depthwise_conv2d_float_large_weights_as_inputs.model.cpp revision bee07f73a5f998a2dd6dc581e7776557c21f9684
1// Generated file (from: depthwise_conv2d_float_large_weights_as_inputs.mod.py). Do not edit 2void CreateModel(Model *model) { 3 OperandType type3(Type::INT32, {}); 4 OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 2}); 5 OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); 6 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3}); 7 OperandType type2(Type::TENSOR_FLOAT32, {2}); 8 // Phase 1, operands 9 auto op1 = model->addOperand(&type0); 10 auto op2 = model->addOperand(&type1); 11 auto op3 = model->addOperand(&type2); 12 auto pad0 = model->addOperand(&type3); 13 auto act = model->addOperand(&type3); 14 auto stride = model->addOperand(&type3); 15 auto channelMultiplier = model->addOperand(&type3); 16 auto op4 = model->addOperand(&type4); 17 // Phase 2, operations 18 static int32_t pad0_init[] = {0}; 19 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 20 static int32_t act_init[] = {0}; 21 model->setOperandValue(act, act_init, sizeof(int32_t) * 1); 22 static int32_t stride_init[] = {1}; 23 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 24 static int32_t channelMultiplier_init[] = {1}; 25 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1); 26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); 27 // Phase 3, inputs and outputs 28 model->identifyInputsAndOutputs( 29 {op1, op2, op3}, 30 {op4}); 31 assert(model->isValid()); 32} 33 34bool is_ignored(int i) { 35 static std::set<int> ignore = {}; 36 return ignore.find(i) != ignore.end(); 37} 38