| // Generated file (from: quantized.mod.py). Do not edit |
| void CreateModel(Model *model) { |
| OperandType type0(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_INT32, {1}); |
| OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}); |
| OperandType type1(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 1}); |
| // Phase 1, operands |
| auto b4 = model->addOperand(&type0); |
| auto b5 = model->addOperand(&type0); |
| auto b6 = model->addOperand(&type0); |
| auto b7 = model->addOperand(&type0); |
| auto op2 = model->addOperand(&type1); |
| auto op3 = model->addOperand(&type2); |
| auto op0 = model->addOperand(&type1); |
| auto op1 = model->addOperand(&type3); |
| // Phase 2, operations |
| static int32_t b4_init[] = {2}; |
| model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); |
| static int32_t b5_init[] = {2}; |
| model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); |
| static int32_t b6_init[] = {2}; |
| model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); |
| static int32_t b7_init[] = {0}; |
| model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); |
| static uint8_t op0_init[] = {1, 1, 1, 1}; |
| model->setOperandValue(op0, op0_init, sizeof(uint8_t) * 4); |
| static int32_t op1_init[] = {0}; |
| model->setOperandValue(op1, op1_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {op2}, |
| {op3}); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |