1// Generated file (from: lstm3_state3.mod.py). Do not edit
2void CreateModel(Model *model) {
3  OperandType type5(Type::TENSOR_FLOAT32, {0});
4  OperandType type4(Type::TENSOR_FLOAT32, {16,20});
5  OperandType type9(Type::TENSOR_FLOAT32, {1});
6  OperandType type6(Type::TENSOR_FLOAT32, {2, 16});
7  OperandType type7(Type::TENSOR_FLOAT32, {2, 20});
8  OperandType type0(Type::TENSOR_FLOAT32, {2, 5});
9  OperandType type10(Type::TENSOR_FLOAT32, {2, 80});
10  OperandType type2(Type::TENSOR_FLOAT32, {20, 16});
11  OperandType type1(Type::TENSOR_FLOAT32, {20, 5});
12  OperandType type3(Type::TENSOR_FLOAT32, {20});
13  OperandType type8(Type::TENSOR_INT32, {1});
14  // Phase 1, operands
15  auto input = model->addOperand(&type0);
16  auto input_to_input_weights = model->addOperand(&type1);
17  auto input_to_forget_weights = model->addOperand(&type1);
18  auto input_to_cell_weights = model->addOperand(&type1);
19  auto input_to_output_weights = model->addOperand(&type1);
20  auto recurrent_to_intput_weights = model->addOperand(&type2);
21  auto recurrent_to_forget_weights = model->addOperand(&type2);
22  auto recurrent_to_cell_weights = model->addOperand(&type2);
23  auto recurrent_to_output_weights = model->addOperand(&type2);
24  auto cell_to_input_weights = model->addOperand(&type3);
25  auto cell_to_forget_weights = model->addOperand(&type3);
26  auto cell_to_output_weights = model->addOperand(&type3);
27  auto input_gate_bias = model->addOperand(&type3);
28  auto forget_gate_bias = model->addOperand(&type3);
29  auto cell_gate_bias = model->addOperand(&type3);
30  auto output_gate_bias = model->addOperand(&type3);
31  auto projection_weights = model->addOperand(&type4);
32  auto projection_bias = model->addOperand(&type5);
33  auto output_state_in = model->addOperand(&type6);
34  auto cell_state_in = model->addOperand(&type7);
35  auto activation_param = model->addOperand(&type8);
36  auto cell_clip_param = model->addOperand(&type9);
37  auto proj_clip_param = model->addOperand(&type9);
38  auto scratch_buffer = model->addOperand(&type10);
39  auto output_state_out = model->addOperand(&type6);
40  auto cell_state_out = model->addOperand(&type7);
41  auto output = model->addOperand(&type6);
42  // Phase 2, operations
43  model->addOperation(ANEURALNETWORKS_LSTM, {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param}, {scratch_buffer, output_state_out, cell_state_out, output});
44  // Phase 3, inputs and outputs
45  model->identifyInputsAndOutputs(
46    {input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_intput_weights, recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights, input_gate_bias, forget_gate_bias, cell_gate_bias, output_gate_bias, projection_weights, projection_bias, output_state_in, cell_state_in, activation_param, cell_clip_param, proj_clip_param},
47    {scratch_buffer, output_state_out, cell_state_out, output});
48  assert(model->isValid());
49}
50
51bool is_ignored(int i) {
52  static std::set<int> ignore = {1, 2, 0};
53  return ignore.find(i) != ignore.end();
54}
55