text: // Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py). Do not edit
  void CreateModel(Model *model) {
    OperandType type3(Type::INT32, {});
    OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
    OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
    OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
    OperandType type2(Type::TENSOR_FLOAT32, {4});
    // Phase 1, operands
    auto op1 = model->addOperand(&type0);
    auto op2 = model->addOperand(&type1);
    auto op3 = model->addOperand(&type2);
    auto pad0 = model->addOperand(&type3);
    auto act = model->addOperand(&type3);
    auto stride = model->addOperand(&type3);
    auto channelMultiplier = model->addOperand(&type3);
    auto op4 = model->addOperand(&type4);
    // Phase 2, operations
    static int32_t pad0_init[] = {0};
    model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
    static int32_t act_init[] = {0};
    model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
    static int32_t stride_init[] = {1};
    model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
    static int32_t channelMultiplier_init[] = {1};
    model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
    model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
    // Phase 3, inputs and outputs
    model->identifyInputsAndOutputs(
      {op1, op2, op3},
      {op4});
    // Phase 4: set relaxed execution
    model->relaxComputationFloat32toFloat16(true);
    assert(model->isValid());
  }
  
  bool is_ignored(int i) {
    static std::set<int> ignore = {};
    return ignore.find(i) != ignore.end();
  }
  