#pragma once

#include <torch/csrc/python_headers.h>
#include <ATen/core/Tensor.h>

#include <torch/csrc/utils/python_arg_parser.h>

namespace torch { namespace autograd { namespace 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<c10::optional<at::Device>, c10::optional<at::ScalarType>, bool, bool, c10::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(c10::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
