if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(
        input_index, " out of range for ", op_name);
    return nullptr;
  }

  const tensorflow::OpDef_ArgDef& input_arg = op_def->input_arg()[input_index];

  if (input_arg.number_attr().empty()) {
    status->status = tensorflow::errors::NotFound(

      absl::StrCat("    signature {"
                   "      name: 'MatMulFunction'"
                   "      input_arg {"
                   "        name: 'a'"
                   "        type: DT_FLOAT"
                   "      }"
                   "      input_arg {"
                   "        name: 'b'"
                   "        type: DT_FLOAT"
                   "      }"

string AddVariablesFunction() {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"
      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"

                        const std::vector<IOSpec>& inputs) {
    const OpDef& signature = fdef.signature();
    ASSERT_EQ(inputs.size(), signature.input_arg_size());
    for (int i = 0; i < inputs.size(); ++i) {
      const OpDef::ArgDef& arg = signature.input_arg(i);
      const IOSpec& in = inputs[i];
      if (in.second != DT_INVALID) {
        ASSERT_EQ(arg.type(), in.second)

}

string MatMulFunction() {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'MatMulFunction'"
      "      input_arg {"
      "        name: 'a'"
      "        type: DT_FLOAT"
      "      }"
      "      output_arg {"
      "        name: 'm'"
      "        type: DT_FLOAT"
      "      }"
      "    }"