1// Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit 2void CreateModel(Model *model) { 3 OperandType type2(Type::INT32, {}); 4 OperandType type1(Type::TENSOR_INT32, {2}, 0.25f, 0); 5 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.5f, 0); 6 OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1,1,1,2}, 1.f, 0); 7 // Phase 1, operands 8 auto op1 = model->addOperand(&type0); 9 auto op2 = model->addOperand(&type0); 10 auto op3 = model->addOperand(&type1); 11 auto pad0 = model->addOperand(&type2); 12 auto act = model->addOperand(&type2); 13 auto stride = model->addOperand(&type2); 14 auto channelMultiplier = model->addOperand(&type2); 15 auto op4 = model->addOperand(&type3); 16 // Phase 2, operations 17 static uint8_t op2_init[] = {2, 4, 2, 0, 2, 2, 2, 0}; 18 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 8); 19 static int32_t op3_init[] = {0, 0}; 20 model->setOperandValue(op3, op3_init, sizeof(int32_t) * 2); 21 static int32_t pad0_init[] = {0}; 22 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 23 static int32_t act_init[] = {0}; 24 model->setOperandValue(act, act_init, sizeof(int32_t) * 1); 25 static int32_t stride_init[] = {1}; 26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 27 static int32_t channelMultiplier_init[] = {1}; 28 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1); 29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 30 // Phase 3, inputs and outputs 31 model->identifyInputsAndOutputs( 32 {op1}, 33 {op4}); 34 assert(model->isValid()); 35} 36 37bool is_ignored(int i) { 38 static std::set<int> ignore = {}; 39 return ignore.find(i) != ignore.end(); 40} 41