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https://github.com/zebrajr/pytorch.git
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ba0fc71a3a
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68693 Generation of python bindings for native functions is split over 8 different files. One for each namespace, with the torch namespace split into 3 shards, and methods in their own file as well. This change ensures that editing any single (non-method) operator only causes one of these files to be rebuilt. Test Plan: Imported from OSS Reviewed By: jbschlosser Differential Revision: D32596270 Pulled By: albanD fbshipit-source-id: 0570ec69e7476b8f1bc21138ba18fe8f95ebbe3f
82 lines
1.9 KiB
C++
82 lines
1.9 KiB
C++
#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
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// ${generated_comment}
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#include "torch/csrc/Device.h"
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#include "torch/csrc/DynamicTypes.h"
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#include "torch/csrc/Exceptions.h"
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#include "torch/csrc/autograd/python_fft_functions.h"
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#include "torch/csrc/autograd/python_return_types.h"
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#include "torch/csrc/autograd/python_variable.h"
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#include "torch/csrc/autograd/utils/wrap_outputs.h"
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#include "torch/csrc/autograd/utils/python_arg_parsing.h"
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#include "torch/csrc/autograd/generated/variable_factories.h"
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#include "torch/csrc/utils/out_types.h"
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#include "torch/csrc/utils/pycfunction_helpers.h"
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#include "torch/csrc/utils/python_arg_parser.h"
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#include "torch/csrc/utils/structseq.h"
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#include "torch/csrc/utils/cuda_lazy_init.h"
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#include <ATen/core/Tensor.h>
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#ifndef AT_PER_OPERATOR_HEADERS
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#include <ATen/Functions.h>
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#else
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$ops_headers
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#endif
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using at::Tensor;
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using at::Device;
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using at::Layout;
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using at::Scalar;
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using at::ScalarType;
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using at::Backend;
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using at::OptionalDeviceGuard;
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using at::DeviceGuard;
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using at::TensorOptions;
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using at::IntArrayRef;
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using at::Generator;
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using at::TensorList;
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using at::Dimname;
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using at::DimnameList;
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using torch::utils::check_out_type_matches;
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using namespace torch::autograd::utils;
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namespace torch { namespace autograd {
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// generated forward declarations start here
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${py_forwards}
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static PyMethodDef fft_functions[] = {
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${py_method_defs}
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{NULL}
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};
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static PyObject* THPFFTVariableFunctionsModule = NULL;
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void initFFTFunctions(PyObject* module) {
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static struct PyModuleDef def = {
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PyModuleDef_HEAD_INIT,
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"torch._C._fft",
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NULL,
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-1,
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fft_functions
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};
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PyObject* fft = PyModule_Create(&def);
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THPFFTVariableFunctionsModule = fft;
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if (!fft) {
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throw python_error();
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}
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// steals a reference to fft
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if (PyModule_AddObject(module, "_fft", fft) != 0) {
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throw python_error();
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}
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}
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// generated methods start here
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${py_methods}
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}} // namespace torch::autograd
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