1 // Generated file (from: lstm3_state3.mod.py). Do not edit
CreateModel(Model * model)2 void 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
is_ignored(int i)51 bool is_ignored(int i) {
52 static std::set<int> ignore = {1, 2, 0};
53 return ignore.find(i) != ignore.end();
54 }
55