1// Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit
2void CreateModel(Model *model) {
3  OperandType type2(Type::INT32, {});
4  OperandType type1(Type::TENSOR_INT32, {2}, 0.25f, 0);
5  OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.5f, 0);
6  OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1,1,1,2}, 1.f, 0);
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 uint8_t op2_init[] = {2, 4, 2, 0, 2, 2, 2, 0};
18  model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 8);
19  static int32_t op3_init[] = {0, 0};
20  model->setOperandValue(op3, op3_init, sizeof(int32_t) * 2);
21  static int32_t pad0_init[] = {0};
22  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
23  static int32_t act_init[] = {0};
24  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
25  static int32_t stride_init[] = {1};
26  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
27  static int32_t channelMultiplier_init[] = {1};
28  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
29  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
30  // Phase 3, inputs and outputs
31  model->identifyInputsAndOutputs(
32    {op1},
33    {op4});
34  assert(model->isValid());
35}
36
37bool is_ignored(int i) {
38  static std::set<int> ignore = {};
39  return ignore.find(i) != ignore.end();
40}
41