1// Generated file (from: svdf2_relaxed.mod.py). Do not edit
2void CreateModel(Model *model) {
3  OperandType type5(Type::INT32, {});
4  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
5  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
6  OperandType type4(Type::TENSOR_FLOAT32, {2, 80});
7  OperandType type3(Type::TENSOR_FLOAT32, {4});
8  OperandType type2(Type::TENSOR_FLOAT32, {8, 10});
9  OperandType type1(Type::TENSOR_FLOAT32, {8, 3});
10  // Phase 1, operands
11  auto input = model->addOperand(&type0);
12  auto weights_feature = model->addOperand(&type1);
13  auto weights_time = model->addOperand(&type2);
14  auto bias = model->addOperand(&type3);
15  auto state_in = model->addOperand(&type4);
16  auto rank_param = model->addOperand(&type5);
17  auto activation_param = model->addOperand(&type5);
18  auto state_out = model->addOperand(&type4);
19  auto output = model->addOperand(&type6);
20  // Phase 2, operations
21  static int32_t rank_param_init[] = {2};
22  model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
23  static int32_t activation_param_init[] = {0};
24  model->setOperandValue(activation_param, activation_param_init, sizeof(int32_t) * 1);
25  model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
26  // Phase 3, inputs and outputs
27  model->identifyInputsAndOutputs(
28    {input, weights_feature, weights_time, bias, state_in},
29    {state_out, output});
30  // Phase 4: set relaxed execution
31  model->relaxComputationFloat32toFloat16(true);
32  assert(model->isValid());
33}
34
35bool is_ignored(int i) {
36  static std::set<int> ignore = {0};
37  return ignore.find(i) != ignore.end();
38}
39