1// Generated file (from: depthwise_conv2d_float_large_weights_as_inputs.mod.py). Do not edit
2void CreateModel(Model *model) {
3  OperandType type2(Type::INT32, {});
4  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
5  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
6  OperandType type1(Type::TENSOR_FLOAT32, {2});
7  // Phase 1, operands
8  auto op1 = model->addOperand(&type0);
9  auto op2 = model->addOperand(&type0);
10  auto op3 = model->addOperand(&type1);
11  auto pad0 = model->addOperand(&type2);
12  auto act = model->addOperand(&type2);
13  auto stride = model->addOperand(&type2);
14  auto channelMultiplier = model->addOperand(&type2);
15  auto op4 = model->addOperand(&type3);
16  // Phase 2, operations
17  static int32_t pad0_init[] = {0};
18  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
19  static int32_t act_init[] = {0};
20  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
21  static int32_t stride_init[] = {1};
22  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
23  static int32_t channelMultiplier_init[] = {1};
24  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
26  // Phase 3, inputs and outputs
27  model->identifyInputsAndOutputs(
28    {op1, op2, op3},
29    {op4});
30  assert(model->isValid());
31}
32
33bool is_ignored(int i) {
34  static std::set<int> ignore = {};
35  return ignore.find(i) != ignore.end();
36}
37