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#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
// ${generated_comment}
// Python bindings for torch.* functions implemented through ATen.
//
// The functions are bound as static methods on a class
// torch._C._VariableFunctions which is also aliased as Variable._torch
// and also copied into 'torch' module.
#include <Python.h>
// Undefine the copysign macro so that at::copysign works as intended with MSVC
// https://github.com/python/cpython/blob/c60394c7fc9cc09b16e9675a3eeb5844b6d8523f/PC/pyconfig.h#L196
#ifdef _MSC_VER
#undef copysign
#endif // _MSC_VER
#include "torch/csrc/autograd/python_torch_functions.h"
#include "torch/csrc/autograd/python_variable.h"
#include "torch/csrc/autograd/utils/wrap_outputs.h"
#include "torch/csrc/Dtype.h"
#include "torch/csrc/DynamicTypes.h"
#include "torch/csrc/Exceptions.h"
#include "torch/csrc/utils/out_types.h"
#include "torch/csrc/utils/pybind.h"
#include "torch/csrc/utils/pycfunction_helpers.h"
#include "torch/csrc/utils/python_arg_parser.h"
#include "torch/csrc/utils/tensor_layouts.h"
#include "torch/csrc/utils/tensor_new.h"
#include "torch/csrc/utils/tensor_numpy.h"
#include "torch/csrc/jit/frontend/tracer.h"
#include "torch/csrc/autograd/generated/variable_factories.h"
#include "torch/csrc/utils/structseq.h"
#include "torch/csrc/utils/cuda_lazy_init.h"
#include "torch/csrc/autograd/python_return_types.h"
#include <ATen/core/Tensor.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Functions.h>
#else
$ops_headers
#endif
#include <functional>
#include <initializer_list>
#include <stdexcept>
#include <utility>
using at::Tensor;
using at::Device;
using at::Layout;
using at::Scalar;
using at::ScalarType;
using at::Backend;
using at::OptionalDeviceGuard;
using at::DeviceGuard;
using at::TensorOptions;
using at::IntArrayRef;
using at::Generator;
using at::TensorList;
using at::Dimname;
using at::DimnameList;
using at::ArrayRef;
using torch::utils::check_out_type_matches;
using namespace torch::autograd::utils;
// NOTE: See [Sharded File] comment in VariableType
namespace torch { namespace autograd {
// generated forward declarations start here
${py_forwards}
static PyMethodDef torch_functions_shard[] = {
${py_method_defs}
};
void gatherTorchFunctions${shard_id}(std::vector<PyMethodDef> &torch_functions) {
constexpr size_t num_functions = sizeof(torch_functions_shard) / sizeof(torch_functions_shard[0]);
torch_functions.insert(
torch_functions.end(),
torch_functions_shard,
torch_functions_shard + num_functions);
}
// generated methods start here
${py_methods}
}} // namespace torch::autograd
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