"_1 = ", "tensorflow::ops::Placeholder(scope.WithOpName(\"",
                  arg.name(), "\"), ", type, ");\n");
              strings::StrAppend(
                  out, absl::Substitute("    InputList $0({$0_0, $0_1});\n",
                                        arg.name()));
            } else {
              strings::StrAppend(
                  out, "    auto ", arg.name(), " = ",

  };

  if (!can_convert_to_fully_connected(op)) {
    return false;
  }

  Value input_lhs = get_real_input_value(op.getX());
  Value input_rhs = get_real_input_value(op.getY());

  Value legalized_lhs =
      op.getAdjX() ? create_z_x_transpose_op(input_lhs) : input_lhs;

  // The rhs need to be transposed if adj_y == false AND this matmul will be
  // legalized to tfl.fully_connected

    const auto& api_def_arg = *FindInputArg(api_def.arg_order(i), api_def);
    arg_types.push_back(strings::StrCat(
        "::tensorflow::", ArgIsList(arg) ? "InputList" : "Input"));
    arg_names.push_back(AvoidCPPKeywords(api_def_arg.rename_to()));

    // TODO(keveman): Include input type information.
    StringPiece description = api_def_arg.description();