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