mirror of
https://github.com/zebrajr/pytorch.git
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c0a419e6ba
* Add non_blocking to Tensor/Module.to * flake8 * Add argparse tests * cpp parse * Use C++ parser * use a commong parse function with Tensor.to * fix test_jit * use THPObjectPtr * increase refcount for None, True, and False * address comments * address comments
79 lines
2.1 KiB
C++
79 lines
2.1 KiB
C++
#include "python_nn_functions.h"
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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_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/utils/python_arg_parser.h"
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#include "python_nn_functions_dispatch.h"
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using at::Tensor;
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using at::Scalar;
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using namespace torch::autograd::utils;
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namespace torch { namespace autograd {
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static PyObject * THPVariable__parse_to(PyObject* module, PyObject* args, PyObject* kwargs)
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{
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HANDLE_TH_ERRORS
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auto parsed = parse_to_conversion(args, kwargs);
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auto& device = std::get<0>(parsed);
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auto& scalarType = std::get<1>(parsed);
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auto non_blocking = std::get<2>(parsed);
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auto tuple = THPObjectPtr{PyTuple_New(3)};
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if (!tuple) throw python_error();
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if (device) {
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PyTuple_SET_ITEM(tuple.get(), 0, THPDevice_New(*device));
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} else {
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Py_INCREF(Py_None);
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PyTuple_SET_ITEM(tuple.get(), 0, Py_None);
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}
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if (scalarType) {
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PyTuple_SET_ITEM(tuple.get(), 1, torch::autograd::utils::wrap(torch::getDtype(*scalarType)));
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} else {
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Py_INCREF(Py_None);
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PyTuple_SET_ITEM(tuple.get(), 1, Py_None);
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}
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PyTuple_SET_ITEM(tuple.get(), 2, torch::autograd::utils::wrap(non_blocking));
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return tuple.release();
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END_HANDLE_TH_ERRORS
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}
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${py_methods}
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static PyMethodDef nn_functions[] = {
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{"_parse_to", (PyCFunction)THPVariable__parse_to, METH_VARARGS | METH_KEYWORDS, nullptr},
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${py_method_defs}
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{NULL}
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};
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void initNNFunctions(PyObject* module) {
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#if PY_MAJOR_VERSION == 2
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PyObject* nn = Py_InitModule("torch._C._nn", nn_functions);
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Py_XINCREF(nn); // Py_InitModule returns "borrowed" reference
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#else
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static struct PyModuleDef def = {
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PyModuleDef_HEAD_INIT,
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"torch._C._nn",
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NULL,
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-1,
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nn_functions
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};
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PyObject* nn = PyModule_Create(&def);
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#endif
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if (!nn) {
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throw python_error();
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}
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// steals a reference to nn
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if (PyModule_AddObject(module, "_nn", nn) != 0) {
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throw python_error();
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}
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}
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}} // namespace torch::autograd
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