| // clang-format off |
| // Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit |
| void CreateModel(Model *model) { |
| OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.5f, 0); |
| OperandType type1(Type::TENSOR_INT32, {2}, 0.25f, 0); |
| OperandType type2(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 2}, 1.0f, 0); |
| // Phase 1, operands |
| auto op1 = model->addOperand(&type0); |
| auto op2 = model->addOperand(&type0); |
| auto op3 = model->addOperand(&type1); |
| auto pad0 = model->addOperand(&type2); |
| auto stride = model->addOperand(&type2); |
| auto channelMultiplier = model->addOperand(&type2); |
| auto act = model->addOperand(&type2); |
| auto op4 = model->addOperand(&type3); |
| // Phase 2, operations |
| static uint8_t op2_init[] = {2, 4, 2, 0, 2, 2, 2, 0}; |
| model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 8); |
| static int32_t op3_init[] = {0, 0}; |
| model->setOperandValue(op3, op3_init, sizeof(int32_t) * 2); |
| static int32_t pad0_init[] = {0}; |
| model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); |
| static int32_t stride_init[] = {1}; |
| model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); |
| static int32_t channelMultiplier_init[] = {1}; |
| model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1); |
| static int32_t act_init[] = {0}; |
| model->setOperandValue(act, act_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {op1}, |
| {op4}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |