1 // clang-format off 2 // Generated file (from: depthwise_conv_relaxed.mod.py). Do not edit 3 void CreateModel(Model *model) { 4 OperandType type0(Type::INT32, {}); 5 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 6 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 7 OperandType type3(Type::TENSOR_FLOAT32, {3}); 8 // Phase 1, operands 9 auto op2 = model->addOperand(&type1); 10 auto op0 = model->addOperand(&type2); 11 auto op1 = model->addOperand(&type3); 12 auto b4 = model->addOperand(&type0); 13 auto b5 = model->addOperand(&type0); 14 auto b6 = model->addOperand(&type0); 15 auto b7 = model->addOperand(&type0); 16 auto b8 = model->addOperand(&type0); 17 auto op3 = model->addOperand(&type1); 18 // Phase 2, operations 19 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 20 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 21 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 22 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 23 static int32_t b4_init[] = {1}; 24 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 25 static int32_t b5_init[] = {1}; 26 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 27 static int32_t b6_init[] = {1}; 28 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 29 static int32_t b7_init[] = {1}; 30 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 31 static int32_t b8_init[] = {0}; 32 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 33 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 34 // Phase 3, inputs and outputs 35 model->identifyInputsAndOutputs( 36 {op2}, 37 {op3}); 38 // Phase 4: set relaxed execution 39 model->relaxComputationFloat32toFloat16(true); 40 assert(model->isValid()); 41 } 42 43 inline bool is_ignored(int i) { 44 static std::set<int> ignore = {}; 45 return ignore.find(i) != ignore.end(); 46 } 47 48 void CreateModel_dynamic_output_shape(Model *model) { 49 OperandType type0(Type::INT32, {}); 50 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 51 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 52 OperandType type3(Type::TENSOR_FLOAT32, {3}); 53 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); 54 // Phase 1, operands 55 auto op2 = model->addOperand(&type1); 56 auto op0 = model->addOperand(&type2); 57 auto op1 = model->addOperand(&type3); 58 auto b4 = model->addOperand(&type0); 59 auto b5 = model->addOperand(&type0); 60 auto b6 = model->addOperand(&type0); 61 auto b7 = model->addOperand(&type0); 62 auto b8 = model->addOperand(&type0); 63 auto op3 = model->addOperand(&type4); 64 // Phase 2, operations 65 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 66 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 67 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 68 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 69 static int32_t b4_init[] = {1}; 70 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 71 static int32_t b5_init[] = {1}; 72 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 73 static int32_t b6_init[] = {1}; 74 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 75 static int32_t b7_init[] = {1}; 76 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 77 static int32_t b8_init[] = {0}; 78 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 79 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 80 // Phase 3, inputs and outputs 81 model->identifyInputsAndOutputs( 82 {op2}, 83 {op3}); 84 // Phase 4: set relaxed execution 85 model->relaxComputationFloat32toFloat16(true); 86 assert(model->isValid()); 87 } 88 89 inline bool is_ignored_dynamic_output_shape(int i) { 90 static std::set<int> ignore = {}; 91 return ignore.find(i) != ignore.end(); 92 } 93 94 void CreateModel_2(Model *model) { 95 OperandType type0(Type::INT32, {}); 96 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 97 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 98 OperandType type3(Type::TENSOR_FLOAT32, {3}); 99 // Phase 1, operands 100 auto op2 = model->addOperand(&type1); 101 auto op0 = model->addOperand(&type2); 102 auto op1 = model->addOperand(&type3); 103 auto b4 = model->addOperand(&type0); 104 auto b5 = model->addOperand(&type0); 105 auto b6 = model->addOperand(&type0); 106 auto b7 = model->addOperand(&type0); 107 auto b8 = model->addOperand(&type0); 108 auto op3 = model->addOperand(&type1); 109 // Phase 2, operations 110 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 111 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 112 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 113 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 114 static int32_t b4_init[] = {1}; 115 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 116 static int32_t b5_init[] = {1}; 117 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 118 static int32_t b6_init[] = {1}; 119 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 120 static int32_t b7_init[] = {1}; 121 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 122 static int32_t b8_init[] = {0}; 123 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 124 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 125 // Phase 3, inputs and outputs 126 model->identifyInputsAndOutputs( 127 {op2}, 128 {op3}); 129 // Phase 4: set relaxed execution 130 model->relaxComputationFloat32toFloat16(true); 131 assert(model->isValid()); 132 } 133 134 inline bool is_ignored_2(int i) { 135 static std::set<int> ignore = {}; 136 return ignore.find(i) != ignore.end(); 137 } 138 139 void CreateModel_dynamic_output_shape_2(Model *model) { 140 OperandType type0(Type::INT32, {}); 141 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 142 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 143 OperandType type3(Type::TENSOR_FLOAT32, {3}); 144 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); 145 // Phase 1, operands 146 auto op2 = model->addOperand(&type1); 147 auto op0 = model->addOperand(&type2); 148 auto op1 = model->addOperand(&type3); 149 auto b4 = model->addOperand(&type0); 150 auto b5 = model->addOperand(&type0); 151 auto b6 = model->addOperand(&type0); 152 auto b7 = model->addOperand(&type0); 153 auto b8 = model->addOperand(&type0); 154 auto op3 = model->addOperand(&type4); 155 // Phase 2, operations 156 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 157 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 158 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 159 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 160 static int32_t b4_init[] = {1}; 161 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 162 static int32_t b5_init[] = {1}; 163 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 164 static int32_t b6_init[] = {1}; 165 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 166 static int32_t b7_init[] = {1}; 167 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 168 static int32_t b8_init[] = {0}; 169 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 170 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 171 // Phase 3, inputs and outputs 172 model->identifyInputsAndOutputs( 173 {op2}, 174 {op3}); 175 // Phase 4: set relaxed execution 176 model->relaxComputationFloat32toFloat16(true); 177 assert(model->isValid()); 178 } 179 180 inline bool is_ignored_dynamic_output_shape_2(int i) { 181 static std::set<int> ignore = {}; 182 return ignore.find(i) != ignore.end(); 183 } 184 185
