1 // clang-format off 2 // Generated file (from: depthwise_conv.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 assert(model->isValid()); 39 } 40 41 inline bool is_ignored(int i) { 42 static std::set<int> ignore = {}; 43 return ignore.find(i) != ignore.end(); 44 } 45 46 void CreateModel_dynamic_output_shape(Model *model) { 47 OperandType type0(Type::INT32, {}); 48 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 49 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 50 OperandType type3(Type::TENSOR_FLOAT32, {3}); 51 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); 52 // Phase 1, operands 53 auto op2 = model->addOperand(&type1); 54 auto op0 = model->addOperand(&type2); 55 auto op1 = model->addOperand(&type3); 56 auto b4 = model->addOperand(&type0); 57 auto b5 = model->addOperand(&type0); 58 auto b6 = model->addOperand(&type0); 59 auto b7 = model->addOperand(&type0); 60 auto b8 = model->addOperand(&type0); 61 auto op3 = model->addOperand(&type4); 62 // Phase 2, operations 63 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 64 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 65 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 66 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 67 static int32_t b4_init[] = {1}; 68 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 69 static int32_t b5_init[] = {1}; 70 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 71 static int32_t b6_init[] = {1}; 72 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 73 static int32_t b7_init[] = {1}; 74 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 75 static int32_t b8_init[] = {0}; 76 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 77 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 78 // Phase 3, inputs and outputs 79 model->identifyInputsAndOutputs( 80 {op2}, 81 {op3}); 82 assert(model->isValid()); 83 } 84 85 inline bool is_ignored_dynamic_output_shape(int i) { 86 static std::set<int> ignore = {}; 87 return ignore.find(i) != ignore.end(); 88 } 89 90 void CreateModel_2(Model *model) { 91 OperandType type0(Type::INT32, {}); 92 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 93 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 94 OperandType type3(Type::TENSOR_FLOAT32, {3}); 95 // Phase 1, operands 96 auto op2 = model->addOperand(&type1); 97 auto op0 = model->addOperand(&type2); 98 auto op1 = model->addOperand(&type3); 99 auto b4 = model->addOperand(&type0); 100 auto b5 = model->addOperand(&type0); 101 auto b6 = model->addOperand(&type0); 102 auto b7 = model->addOperand(&type0); 103 auto b8 = model->addOperand(&type0); 104 auto op3 = model->addOperand(&type1); 105 // Phase 2, operations 106 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 107 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 108 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 109 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 110 static int32_t b4_init[] = {1}; 111 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 112 static int32_t b5_init[] = {1}; 113 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 114 static int32_t b6_init[] = {1}; 115 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 116 static int32_t b7_init[] = {1}; 117 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 118 static int32_t b8_init[] = {0}; 119 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 120 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 121 // Phase 3, inputs and outputs 122 model->identifyInputsAndOutputs( 123 {op2}, 124 {op3}); 125 assert(model->isValid()); 126 } 127 128 inline bool is_ignored_2(int i) { 129 static std::set<int> ignore = {}; 130 return ignore.find(i) != ignore.end(); 131 } 132 133 void CreateModel_dynamic_output_shape_2(Model *model) { 134 OperandType type0(Type::INT32, {}); 135 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); 136 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3}); 137 OperandType type3(Type::TENSOR_FLOAT32, {3}); 138 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); 139 // Phase 1, operands 140 auto op2 = model->addOperand(&type1); 141 auto op0 = model->addOperand(&type2); 142 auto op1 = model->addOperand(&type3); 143 auto b4 = model->addOperand(&type0); 144 auto b5 = model->addOperand(&type0); 145 auto b6 = model->addOperand(&type0); 146 auto b7 = model->addOperand(&type0); 147 auto b8 = model->addOperand(&type0); 148 auto op3 = model->addOperand(&type4); 149 // Phase 2, operations 150 static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f}; 151 model->setOperandValue(op0, op0_init, sizeof(float) * 3); 152 static float op1_init[] = {0.0f, 0.0f, 0.0f}; 153 model->setOperandValue(op1, op1_init, sizeof(float) * 3); 154 static int32_t b4_init[] = {1}; 155 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); 156 static int32_t b5_init[] = {1}; 157 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); 158 static int32_t b6_init[] = {1}; 159 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); 160 static int32_t b7_init[] = {1}; 161 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); 162 static int32_t b8_init[] = {0}; 163 model->setOperandValue(b8, b8_init, sizeof(int32_t) * 1); 164 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op2, op0, op1, b4, b5, b6, b7, b8}, {op3}); 165 // Phase 3, inputs and outputs 166 model->identifyInputsAndOutputs( 167 {op2}, 168 {op3}); 169 assert(model->isValid()); 170 } 171 172 inline bool is_ignored_dynamic_output_shape_2(int i) { 173 static std::set<int> ignore = {}; 174 return ignore.find(i) != ignore.end(); 175 } 176 177
