| // clang-format off |
| // Generated file (from: concat_mixed_quant.mod.py). Do not edit |
| void CreateModel_quant8(Model *model) { |
| OperandType type2(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.084f, 127); |
| OperandType type4(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.05f, 0); |
| OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.089f, 123); |
| OperandType type6(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.029f, 0); |
| OperandType type7(Type::TENSOR_QUANT8_ASYMM, {2, 1, 8}, 0.1f, 127); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type3); |
| auto input1 = model->addOperand(&type4); |
| auto input2 = model->addOperand(&type5); |
| auto input3 = model->addOperand(&type6); |
| auto param = model->addOperand(&type2); |
| auto output0 = model->addOperand(&type7); |
| // Phase 2, operations |
| static int32_t param_init[] = {2}; |
| model->setOperandValue(param, param_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_CONCATENATION, {input0, input1, input2, input3, param}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, input1, input2, input3}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_quant8(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| void CreateModel_quant8_2(Model *model) { |
| OperandType type2(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.084f, 127); |
| OperandType type4(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.05f, 0); |
| OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.089f, 123); |
| OperandType type6(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.029f, 0); |
| OperandType type8(Type::TENSOR_QUANT8_ASYMM, {2, 1, 8}, 0.0078125f, 127); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type3); |
| auto input1 = model->addOperand(&type4); |
| auto input2 = model->addOperand(&type5); |
| auto input3 = model->addOperand(&type6); |
| auto param = model->addOperand(&type2); |
| auto output0 = model->addOperand(&type8); |
| // Phase 2, operations |
| static int32_t param_init[] = {2}; |
| model->setOperandValue(param, param_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_CONCATENATION, {input0, input1, input2, input3, param}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, input1, input2, input3}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_quant8_2(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |