// CHECK-NEXT:     }, {
  // CHECK-NEXT:       opcode_index: 1,
  // CHECK-NEXT:       inputs: [ 0, 2 ],
  // CHECK-NEXT:       outputs: [ 3 ],
  // CHECK-NEXT:       builtin_options_type: MulOptions,
  // CHECK-NEXT:       builtin_options: {
  // CHECK-EMPTY:
  // CHECK-NEXT:       }
  // CHECK-NEXT:     }, {
  // CHECK-NEXT:       opcode_index: 2,
  // CHECK-NEXT:       inputs: [ 3, 2 ],

  for (auto msubgraph : *mutable_subgraphs) {
    auto operators = msubgraph->mutable_operators();
    for (auto op : *operators) {
      auto opcode_idx = op->opcode_index();
      auto opcodes = mutable_model->operator_codes();
      auto opcode = (*opcodes)[opcode_idx]->builtin_code();
      if (opcode == tflite::BuiltinOperator_CUSTOM) {
        std::vector<int32_t> inputs(op->inputs()->begin(), op->inputs()->end());

// CHECK-NEXT:      outputs: [ 2 ],
// CHECK-NEXT:      builtin_options_type: MulOptions,
// CHECK-NEXT:      builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT:      }
// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 1,
// CHECK-NEXT:      inputs: [ 2, 1 ],
// CHECK-NEXT:      outputs: [ 3 ],

  ASSERT_THAT(GetBuiltinCode(model_.operator_codes[op1->opcode_index].get()),
              Eq(BuiltinOperator_QUANTIZE));
  ASSERT_THAT(GetBuiltinCode(model_.operator_codes[op2->opcode_index].get()),
              Eq(BuiltinOperator_QUANTIZE));
  ASSERT_THAT(GetBuiltinCode(model_.operator_codes[op3->opcode_index].get()),
              Eq(BuiltinOperator_PACK));

// CHECK-NEXT:     outputs: [ 3 ],
// CHECK-NEXT:     operators: [ {
// CHECK-NEXT:       inputs: [ 0, 1 ],
// CHECK-NEXT:       outputs: [ 2 ]
// CHECK-NEXT:     }, {
// CHECK-NEXT:       opcode_index: 1,
// CHECK-NEXT:       inputs: [ 2, 0, 1 ],
// CHECK-NEXT:       outputs: [ 3 ],
// CHECK-NEXT:       builtin_options_type: IfOptions,
// CHECK-NEXT:       builtin_options: {

// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 1,
// CHECK-NEXT:      inputs: [ 2, 3, 4 ],
// CHECK-NEXT:      outputs: [ 5 ],
// CHECK-NEXT:      builtin_options_type: Conv2DOptions,
// CHECK-NEXT:      builtin_options: {
// CHECK-NEXT:        stride_w: 2,
// CHECK-NEXT:        stride_h: 2
// CHECK-NEXT:      }
// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 2,
// CHECK-NEXT:      inputs: [ 5, 1 ],

// CHECK-NEXT:     operators: [ {
// CHECK-NEXT:       opcode_index: 2,
// CHECK-NEXT:       inputs: [ 0, 2 ],
// CHECK-NEXT:       outputs: [ 3 ],
// CHECK-NEXT:       builtin_options_type: SubOptions,
// CHECK-NEXT:       builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT:       }
// CHECK-NEXT:     }, {
// CHECK-NEXT:       opcode_index: 3,
// CHECK-NEXT:       inputs: [ 1, 1 ],

      const auto op = subgraph->operators()->Get(op_idx);
      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;
  }
};

// CHECK-NEXT:      }
// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 1,
// CHECK-NEXT:      inputs: [ 2, 1 ],
// CHECK-NEXT:      outputs: [ 3 ],
// CHECK-NEXT:      custom_options: [ 3, 68, 105, 118, 0, 20, 18, 3, 68, 105, 118, 26, 0, 26, 0, 42, 7, 10, 1, 84, 18, 2, 48, 1, 50, 0, 0, 2, 27, 23, 20, 20, 4, 40, 1 ]
// CHECK-NEXT:    }, {
// CHECK-NEXT:      opcode_index: 2,
// CHECK-NEXT:      inputs: [ 3 ],

// CHECK-NEXT:     operators: [ {
// CHECK-NEXT:       opcode_index: 2,
// CHECK-NEXT:       inputs: [ 0, 2 ],
// CHECK-NEXT:       outputs: [ 3 ],
// CHECK-NEXT:       builtin_options_type: SubOptions,
// CHECK-NEXT:       builtin_options: {
// CHECK-EMPTY:
// CHECK-NEXT:       }
// CHECK-NEXT:     }, {
// CHECK-NEXT:       opcode_index: 3,
// CHECK-NEXT:       inputs: [ 1, 1 ],