64_t decimals=0); +TORCH_API at::Tensor & special_round_out(at::Tensor & out, const at::Tensor & self, int64_t decimals=0); +TORCH_API at::Tensor & special_round_outf(const at::Tensor & self, int64_t decimals, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/stft_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/stft_native.h new file mode 100644 index 0000000000000000000000000000000000000000..4e69782a2307cd91f493b358a7475c61e88a715f --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/stft_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 stft(const at::Tensor & self, int64_t n_fft, c10::optional hop_length=c10::nullopt, c10::optional win_length=c10::nullopt, const c10::optional & window={}, bool normalized=false, c10::optional onesided=c10::nullopt, c10::optional return_complex=c10::nullopt); +TORCH_API at::Tensor stft(const at::Tensor & self, int64_t n_fft, c10::optional hop_length=c10::nullopt, c10::optional win_length=c10::nullopt, const c10::optional & window={}, bool center=true, c10::string_view pad_mode="reflect", bool normalized=false, c10::optional onesided=c10::nullopt, c10::optional return_complex=c10::nullopt); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/t_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..8f001ff5cbb6e8980286929dcc5ec848006c5767 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/t_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 t(const at::Tensor & self); +TORCH_API at::Tensor & t_(at::Tensor & self); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..53b572dd4dcdd6d9b1c584c250c3ea2b989fb7e2 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/tensor_split_compositeimplicitautograd_dispatch.h @@ -0,0 +1,27 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: 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::vector tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0); +TORCH_API ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymInt sections, int64_t dim=0); +TORCH_API ::std::vector tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0); +TORCH_API ::std::vector tensor_split_symint(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim=0); +TORCH_API ::std::vector tensor_split(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim=0); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/thnn_conv2d_compositeimplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/thnn_conv2d_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4690e7cf42eb5e54c14423364b08e04725ee9b5c --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/thnn_conv2d_compositeimplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 thnn_conv2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0); +TORCH_API at::Tensor thnn_conv2d_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)); +TORCH_API at::Tensor & thnn_conv2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0); +TORCH_API at::Tensor & thnn_conv2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); +TORCH_API at::Tensor & thnn_conv2d_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0)); +TORCH_API at::Tensor & thnn_conv2d_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef kernel_size, const c10::optional & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & out); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ffe337e060a4d955b94df5b38c363c2be34f05aa --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_bilinear2d_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_bilinear2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_bilinear2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_bilinear2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_cuda_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aba9dffe4acaf04178b97ce6fd5ceaf9b9756145 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest3d_backward_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_nearest3d_backward_symint(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); +TORCH_API at::Tensor & upsample_nearest3d_backward_symint_out(at::Tensor & grad_input, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest3d_backward_symint_outf(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_native.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_native.h new file mode 100644 index 0000000000000000000000000000000000000000..120fa1e4ff7e8f8dceb95d34fc943240994481f8 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/var_mean_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 + + +namespace at { +namespace native { +TORCH_API ::std::tuple var_mean(const at::Tensor & self, bool unbiased=true); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean_correction_out(const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim, at::Tensor & out0, at::Tensor & out1); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, bool unbiased=true, bool keepdim=false); +TORCH_API ::std::tuple var_mean(const at::Tensor & self, at::DimnameList dim, const c10::optional & correction=c10::nullopt, bool keepdim=false); +} // namespace native +} // namespace at diff --git a/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_compositeexplicitautograd_dispatch.h b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..cccf22d5e96f0851d0ca80f821f3e56abea0b7b2 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/torch/include/ATen/ops/zeros_compositeexplicitautograd_dispatch.h @@ -0,0 +1,34 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#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 zeros(at::IntArrayRef size, c10::optional names, at::TensorOptions options={}); +TORCH_API at::Tensor zeros(at::IntArrayRef size, c10::optional names, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & zeros_out(at::Tensor & out, at::IntArrayRef size, c10::optional names); +TORCH_API at::Tensor & zeros_outf(at::IntArrayRef size, c10::optional names, at::Tensor & out); +TORCH_API at::Tensor zeros(at::IntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor zeros(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor zeros_symint(c10::SymIntArrayRef size, at::TensorOptions options={}); +TORCH_API at::Tensor zeros_symint(c10::SymIntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); +TORCH_API at::Tensor & zeros_out(at::Tensor & out, at::IntArrayRef size); +TORCH_API at::Tensor & zeros_outf(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor & zeros_symint_out(at::Tensor & out, c10::SymIntArrayRef size); +TORCH_API at::Tensor & zeros_symint_outf(c10::SymIntArrayRef size, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at