1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
|
#include <torch/csrc/utils/nested.h>
#include <torch/csrc/utils/pycfunction_helpers.h>
#include <torch/csrc/utils/python_arg_parser.h>
#include <torch/torch.h>
namespace torch::autograd {
static PyObject* THPVariable_nested_tensor(
PyObject* /*self*/,
PyObject* args,
PyObject* kwargs) {
HANDLE_TH_ERRORS
static PythonArgParser parser({
"nested_tensor(PyObject* data, *, ScalarType dtype=None, Device? device=None, bool pin_memory=False, bool requires_grad=False)",
});
constexpr int ctor_num_args = 5;
ParsedArgs<ctor_num_args> parsed_args;
auto r = parser.parse(args, kwargs, parsed_args);
jit::tracer::warn(
"torch.nested.nested_tensor", jit::tracer::WARN_CONSTRUCTOR);
return THPVariable_Wrap(torch::utils::nested_tensor_ctor(
torch::tensors::get_default_dispatch_key(),
torch::tensors::get_default_scalar_type(),
r));
END_HANDLE_TH_ERRORS
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
static PyMethodDef nested_functions_manual[] = {
{"nested_tensor",
castPyCFunctionWithKeywords(THPVariable_nested_tensor),
METH_VARARGS | METH_KEYWORDS,
nullptr},
};
PyMethodDef* get_nested_functions_manual() {
return nested_functions_manual;
}
} // namespace torch::autograd
|