| // clang-format off | |
| // Generated file (from: pad.mod.py). Do not edit | |
| void CreateModel(Model *model) { | |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); | |
| OperandType type1(Type::TENSOR_INT32, {4, 2}); | |
| OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); | |
| // Phase 1, operands | |
| auto op1 = model->addOperand(&type0); | |
| auto op2 = model->addOperand(&type1); | |
| auto op3 = model->addOperand(&type2); | |
| // Phase 2, operations | |
| static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0}; | |
| model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); | |
| model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); | |
| // Phase 3, inputs and outputs | |
| model->identifyInputsAndOutputs( | |
| {op1}, | |
| {op3}); | |
| assert(model->isValid()); | |
| } | |
| inline bool is_ignored(int i) { | |
| static std::set<int> ignore = {}; | |
| return ignore.find(i) != ignore.end(); | |
| } | |
| void CreateModel_dynamic_output_shape(Model *model) { | |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); | |
| OperandType type1(Type::TENSOR_INT32, {4, 2}); | |
| OperandType type3(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); | |
| // Phase 1, operands | |
| auto op1 = model->addOperand(&type0); | |
| auto op2 = model->addOperand(&type1); | |
| auto op3 = model->addOperand(&type3); | |
| // Phase 2, operations | |
| static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0}; | |
| model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); | |
| model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); | |
| // Phase 3, inputs and outputs | |
| model->identifyInputsAndOutputs( | |
| {op1}, | |
| {op3}); | |
| assert(model->isValid()); | |
| } | |
| inline bool is_ignored_dynamic_output_shape(int i) { | |
| static std::set<int> ignore = {}; | |
| return ignore.find(i) != ignore.end(); | |
| } | |