1 // clang-format off 2 // Generated file (from: bidirectional_sequence_lstm.mod.py). Do not edit 3 void CreateModel(Model *model) { 4 OperandType type0(Type::TENSOR_FLOAT32, {3, 1, 2}); 5 OperandType type1(Type::TENSOR_FLOAT32, {4, 2}); 6 OperandType type2(Type::TENSOR_FLOAT32, {4, 4}); 7 OperandType type3(Type::TENSOR_FLOAT32, {4}); 8 OperandType type4(Type::TENSOR_FLOAT32, {1, 4}); 9 OperandType type5(Type::TENSOR_FLOAT32, {3, 1, 4}); 10 OperandType type6(Type::INT32, {}); 11 OperandType type7(Type::FLOAT32, {}); 12 OperandType type8(Type::BOOL, {}); 13 // Phase 1, operands 14 auto input = model->addOperand(&type0); 15 auto fw_input_to_input_weights = model->addOperand(&type1); 16 auto fw_input_to_forget_weights = model->addOperand(&type1); 17 auto fw_input_to_cell_weights = model->addOperand(&type1); 18 auto fw_input_to_output_weights = model->addOperand(&type1); 19 auto fw_recurrent_to_input_weights = model->addOperand(&type2); 20 auto fw_recurrent_to_forget_weights = model->addOperand(&type2); 21 auto fw_recurrent_to_cell_weights = model->addOperand(&type2); 22 auto fw_recurrent_to_output_weights = model->addOperand(&type2); 23 auto fw_cell_to_input_weights = model->addOperand(&type3); 24 auto fw_cell_to_forget_weights = model->addOperand(&type3); 25 auto fw_cell_to_output_weights = model->addOperand(&type3); 26 auto fw_input_gate_bias = model->addOperand(&type3); 27 auto fw_forget_gate_bias = model->addOperand(&type3); 28 auto fw_cell_bias = model->addOperand(&type3); 29 auto fw_output_gate_bias = model->addOperand(&type3); 30 auto fw_projection_weights = model->addOperand(&type2); 31 auto fw_projection_bias = model->addOperand(&type3); 32 auto bw_input_to_input_weights = model->addOperand(&type1); 33 auto bw_input_to_forget_weights = model->addOperand(&type1); 34 auto bw_input_to_cell_weights = model->addOperand(&type1); 35 auto bw_input_to_output_weights = model->addOperand(&type1); 36 auto bw_recurrent_to_input_weights = model->addOperand(&type2); 37 auto bw_recurrent_to_forget_weights = model->addOperand(&type2); 38 auto bw_recurrent_to_cell_weights = model->addOperand(&type2); 39 auto bw_recurrent_to_output_weights = model->addOperand(&type2); 40 auto bw_cell_to_input_weights = model->addOperand(&type3); 41 auto bw_cell_to_forget_weights = model->addOperand(&type3); 42 auto bw_cell_to_output_weights = model->addOperand(&type3); 43 auto bw_input_gate_bias = model->addOperand(&type3); 44 auto bw_forget_gate_bias = model->addOperand(&type3); 45 auto bw_cell_bias = model->addOperand(&type3); 46 auto bw_output_gate_bias = model->addOperand(&type3); 47 auto bw_projection_weights = model->addOperand(&type2); 48 auto bw_projection_bias = model->addOperand(&type3); 49 auto fw_activatiom_state = model->addOperand(&type4); 50 auto fw_cell_state = model->addOperand(&type4); 51 auto bw_activatiom_state = model->addOperand(&type4); 52 auto bw_cell_state = model->addOperand(&type4); 53 auto input1 = model->addOperand(&type0); 54 auto fw_aux_input_to_input_weights = model->addOperand(&type1); 55 auto fw_input_to_forget_weights1 = model->addOperand(&type1); 56 auto fw_aux_input_to_cell_weights = model->addOperand(&type1); 57 auto fw_aux_input_to_output_weights = model->addOperand(&type1); 58 auto bw_aux_input_to_input_weights = model->addOperand(&type1); 59 auto bw_input_to_forget_weights1 = model->addOperand(&type1); 60 auto bw_aux_input_to_cell_weights = model->addOperand(&type1); 61 auto bw_aux_input_to_output_weights = model->addOperand(&type1); 62 auto activation = model->addOperand(&type6); 63 auto cell_clip = model->addOperand(&type7); 64 auto proj_clip = model->addOperand(&type7); 65 auto merge_outputs = model->addOperand(&type8); 66 auto time_major = model->addOperand(&type8); 67 auto input_layer_norm_weights = model->addOperand(&type3); 68 auto forget_layer_norm_weights = model->addOperand(&type3); 69 auto cell_layer_norm_weights = model->addOperand(&type3); 70 auto output_layer_norm_weights = model->addOperand(&type3); 71 auto input_layer_norm_weights1 = model->addOperand(&type3); 72 auto forget_layer_norm_weights1 = model->addOperand(&type3); 73 auto cell_layer_norm_weights1 = model->addOperand(&type3); 74 auto output_layer_norm_weights1 = model->addOperand(&type3); 75 auto fw_output = model->addOperand(&type5); 76 auto bw_output = model->addOperand(&type5); 77 // Phase 2, operations 78 static int32_t activation_init[] = {4}; 79 model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1); 80 static float cell_clip_init[] = {0.0f}; 81 model->setOperandValue(cell_clip, cell_clip_init, sizeof(float) * 1); 82 static float proj_clip_init[] = {0.0f}; 83 model->setOperandValue(proj_clip, proj_clip_init, sizeof(float) * 1); 84 static bool8 merge_outputs_init[] = {false}; 85 model->setOperandValue(merge_outputs, merge_outputs_init, sizeof(bool8) * 1); 86 static bool8 time_major_init[] = {true}; 87 model->setOperandValue(time_major, time_major_init, sizeof(bool8) * 1); 88 model->addOperation(ANEURALNETWORKS_BIDIRECTIONAL_SEQUENCE_LSTM, {input, fw_input_to_input_weights, fw_input_to_forget_weights, fw_input_to_cell_weights, fw_input_to_output_weights, fw_recurrent_to_input_weights, fw_recurrent_to_forget_weights, fw_recurrent_to_cell_weights, fw_recurrent_to_output_weights, fw_cell_to_input_weights, fw_cell_to_forget_weights, fw_cell_to_output_weights, fw_input_gate_bias, fw_forget_gate_bias, fw_cell_bias, fw_output_gate_bias, fw_projection_weights, fw_projection_bias, bw_input_to_input_weights, bw_input_to_forget_weights, bw_input_to_cell_weights, bw_input_to_output_weights, bw_recurrent_to_input_weights, bw_recurrent_to_forget_weights, bw_recurrent_to_cell_weights, bw_recurrent_to_output_weights, bw_cell_to_input_weights, bw_cell_to_forget_weights, bw_cell_to_output_weights, bw_input_gate_bias, bw_forget_gate_bias, bw_cell_bias, bw_output_gate_bias, bw_projection_weights, bw_projection_bias, fw_activatiom_state, fw_cell_state, bw_activatiom_state, bw_cell_state, input1, fw_aux_input_to_input_weights, fw_input_to_forget_weights1, fw_aux_input_to_cell_weights, fw_aux_input_to_output_weights, bw_aux_input_to_input_weights, bw_input_to_forget_weights1, bw_aux_input_to_cell_weights, bw_aux_input_to_output_weights, activation, cell_clip, proj_clip, merge_outputs, time_major, input_layer_norm_weights, forget_layer_norm_weights, cell_layer_norm_weights, output_layer_norm_weights, input_layer_norm_weights1, forget_layer_norm_weights1, cell_layer_norm_weights1, output_layer_norm_weights1}, {fw_output, bw_output}); 89 // Phase 3, inputs and outputs 90 model->identifyInputsAndOutputs( 91 {input, fw_input_to_input_weights, fw_input_to_forget_weights, fw_input_to_cell_weights, fw_input_to_output_weights, fw_recurrent_to_input_weights, fw_recurrent_to_forget_weights, fw_recurrent_to_cell_weights, fw_recurrent_to_output_weights, fw_cell_to_input_weights, fw_cell_to_forget_weights, fw_cell_to_output_weights, fw_input_gate_bias, fw_forget_gate_bias, fw_cell_bias, fw_output_gate_bias, fw_projection_weights, fw_projection_bias, bw_input_to_input_weights, bw_input_to_forget_weights, bw_input_to_cell_weights, bw_input_to_output_weights, bw_recurrent_to_input_weights, bw_recurrent_to_forget_weights, bw_recurrent_to_cell_weights, bw_recurrent_to_output_weights, bw_cell_to_input_weights, bw_cell_to_forget_weights, bw_cell_to_output_weights, bw_input_gate_bias, bw_forget_gate_bias, bw_cell_bias, bw_output_gate_bias, bw_projection_weights, bw_projection_bias, fw_activatiom_state, fw_cell_state, bw_activatiom_state, bw_cell_state, input1, fw_aux_input_to_input_weights, fw_input_to_forget_weights1, fw_aux_input_to_cell_weights, fw_aux_input_to_output_weights, bw_aux_input_to_input_weights, bw_input_to_forget_weights1, bw_aux_input_to_cell_weights, bw_aux_input_to_output_weights, input_layer_norm_weights, forget_layer_norm_weights, cell_layer_norm_weights, output_layer_norm_weights, input_layer_norm_weights1, forget_layer_norm_weights1, cell_layer_norm_weights1, output_layer_norm_weights1}, 92 {fw_output, bw_output}); 93 assert(model->isValid()); 94 } 95 96 inline bool is_ignored(int i) { 97 static std::set<int> ignore = {}; 98 return ignore.find(i) != ignore.end(); 99 } 100 101 void CreateModel_dynamic_output_shape(Model *model) { 102 OperandType type0(Type::TENSOR_FLOAT32, {3, 1, 2}); 103 OperandType type1(Type::TENSOR_FLOAT32, {4, 2}); 104 OperandType type2(Type::TENSOR_FLOAT32, {4, 4}); 105 OperandType type3(Type::TENSOR_FLOAT32, {4}); 106 OperandType type4(Type::TENSOR_FLOAT32, {1, 4}); 107 OperandType type6(Type::INT32, {}); 108 OperandType type7(Type::FLOAT32, {}); 109 OperandType type8(Type::BOOL, {}); 110 OperandType type9(Type::TENSOR_FLOAT32, {0, 0, 0}); 111 // Phase 1, operands 112 auto input = model->addOperand(&type0); 113 auto fw_input_to_input_weights = model->addOperand(&type1); 114 auto fw_input_to_forget_weights = model->addOperand(&type1); 115 auto fw_input_to_cell_weights = model->addOperand(&type1); 116 auto fw_input_to_output_weights = model->addOperand(&type1); 117 auto fw_recurrent_to_input_weights = model->addOperand(&type2); 118 auto fw_recurrent_to_forget_weights = model->addOperand(&type2); 119 auto fw_recurrent_to_cell_weights = model->addOperand(&type2); 120 auto fw_recurrent_to_output_weights = model->addOperand(&type2); 121 auto fw_cell_to_input_weights = model->addOperand(&type3); 122 auto fw_cell_to_forget_weights = model->addOperand(&type3); 123 auto fw_cell_to_output_weights = model->addOperand(&type3); 124 auto fw_input_gate_bias = model->addOperand(&type3); 125 auto fw_forget_gate_bias = model->addOperand(&type3); 126 auto fw_cell_bias = model->addOperand(&type3); 127 auto fw_output_gate_bias = model->addOperand(&type3); 128 auto fw_projection_weights = model->addOperand(&type2); 129 auto fw_projection_bias = model->addOperand(&type3); 130 auto bw_input_to_input_weights = model->addOperand(&type1); 131 auto bw_input_to_forget_weights = model->addOperand(&type1); 132 auto bw_input_to_cell_weights = model->addOperand(&type1); 133 auto bw_input_to_output_weights = model->addOperand(&type1); 134 auto bw_recurrent_to_input_weights = model->addOperand(&type2); 135 auto bw_recurrent_to_forget_weights = model->addOperand(&type2); 136 auto bw_recurrent_to_cell_weights = model->addOperand(&type2); 137 auto bw_recurrent_to_output_weights = model->addOperand(&type2); 138 auto bw_cell_to_input_weights = model->addOperand(&type3); 139 auto bw_cell_to_forget_weights = model->addOperand(&type3); 140 auto bw_cell_to_output_weights = model->addOperand(&type3); 141 auto bw_input_gate_bias = model->addOperand(&type3); 142 auto bw_forget_gate_bias = model->addOperand(&type3); 143 auto bw_cell_bias = model->addOperand(&type3); 144 auto bw_output_gate_bias = model->addOperand(&type3); 145 auto bw_projection_weights = model->addOperand(&type2); 146 auto bw_projection_bias = model->addOperand(&type3); 147 auto fw_activatiom_state = model->addOperand(&type4); 148 auto fw_cell_state = model->addOperand(&type4); 149 auto bw_activatiom_state = model->addOperand(&type4); 150 auto bw_cell_state = model->addOperand(&type4); 151 auto input1 = model->addOperand(&type0); 152 auto fw_aux_input_to_input_weights = model->addOperand(&type1); 153 auto fw_input_to_forget_weights1 = model->addOperand(&type1); 154 auto fw_aux_input_to_cell_weights = model->addOperand(&type1); 155 auto fw_aux_input_to_output_weights = model->addOperand(&type1); 156 auto bw_aux_input_to_input_weights = model->addOperand(&type1); 157 auto bw_input_to_forget_weights1 = model->addOperand(&type1); 158 auto bw_aux_input_to_cell_weights = model->addOperand(&type1); 159 auto bw_aux_input_to_output_weights = model->addOperand(&type1); 160 auto activation = model->addOperand(&type6); 161 auto cell_clip = model->addOperand(&type7); 162 auto proj_clip = model->addOperand(&type7); 163 auto merge_outputs = model->addOperand(&type8); 164 auto time_major = model->addOperand(&type8); 165 auto input_layer_norm_weights = model->addOperand(&type3); 166 auto forget_layer_norm_weights = model->addOperand(&type3); 167 auto cell_layer_norm_weights = model->addOperand(&type3); 168 auto output_layer_norm_weights = model->addOperand(&type3); 169 auto input_layer_norm_weights1 = model->addOperand(&type3); 170 auto forget_layer_norm_weights1 = model->addOperand(&type3); 171 auto cell_layer_norm_weights1 = model->addOperand(&type3); 172 auto output_layer_norm_weights1 = model->addOperand(&type3); 173 auto fw_output = model->addOperand(&type9); 174 auto bw_output = model->addOperand(&type9); 175 // Phase 2, operations 176 static int32_t activation_init[] = {4}; 177 model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1); 178 static float cell_clip_init[] = {0.0f}; 179 model->setOperandValue(cell_clip, cell_clip_init, sizeof(float) * 1); 180 static float proj_clip_init[] = {0.0f}; 181 model->setOperandValue(proj_clip, proj_clip_init, sizeof(float) * 1); 182 static bool8 merge_outputs_init[] = {false}; 183 model->setOperandValue(merge_outputs, merge_outputs_init, sizeof(bool8) * 1); 184 static bool8 time_major_init[] = {true}; 185 model->setOperandValue(time_major, time_major_init, sizeof(bool8) * 1); 186 model->addOperation(ANEURALNETWORKS_BIDIRECTIONAL_SEQUENCE_LSTM, {input, fw_input_to_input_weights, fw_input_to_forget_weights, fw_input_to_cell_weights, fw_input_to_output_weights, fw_recurrent_to_input_weights, fw_recurrent_to_forget_weights, fw_recurrent_to_cell_weights, fw_recurrent_to_output_weights, fw_cell_to_input_weights, fw_cell_to_forget_weights, fw_cell_to_output_weights, fw_input_gate_bias, fw_forget_gate_bias, fw_cell_bias, fw_output_gate_bias, fw_projection_weights, fw_projection_bias, bw_input_to_input_weights, bw_input_to_forget_weights, bw_input_to_cell_weights, bw_input_to_output_weights, bw_recurrent_to_input_weights, bw_recurrent_to_forget_weights, bw_recurrent_to_cell_weights, bw_recurrent_to_output_weights, bw_cell_to_input_weights, bw_cell_to_forget_weights, bw_cell_to_output_weights, bw_input_gate_bias, bw_forget_gate_bias, bw_cell_bias, bw_output_gate_bias, bw_projection_weights, bw_projection_bias, fw_activatiom_state, fw_cell_state, bw_activatiom_state, bw_cell_state, input1, fw_aux_input_to_input_weights, fw_input_to_forget_weights1, fw_aux_input_to_cell_weights, fw_aux_input_to_output_weights, bw_aux_input_to_input_weights, bw_input_to_forget_weights1, bw_aux_input_to_cell_weights, bw_aux_input_to_output_weights, activation, cell_clip, proj_clip, merge_outputs, time_major, input_layer_norm_weights, forget_layer_norm_weights, cell_layer_norm_weights, output_layer_norm_weights, input_layer_norm_weights1, forget_layer_norm_weights1, cell_layer_norm_weights1, output_layer_norm_weights1}, {fw_output, bw_output}); 187 // Phase 3, inputs and outputs 188 model->identifyInputsAndOutputs( 189 {input, fw_input_to_input_weights, fw_input_to_forget_weights, fw_input_to_cell_weights, fw_input_to_output_weights, fw_recurrent_to_input_weights, fw_recurrent_to_forget_weights, fw_recurrent_to_cell_weights, fw_recurrent_to_output_weights, fw_cell_to_input_weights, fw_cell_to_forget_weights, fw_cell_to_output_weights, fw_input_gate_bias, fw_forget_gate_bias, fw_cell_bias, fw_output_gate_bias, fw_projection_weights, fw_projection_bias, bw_input_to_input_weights, bw_input_to_forget_weights, bw_input_to_cell_weights, bw_input_to_output_weights, bw_recurrent_to_input_weights, bw_recurrent_to_forget_weights, bw_recurrent_to_cell_weights, bw_recurrent_to_output_weights, bw_cell_to_input_weights, bw_cell_to_forget_weights, bw_cell_to_output_weights, bw_input_gate_bias, bw_forget_gate_bias, bw_cell_bias, bw_output_gate_bias, bw_projection_weights, bw_projection_bias, fw_activatiom_state, fw_cell_state, bw_activatiom_state, bw_cell_state, input1, fw_aux_input_to_input_weights, fw_input_to_forget_weights1, fw_aux_input_to_cell_weights, fw_aux_input_to_output_weights, bw_aux_input_to_input_weights, bw_input_to_forget_weights1, bw_aux_input_to_cell_weights, bw_aux_input_to_output_weights, input_layer_norm_weights, forget_layer_norm_weights, cell_layer_norm_weights, output_layer_norm_weights, input_layer_norm_weights1, forget_layer_norm_weights1, cell_layer_norm_weights1, output_layer_norm_weights1}, 190 {fw_output, bw_output}); 191 assert(model->isValid()); 192 } 193 194 inline bool is_ignored_dynamic_output_shape(int i) { 195 static std::set<int> ignore = {}; 196 return ignore.find(i) != ignore.end(); 197 } 198 199
