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- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_native.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_amp_update_scale_cpu_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_batch_norm_with_update_ops.h +50 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Long.h +30 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_coalesced.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta.h +27 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h +24 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_dim_arange.h +30 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_efficientzerotensor.h +113 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_compositeexplicitautograd_dispatch.h +24 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_tanh_compositeexplicitautograd_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h +24 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_svd_native.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_local_scalar_dense.h +30 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_mixed_dtypes_linear_ops.h +28 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward.h +47 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sobol_engine_initialize_state_ops.h +28 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_log_softmax_ops.h +61 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax.h +49 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_ops.h +28 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_ops.h +28 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/abs.h +44 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool1d_compositeimplicitautograd_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/addcdiv_meta_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_native.h +22 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/bilinear_native.h +21 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_or_cuda_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv1d_ops.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/gather_backward_ops.h +28 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardswish_cpu_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/hspmm_ops.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/hypot_meta_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/inverse_ops.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf_cuda_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_factor_compositeimplicitautograd_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cuda_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_slogdet_compositeimplicitautograd_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_solve_triangular_cuda_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/lu_unpack.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/mean_compositeimplicitautograd_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/msort_ops.h +39 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_native.h +24 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/nanmedian_cpu_dispatch.h +25 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cuda_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/new_empty_strided_compositeexplicitautogradnonfunctional_dispatch.h +26 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot_compositeimplicitautograd_dispatch.h +23 -0
- .venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot_native.h +21 -0
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_adaptive_avg_pool2d_native.h
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#pragma once
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// @generated by torchgen/gen.py from NativeFunction.h
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#include <c10/core/Scalar.h>
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#include <c10/core/Storage.h>
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#include <c10/core/TensorOptions.h>
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#include <c10/util/Deprecated.h>
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#include <optional>
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#include <c10/core/QScheme.h>
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#include <ATen/core/Reduction.h>
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#include <ATen/core/Tensor.h>
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#include <tuple>
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#include <vector>
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namespace at {
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namespace native {
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TORCH_API at::Tensor & _adaptive_avg_pool2d_out_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out);
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TORCH_API at::Tensor adaptive_avg_pool2d_cpu(const at::Tensor & self, at::IntArrayRef output_size);
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TORCH_API at::Tensor adaptive_avg_pool2d_cuda(const at::Tensor & self, at::IntArrayRef output_size);
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TORCH_API at::Tensor adaptive_avg_pool2d_quantized_cpu(const at::Tensor & self, at::IntArrayRef output_size);
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TORCH_API at::Tensor adaptive_avg_pool2d_quantized_cuda(const at::Tensor & self, at::IntArrayRef output_size);
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} // namespace native
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} // namespace at
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.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_amp_update_scale_cpu_dispatch.h
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#pragma once
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// @generated by torchgen/gen.py from DispatchKeyFunction.h
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// NB: The implementing C++ file is RegisterDispatchKey.cpp
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// The only #includes we need are for custom classes that have defaults in the C++ API
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#include <c10/core/MemoryFormat.h>
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#include <c10/core/Scalar.h>
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#include <ATen/core/Reduction.h>
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// Forward declarations of any types needed in the operator signatures.
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// We can't directly include these classes because it will cause circular include dependencies.
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// This file is included by TensorBody.h, which defines the Tensor class.
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#include <ATen/core/ATen_fwd.h>
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namespace at {
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namespace cpu {
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TORCH_API at::Tensor & _amp_update_scale_(at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval);
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} // namespace cpu
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} // namespace at
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.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_batch_norm_with_update_ops.h
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#pragma once
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// @generated by torchgen/gen.py from Operator.h
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#include <tuple>
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#include <vector>
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// Forward declarations of any types needed in the operator signatures.
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// We can't directly include these classes because it will cause circular include dependencies.
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// This file is included by TensorBody.h, which defines the Tensor class.
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#include <ATen/core/ATen_fwd.h>
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namespace at {
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namespace _ops {
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struct TORCH_API _batch_norm_with_update {
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using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> (const at::Tensor &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, at::Tensor &, at::Tensor &, double, double);
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using ptr_schema = schema*;
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// See Note [static constexpr char* members for windows NVCC]
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_batch_norm_with_update")
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_batch_norm_with_update(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor)")
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static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> call(const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps);
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static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps);
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};
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struct TORCH_API _batch_norm_with_update_out {
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using schema = ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> (const at::Tensor &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, at::Tensor &, at::Tensor &, double, double, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &);
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using ptr_schema = schema*;
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// See Note [static constexpr char* members for windows NVCC]
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_batch_norm_with_update")
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_batch_norm_with_update.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd, Tensor(g!) reserve) -> (Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!))")
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static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> call(const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, at::Tensor & reserve);
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static ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, at::Tensor & reserve);
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};
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struct TORCH_API _batch_norm_with_update_functional {
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using schema = ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> (const at::Tensor &, const ::std::optional<at::Tensor> &, const ::std::optional<at::Tensor> &, const at::Tensor &, const at::Tensor &, double, double);
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| 41 |
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using ptr_schema = schema*;
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| 42 |
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// See Note [static constexpr char* members for windows NVCC]
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| 43 |
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_batch_norm_with_update_functional")
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| 44 |
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
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| 45 |
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STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_batch_norm_with_update_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out)")
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| 46 |
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static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> call(const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps);
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| 47 |
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static ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & bias, const at::Tensor & running_mean, const at::Tensor & running_var, double momentum, double eps);
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| 48 |
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};
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| 49 |
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| 50 |
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}} // namespace at::_ops
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.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_cast_Long.h
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#pragma once
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// @generated by torchgen/gen.py from Function.h
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#include <ATen/Context.h>
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#include <ATen/DeviceGuard.h>
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#include <ATen/TensorUtils.h>
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| 8 |
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#include <ATen/TracerMode.h>
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| 9 |
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#include <ATen/core/Generator.h>
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| 10 |
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#include <ATen/core/Reduction.h>
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| 11 |
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#include <ATen/core/Tensor.h>
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| 12 |
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#include <c10/core/Scalar.h>
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| 13 |
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#include <c10/core/Storage.h>
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| 14 |
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#include <c10/core/TensorOptions.h>
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| 15 |
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#include <c10/util/Deprecated.h>
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#include <optional>
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| 17 |
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#include <ATen/ops/_cast_Long_ops.h>
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namespace at {
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// aten::_cast_Long(Tensor self, bool non_blocking=False) -> Tensor
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inline at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false) {
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return at::_ops::_cast_Long::call(self, non_blocking);
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}
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| 29 |
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}
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.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_coalesced.h
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#pragma once
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// @generated by torchgen/gen.py from Function.h
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#include <ATen/Context.h>
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#include <ATen/DeviceGuard.h>
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#include <ATen/TensorUtils.h>
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| 8 |
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#include <ATen/TracerMode.h>
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#include <ATen/core/Generator.h>
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| 10 |
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#include <ATen/core/Reduction.h>
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| 11 |
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#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_coalesced_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!)
|
| 26 |
+
inline at::Tensor & _coalesced_out(at::Tensor & out, const at::Tensor & self, bool coalesced) {
|
| 27 |
+
return at::_ops::_coalesced_out::call(self, coalesced, out);
|
| 28 |
+
}
|
| 29 |
+
// aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!)
|
| 30 |
+
inline at::Tensor & _coalesced_outf(const at::Tensor & self, bool coalesced, at::Tensor & out) {
|
| 31 |
+
return at::_ops::_coalesced_out::call(self, coalesced, out);
|
| 32 |
+
}
|
| 33 |
+
|
| 34 |
+
// aten::_coalesced(Tensor self, bool coalesced) -> Tensor
|
| 35 |
+
inline at::Tensor _coalesced(const at::Tensor & self, bool coalesced) {
|
| 36 |
+
return at::_ops::_coalesced::call(self, coalesced);
|
| 37 |
+
}
|
| 38 |
+
|
| 39 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_convert_indices_from_coo_to_csr_meta.h
ADDED
|
@@ -0,0 +1,27 @@
|
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|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeMetaFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/TensorIterator.h>
|
| 13 |
+
#include <ATen/TensorMeta.h>
|
| 14 |
+
#include <tuple>
|
| 15 |
+
#include <vector>
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace meta {
|
| 19 |
+
|
| 20 |
+
struct TORCH_API structured__convert_indices_from_coo_to_csr : public at::impl::MetaBase {
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
void meta(const at::Tensor & self, int64_t size, bool out_int32);
|
| 24 |
+
};
|
| 25 |
+
|
| 26 |
+
} // namespace native
|
| 27 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_ctc_loss_backward_compositeexplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeexplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor & _ctc_loss_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false);
|
| 21 |
+
TORCH_API at::Tensor & _ctc_loss_backward_outf(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out);
|
| 22 |
+
|
| 23 |
+
} // namespace compositeexplicitautograd
|
| 24 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_dim_arange.h
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_dim_arange_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_dim_arange(Tensor like, int dim) -> Tensor
|
| 26 |
+
inline at::Tensor _dim_arange(const at::Tensor & like, int64_t dim) {
|
| 27 |
+
return at::_ops::_dim_arange::call(like, dim);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_efficientzerotensor.h
ADDED
|
@@ -0,0 +1,113 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_efficientzerotensor_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
| 26 |
+
inline at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}) {
|
| 27 |
+
return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
|
| 28 |
+
}
|
| 29 |
+
namespace symint {
|
| 30 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, int64_t>::value>>
|
| 31 |
+
at::Tensor _efficientzerotensor(at::IntArrayRef size, at::TensorOptions options={}) {
|
| 32 |
+
return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
|
| 33 |
+
}
|
| 34 |
+
}
|
| 35 |
+
|
| 36 |
+
// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
| 37 |
+
inline at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
|
| 38 |
+
return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory);
|
| 39 |
+
}
|
| 40 |
+
namespace symint {
|
| 41 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, int64_t>::value>>
|
| 42 |
+
at::Tensor _efficientzerotensor(at::IntArrayRef size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
|
| 43 |
+
return at::_ops::_efficientzerotensor::call(c10::fromIntArrayRefSlow(size), dtype, layout, device, pin_memory);
|
| 44 |
+
}
|
| 45 |
+
}
|
| 46 |
+
|
| 47 |
+
// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
| 48 |
+
inline at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, at::TensorOptions options={}) {
|
| 49 |
+
return at::_ops::_efficientzerotensor::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
|
| 50 |
+
}
|
| 51 |
+
namespace symint {
|
| 52 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, c10::SymInt>::value>>
|
| 53 |
+
at::Tensor _efficientzerotensor(c10::SymIntArrayRef size, at::TensorOptions options={}) {
|
| 54 |
+
return at::_ops::_efficientzerotensor::call(size, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
|
| 55 |
+
}
|
| 56 |
+
}
|
| 57 |
+
|
| 58 |
+
// aten::_efficientzerotensor(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
| 59 |
+
inline at::Tensor _efficientzerotensor_symint(c10::SymIntArrayRef size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
|
| 60 |
+
return at::_ops::_efficientzerotensor::call(size, dtype, layout, device, pin_memory);
|
| 61 |
+
}
|
| 62 |
+
namespace symint {
|
| 63 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, c10::SymInt>::value>>
|
| 64 |
+
at::Tensor _efficientzerotensor(c10::SymIntArrayRef size, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
|
| 65 |
+
return at::_ops::_efficientzerotensor::call(size, dtype, layout, device, pin_memory);
|
| 66 |
+
}
|
| 67 |
+
}
|
| 68 |
+
|
| 69 |
+
// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
|
| 70 |
+
inline at::Tensor & _efficientzerotensor_out(at::Tensor & out, at::IntArrayRef size) {
|
| 71 |
+
return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out);
|
| 72 |
+
}
|
| 73 |
+
namespace symint {
|
| 74 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, int64_t>::value>>
|
| 75 |
+
at::Tensor & _efficientzerotensor_out(at::Tensor & out, at::IntArrayRef size) {
|
| 76 |
+
return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out);
|
| 77 |
+
}
|
| 78 |
+
}
|
| 79 |
+
|
| 80 |
+
// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
|
| 81 |
+
inline at::Tensor & _efficientzerotensor_outf(at::IntArrayRef size, at::Tensor & out) {
|
| 82 |
+
return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out);
|
| 83 |
+
}
|
| 84 |
+
namespace symint {
|
| 85 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, int64_t>::value>>
|
| 86 |
+
at::Tensor & _efficientzerotensor_outf(at::IntArrayRef size, at::Tensor & out) {
|
| 87 |
+
return at::_ops::_efficientzerotensor_out::call(c10::fromIntArrayRefSlow(size), out);
|
| 88 |
+
}
|
| 89 |
+
}
|
| 90 |
+
|
| 91 |
+
// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
|
| 92 |
+
inline at::Tensor & _efficientzerotensor_symint_out(at::Tensor & out, c10::SymIntArrayRef size) {
|
| 93 |
+
return at::_ops::_efficientzerotensor_out::call(size, out);
|
| 94 |
+
}
|
| 95 |
+
namespace symint {
|
| 96 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, c10::SymInt>::value>>
|
| 97 |
+
at::Tensor & _efficientzerotensor_out(at::Tensor & out, c10::SymIntArrayRef size) {
|
| 98 |
+
return at::_ops::_efficientzerotensor_out::call(size, out);
|
| 99 |
+
}
|
| 100 |
+
}
|
| 101 |
+
|
| 102 |
+
// aten::_efficientzerotensor.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)
|
| 103 |
+
inline at::Tensor & _efficientzerotensor_symint_outf(c10::SymIntArrayRef size, at::Tensor & out) {
|
| 104 |
+
return at::_ops::_efficientzerotensor_out::call(size, out);
|
| 105 |
+
}
|
| 106 |
+
namespace symint {
|
| 107 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, c10::SymInt>::value>>
|
| 108 |
+
at::Tensor & _efficientzerotensor_outf(c10::SymIntArrayRef size, at::Tensor & out) {
|
| 109 |
+
return at::_ops::_efficientzerotensor_out::call(size, out);
|
| 110 |
+
}
|
| 111 |
+
}
|
| 112 |
+
|
| 113 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_embedding_bag_forward_only_compositeexplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeexplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _embedding_bag_forward_only_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, 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 ::std::optional<at::Tensor> & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
|
| 21 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _embedding_bag_forward_only_outf(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const ::std::optional<at::Tensor> & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3);
|
| 22 |
+
|
| 23 |
+
} // namespace compositeexplicitautograd
|
| 24 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_fake_quantize_learnable_per_channel_affine_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_fake_quantize_learnable_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor
|
| 26 |
+
inline at::Tensor _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0) {
|
| 27 |
+
return at::_ops::_fake_quantize_learnable_per_channel_affine::call(self, scale, zero_point, axis, quant_min, quant_max, grad_factor);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
// aten::_fake_quantize_learnable_per_channel_affine.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!)
|
| 31 |
+
inline at::Tensor & _fake_quantize_learnable_per_channel_affine_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0) {
|
| 32 |
+
return at::_ops::_fake_quantize_learnable_per_channel_affine_out::call(self, scale, zero_point, axis, quant_min, quant_max, grad_factor, out);
|
| 33 |
+
}
|
| 34 |
+
// aten::_fake_quantize_learnable_per_channel_affine.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!)
|
| 35 |
+
inline at::Tensor & _fake_quantize_learnable_per_channel_affine_outf(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor, at::Tensor & out) {
|
| 36 |
+
return at::_ops::_fake_quantize_learnable_per_channel_affine_out::call(self, scale, zero_point, axis, quant_min, quant_max, grad_factor, out);
|
| 37 |
+
}
|
| 38 |
+
|
| 39 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_fake_quantize_learnable_per_channel_affine_cpu_dispatch.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cpu {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0);
|
| 21 |
+
|
| 22 |
+
} // namespace cpu
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_foreach_tanh_compositeexplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeexplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::vector<at::Tensor> _foreach_tanh(at::TensorList self);
|
| 21 |
+
TORCH_API void _foreach_tanh_out(at::TensorList out, at::TensorList self);
|
| 22 |
+
TORCH_API void _foreach_tanh_outf(at::TensorList self, at::TensorList out);
|
| 23 |
+
TORCH_API void _foreach_tanh_(at::TensorList self);
|
| 24 |
+
|
| 25 |
+
} // namespace compositeexplicitautograd
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_compositeexplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeexplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor & _histogramdd_from_bin_tensors_out(at::Tensor & out, const at::Tensor & self, at::TensorList bins, const ::std::optional<at::Tensor> & weight={}, bool density=false);
|
| 21 |
+
TORCH_API at::Tensor & _histogramdd_from_bin_tensors_outf(const at::Tensor & self, at::TensorList bins, const ::std::optional<at::Tensor> & weight, bool density, at::Tensor & out);
|
| 22 |
+
|
| 23 |
+
} // namespace compositeexplicitautograd
|
| 24 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_linalg_svd_native.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/core/Tensor.h>
|
| 13 |
+
#include <tuple>
|
| 14 |
+
#include <vector>
|
| 15 |
+
#include <ATen/ops/_linalg_svd_meta.h>
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace native {
|
| 19 |
+
struct TORCH_API structured__linalg_svd_out : public at::meta::structured__linalg_svd {
|
| 20 |
+
void impl(const at::Tensor & A, bool full_matrices, bool compute_uv, ::std::optional<c10::string_view> driver, const at::Tensor & U, const at::Tensor & S, const at::Tensor & Vh);
|
| 21 |
+
};
|
| 22 |
+
} // namespace native
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_local_scalar_dense.h
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_local_scalar_dense_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_local_scalar_dense(Tensor self) -> Scalar
|
| 26 |
+
inline at::Scalar _local_scalar_dense(const at::Tensor & self) {
|
| 27 |
+
return at::_ops::_local_scalar_dense::call(self);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_mixed_dtypes_linear_ops.h
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API _mixed_dtypes_linear {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const ::std::optional<at::Tensor> &, ::std::optional<c10::string_view>);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_mixed_dtypes_linear")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_mixed_dtypes_linear(Tensor input, Tensor weight, Tensor scale, *, Tensor? bias=None, str? activation=None) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & scale, const ::std::optional<at::Tensor> & bias, ::std::optional<c10::string_view> activation);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & scale, const ::std::optional<at::Tensor> & bias, ::std::optional<c10::string_view> activation);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_scaled_dot_product_flash_attention_backward.h
ADDED
|
@@ -0,0 +1,47 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_scaled_dot_product_flash_attention_backward_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor philox_seed, Tensor philox_offset, *, float? scale=None) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value)
|
| 26 |
+
inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional<double> scale=::std::nullopt) {
|
| 27 |
+
return at::_ops::_scaled_dot_product_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale);
|
| 28 |
+
}
|
| 29 |
+
namespace symint {
|
| 30 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, int64_t>::value>>
|
| 31 |
+
::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional<double> scale=::std::nullopt) {
|
| 32 |
+
return at::_ops::_scaled_dot_product_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale);
|
| 33 |
+
}
|
| 34 |
+
}
|
| 35 |
+
|
| 36 |
+
// aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max_k, float dropout_p, bool is_causal, Tensor philox_seed, Tensor philox_offset, *, float? scale=None) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value)
|
| 37 |
+
inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward_symint(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional<double> scale=::std::nullopt) {
|
| 38 |
+
return at::_ops::_scaled_dot_product_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale);
|
| 39 |
+
}
|
| 40 |
+
namespace symint {
|
| 41 |
+
template <typename T, typename = std::enable_if_t<std::is_same<T, c10::SymInt>::value>>
|
| 42 |
+
::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, c10::SymInt max_q, c10::SymInt max_k, double dropout_p, bool is_causal, const at::Tensor & philox_seed, const at::Tensor & philox_offset, ::std::optional<double> scale=::std::nullopt) {
|
| 43 |
+
return at::_ops::_scaled_dot_product_flash_attention_backward::call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset, scale);
|
| 44 |
+
}
|
| 45 |
+
}
|
| 46 |
+
|
| 47 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sobol_engine_initialize_state_ops.h
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API _sobol_engine_initialize_state_ {
|
| 18 |
+
using schema = at::Tensor & (at::Tensor &, int64_t);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sobol_engine_initialize_state_")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!)")
|
| 24 |
+
static at::Tensor & call(at::Tensor & self, int64_t dimension);
|
| 25 |
+
static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dimension);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_log_softmax_ops.h
ADDED
|
@@ -0,0 +1,61 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API _sparse_log_softmax_int {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &, int64_t, ::std::optional<at::ScalarType>);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_log_softmax")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "int")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & self, int64_t dim, ::std::optional<at::ScalarType> dtype);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, ::std::optional<at::ScalarType> dtype);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
struct TORCH_API _sparse_log_softmax_Dimname {
|
| 29 |
+
using schema = at::Tensor (const at::Tensor &, at::Dimname, ::std::optional<at::ScalarType>);
|
| 30 |
+
using ptr_schema = schema*;
|
| 31 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 32 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_log_softmax")
|
| 33 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Dimname")
|
| 34 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor")
|
| 35 |
+
static at::Tensor call(const at::Tensor & self, at::Dimname dim, ::std::optional<at::ScalarType> dtype);
|
| 36 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, ::std::optional<at::ScalarType> dtype);
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
struct TORCH_API _sparse_log_softmax {
|
| 40 |
+
using schema = at::Tensor (const at::Tensor &, int64_t, bool);
|
| 41 |
+
using ptr_schema = schema*;
|
| 42 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 43 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_log_softmax")
|
| 44 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 45 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor")
|
| 46 |
+
static at::Tensor call(const at::Tensor & self, int64_t dim, bool half_to_float);
|
| 47 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float);
|
| 48 |
+
};
|
| 49 |
+
|
| 50 |
+
struct TORCH_API _sparse_log_softmax_out {
|
| 51 |
+
using schema = at::Tensor & (const at::Tensor &, int64_t, bool, at::Tensor &);
|
| 52 |
+
using ptr_schema = schema*;
|
| 53 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 54 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_sparse_log_softmax")
|
| 55 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
|
| 56 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_sparse_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)")
|
| 57 |
+
static at::Tensor & call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out);
|
| 58 |
+
static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out);
|
| 59 |
+
};
|
| 60 |
+
|
| 61 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_sparse_softmax.h
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/_sparse_softmax_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor
|
| 26 |
+
inline at::Tensor _sparse_softmax(const at::Tensor & self, int64_t dim, ::std::optional<at::ScalarType> dtype=::std::nullopt) {
|
| 27 |
+
return at::_ops::_sparse_softmax_int::call(self, dim, dtype);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
// aten::_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor
|
| 31 |
+
inline at::Tensor _sparse_softmax(const at::Tensor & self, at::Dimname dim, ::std::optional<at::ScalarType> dtype=::std::nullopt) {
|
| 32 |
+
return at::_ops::_sparse_softmax_Dimname::call(self, dim, dtype);
|
| 33 |
+
}
|
| 34 |
+
|
| 35 |
+
// aten::_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor
|
| 36 |
+
inline at::Tensor _sparse_softmax(const at::Tensor & self, int64_t dim, bool half_to_float) {
|
| 37 |
+
return at::_ops::_sparse_softmax::call(self, dim, half_to_float);
|
| 38 |
+
}
|
| 39 |
+
|
| 40 |
+
// aten::_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)
|
| 41 |
+
inline at::Tensor & _sparse_softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float) {
|
| 42 |
+
return at::_ops::_sparse_softmax_out::call(self, dim, half_to_float, out);
|
| 43 |
+
}
|
| 44 |
+
// aten::_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)
|
| 45 |
+
inline at::Tensor & _sparse_softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out) {
|
| 46 |
+
return at::_ops::_sparse_softmax_out::call(self, dim, half_to_float, out);
|
| 47 |
+
}
|
| 48 |
+
|
| 49 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_unpack_dual_ops.h
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API _unpack_dual {
|
| 18 |
+
using schema = ::std::tuple<at::Tensor,at::Tensor> (const at::Tensor &, int64_t);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_unpack_dual")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent)")
|
| 24 |
+
static ::std::tuple<at::Tensor,at::Tensor> call(const at::Tensor & dual, int64_t level);
|
| 25 |
+
static ::std::tuple<at::Tensor,at::Tensor> redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dual, int64_t level);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/_weight_int4pack_mm_ops.h
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API _weight_int4pack_mm {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_weight_int4pack_mm")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_weight_int4pack_mm(Tensor self, Tensor mat2, int qGroupSize, Tensor qScaleAndZeros) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2, int64_t qGroupSize, const at::Tensor & qScaleAndZeros);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/abs.h
ADDED
|
@@ -0,0 +1,44 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/abs_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::abs(Tensor self) -> Tensor
|
| 26 |
+
inline at::Tensor abs(const at::Tensor & self) {
|
| 27 |
+
return at::_ops::abs::call(self);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
// aten::abs_(Tensor(a!) self) -> Tensor(a!)
|
| 31 |
+
inline at::Tensor & abs_(at::Tensor & self) {
|
| 32 |
+
return at::_ops::abs_::call(self);
|
| 33 |
+
}
|
| 34 |
+
|
| 35 |
+
// aten::abs.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
|
| 36 |
+
inline at::Tensor & abs_out(at::Tensor & out, const at::Tensor & self) {
|
| 37 |
+
return at::_ops::abs_out::call(self, out);
|
| 38 |
+
}
|
| 39 |
+
// aten::abs.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)
|
| 40 |
+
inline at::Tensor & abs_outf(const at::Tensor & self, at::Tensor & out) {
|
| 41 |
+
return at::_ops::abs_out::call(self, out);
|
| 42 |
+
}
|
| 43 |
+
|
| 44 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool1d_compositeimplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeimplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor,at::Tensor> adaptive_max_pool1d(const at::Tensor & self, at::IntArrayRef output_size);
|
| 21 |
+
|
| 22 |
+
} // namespace compositeimplicitautograd
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/adaptive_max_pool2d_backward.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/adaptive_max_pool2d_backward_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::adaptive_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
|
| 26 |
+
inline at::Tensor & adaptive_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices) {
|
| 27 |
+
return at::_ops::adaptive_max_pool2d_backward_grad_input::call(grad_output, self, indices, grad_input);
|
| 28 |
+
}
|
| 29 |
+
// aten::adaptive_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)
|
| 30 |
+
inline at::Tensor & adaptive_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input) {
|
| 31 |
+
return at::_ops::adaptive_max_pool2d_backward_grad_input::call(grad_output, self, indices, grad_input);
|
| 32 |
+
}
|
| 33 |
+
|
| 34 |
+
// aten::adaptive_max_pool2d_backward(Tensor grad_output, Tensor self, Tensor indices) -> Tensor
|
| 35 |
+
inline at::Tensor adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices) {
|
| 36 |
+
return at::_ops::adaptive_max_pool2d_backward::call(grad_output, self, indices);
|
| 37 |
+
}
|
| 38 |
+
|
| 39 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/addcdiv_meta_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace meta {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1);
|
| 21 |
+
TORCH_API at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1);
|
| 22 |
+
TORCH_API at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out);
|
| 23 |
+
TORCH_API at::Tensor & addcdiv_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1);
|
| 24 |
+
|
| 25 |
+
} // namespace meta
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/batch_norm_gather_stats_native.h
ADDED
|
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/core/Tensor.h>
|
| 13 |
+
#include <tuple>
|
| 14 |
+
#include <vector>
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace native {
|
| 19 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> batch_norm_gather_stats_out(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional<at::Tensor> & running_mean, const ::std::optional<at::Tensor> & running_var, double momentum, double eps, int64_t count, at::Tensor & out0, at::Tensor & out1);
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor,at::Tensor> batch_norm_gather_stats_cuda(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const ::std::optional<at::Tensor> & running_mean, const ::std::optional<at::Tensor> & running_var, double momentum, double eps, int64_t count);
|
| 21 |
+
} // namespace native
|
| 22 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bilinear_native.h
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/core/Tensor.h>
|
| 13 |
+
#include <tuple>
|
| 14 |
+
#include <vector>
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace native {
|
| 19 |
+
TORCH_API at::Tensor bilinear(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const ::std::optional<at::Tensor> & bias={});
|
| 20 |
+
} // namespace native
|
| 21 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/bitwise_or_cuda_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cuda {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Tensor & other);
|
| 21 |
+
TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
|
| 22 |
+
TORCH_API at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
|
| 23 |
+
TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Tensor & other);
|
| 24 |
+
|
| 25 |
+
} // namespace cuda
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/conv1d_ops.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API conv1d {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional<at::Tensor> &, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymIntArrayRef, c10::SymInt);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::conv1d")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "conv1d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, SymInt[1] padding=0, SymInt[1] dilation=1, SymInt groups=1) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional<at::Tensor> & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional<at::Tensor> & bias, c10::SymIntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef dilation, c10::SymInt groups);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
struct TORCH_API conv1d_padding {
|
| 29 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const ::std::optional<at::Tensor> &, c10::SymIntArrayRef, c10::string_view, c10::SymIntArrayRef, c10::SymInt);
|
| 30 |
+
using ptr_schema = schema*;
|
| 31 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 32 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::conv1d")
|
| 33 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "padding")
|
| 34 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "conv1d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[1] stride=1, str padding=\"valid\", SymInt[1] dilation=1, SymInt groups=1) -> Tensor")
|
| 35 |
+
static at::Tensor call(const at::Tensor & input, const at::Tensor & weight, const ::std::optional<at::Tensor> & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups);
|
| 36 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const ::std::optional<at::Tensor> & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation, c10::SymInt groups);
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/gather_backward_ops.h
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API gather_backward {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &, int64_t, const at::Tensor &, bool);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::gather_backward")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "gather_backward(Tensor grad, Tensor self, int dim, Tensor index, bool sparse_grad) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hardswish_cpu_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cpu {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor hardswish(const at::Tensor & self);
|
| 21 |
+
TORCH_API at::Tensor & hardswish_out(at::Tensor & out, const at::Tensor & self);
|
| 22 |
+
TORCH_API at::Tensor & hardswish_outf(const at::Tensor & self, at::Tensor & out);
|
| 23 |
+
TORCH_API at::Tensor & hardswish_(at::Tensor & self);
|
| 24 |
+
|
| 25 |
+
} // namespace cpu
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hspmm_ops.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API hspmm_out {
|
| 18 |
+
using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::hspmm")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)")
|
| 24 |
+
static at::Tensor & call(const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out);
|
| 25 |
+
static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
struct TORCH_API hspmm {
|
| 29 |
+
using schema = at::Tensor (const at::Tensor &, const at::Tensor &);
|
| 30 |
+
using ptr_schema = schema*;
|
| 31 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 32 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::hspmm")
|
| 33 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 34 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "hspmm(Tensor mat1, Tensor mat2) -> Tensor")
|
| 35 |
+
static at::Tensor call(const at::Tensor & mat1, const at::Tensor & mat2);
|
| 36 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2);
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/hypot_meta_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace meta {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor hypot(const at::Tensor & self, const at::Tensor & other);
|
| 21 |
+
TORCH_API at::Tensor & hypot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
|
| 22 |
+
TORCH_API at::Tensor & hypot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
|
| 23 |
+
TORCH_API at::Tensor & hypot_(at::Tensor & self, const at::Tensor & other);
|
| 24 |
+
|
| 25 |
+
} // namespace meta
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/inverse_ops.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API inverse {
|
| 18 |
+
using schema = at::Tensor (const at::Tensor &);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::inverse")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "inverse(Tensor self) -> Tensor")
|
| 24 |
+
static at::Tensor call(const at::Tensor & self);
|
| 25 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
struct TORCH_API inverse_out {
|
| 29 |
+
using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
|
| 30 |
+
using ptr_schema = schema*;
|
| 31 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 32 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::inverse")
|
| 33 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
|
| 34 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "inverse.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)")
|
| 35 |
+
static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
|
| 36 |
+
static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/isneginf_cuda_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cuda {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor isneginf(const at::Tensor & self);
|
| 21 |
+
TORCH_API at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self);
|
| 22 |
+
TORCH_API at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out);
|
| 23 |
+
|
| 24 |
+
} // namespace cuda
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_lu_factor_compositeimplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeimplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor,at::Tensor> linalg_lu_factor(const at::Tensor & A, bool pivot=true);
|
| 21 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> linalg_lu_factor_out(at::Tensor & LU, at::Tensor & pivots, const at::Tensor & A, bool pivot=true);
|
| 22 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> linalg_lu_factor_outf(const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots);
|
| 23 |
+
|
| 24 |
+
} // namespace compositeimplicitautograd
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_matrix_exp_cuda_dispatch.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cuda {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor linalg_matrix_exp(const at::Tensor & self);
|
| 21 |
+
|
| 22 |
+
} // namespace cuda
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_slogdet_compositeimplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeimplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor,at::Tensor> linalg_slogdet(const at::Tensor & A);
|
| 21 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & A);
|
| 22 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> linalg_slogdet_outf(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet);
|
| 23 |
+
|
| 24 |
+
} // namespace compositeimplicitautograd
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/linalg_solve_triangular_cuda_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cuda {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor linalg_solve_triangular(const at::Tensor & self, const at::Tensor & B, bool upper, bool left=true, bool unitriangular=false);
|
| 21 |
+
TORCH_API at::Tensor & linalg_solve_triangular_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & B, bool upper, bool left=true, bool unitriangular=false);
|
| 22 |
+
TORCH_API at::Tensor & linalg_solve_triangular_outf(const at::Tensor & self, const at::Tensor & B, bool upper, bool left, bool unitriangular, at::Tensor & out);
|
| 23 |
+
|
| 24 |
+
} // namespace cuda
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/lu_unpack.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Function.h
|
| 4 |
+
|
| 5 |
+
#include <ATen/Context.h>
|
| 6 |
+
#include <ATen/DeviceGuard.h>
|
| 7 |
+
#include <ATen/TensorUtils.h>
|
| 8 |
+
#include <ATen/TracerMode.h>
|
| 9 |
+
#include <ATen/core/Generator.h>
|
| 10 |
+
#include <ATen/core/Reduction.h>
|
| 11 |
+
#include <ATen/core/Tensor.h>
|
| 12 |
+
#include <c10/core/Scalar.h>
|
| 13 |
+
#include <c10/core/Storage.h>
|
| 14 |
+
#include <c10/core/TensorOptions.h>
|
| 15 |
+
#include <c10/util/Deprecated.h>
|
| 16 |
+
#include <optional>
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
#include <ATen/ops/lu_unpack_ops.h>
|
| 21 |
+
|
| 22 |
+
namespace at {
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
// aten::lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U)
|
| 26 |
+
inline ::std::tuple<at::Tensor,at::Tensor,at::Tensor> lu_unpack(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true) {
|
| 27 |
+
return at::_ops::lu_unpack::call(LU_data, LU_pivots, unpack_data, unpack_pivots);
|
| 28 |
+
}
|
| 29 |
+
|
| 30 |
+
// aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)
|
| 31 |
+
inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> lu_unpack_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true) {
|
| 32 |
+
return at::_ops::lu_unpack_out::call(LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U);
|
| 33 |
+
}
|
| 34 |
+
// aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)
|
| 35 |
+
inline ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> lu_unpack_outf(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U) {
|
| 36 |
+
return at::_ops::lu_unpack_out::call(LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U);
|
| 37 |
+
}
|
| 38 |
+
|
| 39 |
+
}
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/mean_compositeimplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeimplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor mean(const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional<at::ScalarType> dtype=::std::nullopt);
|
| 21 |
+
TORCH_API at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool keepdim=false, ::std::optional<at::ScalarType> dtype=::std::nullopt);
|
| 22 |
+
TORCH_API at::Tensor & mean_outf(const at::Tensor & self, at::DimnameList dim, bool keepdim, ::std::optional<at::ScalarType> dtype, at::Tensor & out);
|
| 23 |
+
|
| 24 |
+
} // namespace compositeimplicitautograd
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/msort_ops.h
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from Operator.h
|
| 4 |
+
|
| 5 |
+
#include <tuple>
|
| 6 |
+
#include <vector>
|
| 7 |
+
|
| 8 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 9 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 10 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 11 |
+
#include <ATen/core/ATen_fwd.h>
|
| 12 |
+
|
| 13 |
+
namespace at {
|
| 14 |
+
namespace _ops {
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
struct TORCH_API msort_out {
|
| 18 |
+
using schema = at::Tensor & (const at::Tensor &, at::Tensor &);
|
| 19 |
+
using ptr_schema = schema*;
|
| 20 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 21 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::msort")
|
| 22 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out")
|
| 23 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "msort.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)")
|
| 24 |
+
static at::Tensor & call(const at::Tensor & self, at::Tensor & out);
|
| 25 |
+
static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out);
|
| 26 |
+
};
|
| 27 |
+
|
| 28 |
+
struct TORCH_API msort {
|
| 29 |
+
using schema = at::Tensor (const at::Tensor &);
|
| 30 |
+
using ptr_schema = schema*;
|
| 31 |
+
// See Note [static constexpr char* members for windows NVCC]
|
| 32 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::msort")
|
| 33 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "")
|
| 34 |
+
STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "msort(Tensor self) -> Tensor")
|
| 35 |
+
static at::Tensor call(const at::Tensor & self);
|
| 36 |
+
static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self);
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
}} // namespace at::_ops
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/multi_margin_loss_native.h
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/core/Tensor.h>
|
| 13 |
+
#include <tuple>
|
| 14 |
+
#include <vector>
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace native {
|
| 19 |
+
TORCH_API at::Tensor multi_margin_loss_cpu(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
|
| 20 |
+
TORCH_API at::Tensor & multi_margin_loss_cpu_out(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & out);
|
| 21 |
+
TORCH_API at::Tensor multi_margin_loss_cuda(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const ::std::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
|
| 22 |
+
TORCH_API at::Tensor & multi_margin_loss_cuda_out(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const ::std::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & out);
|
| 23 |
+
} // namespace native
|
| 24 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/nanmedian_cpu_dispatch.h
ADDED
|
@@ -0,0 +1,25 @@
|
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|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cpu {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor nanmedian(const at::Tensor & self);
|
| 21 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false);
|
| 22 |
+
TORCH_API ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
|
| 23 |
+
|
| 24 |
+
} // namespace cpu
|
| 25 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/native_batch_norm_backward_cuda_dispatch.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace cuda {
|
| 19 |
+
|
| 20 |
+
TORCH_API ::std::tuple<at::Tensor,at::Tensor,at::Tensor> native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const ::std::optional<at::Tensor> & weight, const ::std::optional<at::Tensor> & running_mean, const ::std::optional<at::Tensor> & running_var, const ::std::optional<at::Tensor> & save_mean, const ::std::optional<at::Tensor> & save_invstd, bool train, double eps, ::std::array<bool,3> output_mask);
|
| 21 |
+
|
| 22 |
+
} // namespace cuda
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/new_empty_strided_compositeexplicitautogradnonfunctional_dispatch.h
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeexplicitautogradnonfunctional {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor new_empty_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={});
|
| 21 |
+
TORCH_API at::Tensor new_empty_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
|
| 22 |
+
TORCH_API at::Tensor new_empty_strided_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::TensorOptions options={});
|
| 23 |
+
TORCH_API at::Tensor new_empty_strided_symint(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory);
|
| 24 |
+
|
| 25 |
+
} // namespace compositeexplicitautogradnonfunctional
|
| 26 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot_compositeimplicitautograd_dispatch.h
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
// @generated by torchgen/gen.py from DispatchKeyFunction.h
|
| 3 |
+
|
| 4 |
+
// NB: The implementing C++ file is RegisterDispatchKey.cpp
|
| 5 |
+
|
| 6 |
+
// The only #includes we need are for custom classes that have defaults in the C++ API
|
| 7 |
+
#include <c10/core/MemoryFormat.h>
|
| 8 |
+
#include <c10/core/Scalar.h>
|
| 9 |
+
#include <ATen/core/Reduction.h>
|
| 10 |
+
|
| 11 |
+
// Forward declarations of any types needed in the operator signatures.
|
| 12 |
+
// We can't directly include these classes because it will cause circular include dependencies.
|
| 13 |
+
// This file is included by TensorBody.h, which defines the Tensor class.
|
| 14 |
+
#include <ATen/core/ATen_fwd.h>
|
| 15 |
+
|
| 16 |
+
namespace at {
|
| 17 |
+
|
| 18 |
+
namespace compositeimplicitautograd {
|
| 19 |
+
|
| 20 |
+
TORCH_API at::Tensor one_hot(const at::Tensor & self, int64_t num_classes=-1);
|
| 21 |
+
|
| 22 |
+
} // namespace compositeimplicitautograd
|
| 23 |
+
} // namespace at
|
.venv/lib/python3.11/site-packages/torch/include/ATen/ops/one_hot_native.h
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#pragma once
|
| 2 |
+
|
| 3 |
+
// @generated by torchgen/gen.py from NativeFunction.h
|
| 4 |
+
|
| 5 |
+
#include <c10/core/Scalar.h>
|
| 6 |
+
#include <c10/core/Storage.h>
|
| 7 |
+
#include <c10/core/TensorOptions.h>
|
| 8 |
+
#include <c10/util/Deprecated.h>
|
| 9 |
+
#include <optional>
|
| 10 |
+
#include <c10/core/QScheme.h>
|
| 11 |
+
#include <ATen/core/Reduction.h>
|
| 12 |
+
#include <ATen/core/Tensor.h>
|
| 13 |
+
#include <tuple>
|
| 14 |
+
#include <vector>
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
namespace at {
|
| 18 |
+
namespace native {
|
| 19 |
+
TORCH_API at::Tensor one_hot(const at::Tensor & self, int64_t num_classes=-1);
|
| 20 |
+
} // namespace native
|
| 21 |
+
} // namespace at
|