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#pragma once
#include <ATen/core/Tensor.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/python_arg_parser.h>
namespace torch::autograd::utils {
// The parameter allow_copy is to accept copy for Tensor.to (and by proxy
// PackedSequences.to) but not nn.Module.to.
inline std::tuple<
std::optional<at::Device>,
std::optional<at::ScalarType>,
bool,
bool,
std::optional<at::MemoryFormat>>
parse_to_conversion(PythonArgs& r, bool allow_copy) {
if (r.idx == 0) {
if (!allow_copy && !r.isNone(3))
throw std::runtime_error(".to() does not accept copy argument");
return std::make_tuple(
r.deviceOptional(0),
r.scalartypeOptional(1),
r.toBool(2),
r.toBool(3),
r.memoryformatOptional(4));
} else if (r.idx == 1) {
if (!allow_copy && !r.isNone(2))
throw std::runtime_error(".to() does not accept copy argument");
return std::make_tuple(
std::nullopt,
r.scalartype(0),
r.toBool(1),
r.toBool(2),
r.memoryformatOptional(3));
} else {
auto tensor = r.tensor(0);
if (!allow_copy && !r.isNone(2))
throw std::runtime_error(".to() does not accept copy argument");
return std::make_tuple(
tensor.device(),
tensor.scalar_type(),
r.toBool(1),
r.toBool(2),
r.memoryformatOptional(3));
}
}
} // namespace torch::autograd::utils
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