checkAndNormalizeInputs Class — pytorch Architecture

Source Code

aten/src/ATen/core/function_schema_inl.h lines 27–76

template <typename T>
inline void FunctionSchema::checkAndNormalizeInputs(
    std::vector<IValue>& inputs,
    const std::unordered_map<std::string, IValue>& kwargs) const {
  // Do we have more inputs than the schema accepts?
  TORCH_CHECK(
      inputs.size() <= arguments().size(),
      "Expected at most ",
      arguments().size(),
      " argument(s) for operator '",
      name(),
      "', but received ",
      inputs.size(),
      " argument(s). Declaration: ",
      *this);

  size_t consumed_kwargs = 0;
  for (const auto pos : c10::irange(arguments().size())) {
    const auto& argument = arguments()[pos];
    if (pos < inputs.size()) {
      checkArg<T>(inputs[pos], argument, pos);
      continue;
    }
    auto it = kwargs.find(argument.name());
    if (it != kwargs.end()) {
      checkArg<T>(it->second, argument, std::nullopt);
      inputs.push_back(it->second);
      consumed_kwargs++;
      continue;
    }
    if (argument.default_value()) {
      inputs.push_back(*argument.default_value());
      continue;
    }
    TORCH_CHECK(false,
        name(),
        "() is missing value for argument '",
        argument.name(),
        "'. Declaration: ",
        *this);
  }
  if (consumed_kwargs != kwargs.size()) {
    std::vector<std::string> names;
    names.reserve(kwargs.size());
    for(const auto& k : kwargs) {
      names.emplace_back(k.first);
    }
    TORCH_CHECK(false, findErrorInKwargs(names));
  }
}