expected_op_metadata->hardware());

      EXPECT_EQ(result_op_metadata->op_costs()->size(),
                expected_op_metadata->op_costs()->size());
      for (int i = 0; i < result_op_metadata->op_costs()->size(); ++i) {
        EXPECT_FLOAT_EQ(result_op_metadata->op_costs()->Get(i),
                        expected_op_metadata->op_costs()->Get(i));
      }
    }
  }
}

TEST(ExporterTest, Valid) {

    const tflite::OperatorT& op, const std::vector<Value>& vals_map,
    const std::vector<mlir::TensorType>& intermediate_types,
    Value optional_arg_marker,
    const std::vector<std::unique_ptr<tflite::OperatorCodeT>>& op_codes,
    const std::vector<std::string>& func_names,
    const std::vector<std::unique_ptr<tflite::TensorT>>& tensors, Location loc,
    OpBuilder builder,
    const std::unique_ptr<tflite::FlatBufferModel>& model_ptr) {

  // The resulting model should be:
  // reshape->dequantize->custom->custom->quantize->squeeze.
  ASSERT_THAT(subgraph->operators, SizeIs(6));
  const std::vector<BuiltinOperator> op_codes = {
      BuiltinOperator_RESHAPE,  BuiltinOperator_DEQUANTIZE,
      BuiltinOperator_CUSTOM,   BuiltinOperator_CUSTOM,
      BuiltinOperator_QUANTIZE, BuiltinOperator_SQUEEZE};