// check op and versioning.
  EXPECT_THAT(model_.operator_codes, SizeIs(2));
  EXPECT_THAT(GetBuiltinCode(model_.operator_codes[0].get()),
              Eq(BuiltinOperator_ADD));
  ASSERT_THAT(model_.operator_codes[0]->version, Eq(2));
  EXPECT_THAT(GetBuiltinCode(model_.operator_codes[1].get()),
              Eq(BuiltinOperator_RESHAPE));
  ASSERT_THAT(model_.operator_codes[1]->version, Eq(1));
}

      for (size_t i = 0; i < op->outputs()->size(); ++i) {
        if (op->outputs()->Get(i) == tensor_idx) {
          const uint32_t op_code_idx = op->opcode_index();
          *op_code = GetBuiltinCode(model->operator_codes()->Get(op_code_idx));
          return true;
        }
      }
    }
    return false;
  }
};

// Returns true if everything between the two graphs
// are identical except for name field.

    for (int j = 0; j < subgraph->operators()->Length(); ++j) {
      const tflite::Operator* op = subgraph->operators()->Get(j);
      const tflite::OperatorCode* op_code =
          model->operator_codes()->Get(op->opcode_index());
      auto status =
          tflite::CheckGpuDelegateCompatibility(op_code, op, subgraph, model);
      if (!status.ok()) {
        gpu_compatibile = false;

    A generic op for any TFLite custom operation.

    input: A list of inputs in the original op.
    custom_code: A string used to identify which exactly this op is, which
                 corresponds to operator_codes.custom_code in the flatbuffer.
    custom_option: a holder to save the op attributes in bytes fashion.
    output: A list of outputs in the original op.
  }];

  let arguments = (ins