1 // Generated file (from: conv_float_large_weights_as_inputs.mod.py). Do not edit 2 void CreateModel(Model *model) { 3 OperandType type3(Type::INT32, {}); 4 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 3}); 5 OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3}); 6 OperandType type2(Type::TENSOR_FLOAT32, {3}); 7 // Phase 1, operands 8 auto op1 = model->addOperand(&type0); 9 auto op2 = model->addOperand(&type1); 10 auto op3 = model->addOperand(&type2); 11 auto pad0 = model->addOperand(&type3); 12 auto act = model->addOperand(&type3); 13 auto stride = model->addOperand(&type3); 14 auto op4 = model->addOperand(&type0); 15 // Phase 2, operations 16 static int32_t pad0_init[] = {0}; 17 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 18 static int32_t act_init[] = {0}; 19 model->setOperandValue(act, act_init, sizeof(int32_t) * 1); 20 static int32_t stride_init[] = {1}; 21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 22 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 23 // Phase 3, inputs and outputs 24 model->identifyInputsAndOutputs( 25 {op1, op2, op3}, 26 {op4}); 27 assert(model->isValid()); 28 } 29 30 bool is_ignored(int i) { 31 static std::set<int> ignore = {}; 32 return ignore.find(i) != ignore.end(); 33 } 34
