| // Generated from mul.mod.py |
| // DO NOT EDIT |
| // clang-format off |
| #include "TestGenerated.h" |
| |
| namespace generated_tests::mul { |
| |
| void CreateModel(Model *model) { |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); |
| OperandType type1(Type::INT32, {}); |
| // Phase 1, operands |
| auto op1 = model->addOperand(&type0); |
| auto op2 = model->addOperand(&type0); |
| auto act = model->addOperand(&type1); |
| auto op3 = model->addOperand(&type0); |
| // Phase 2, operations |
| static int32_t act_init[] = {0}; |
| model->setOperandValue(act, act_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {op1, op2}, |
| {op3}); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace generated_tests::mul |
| namespace generated_tests::mul { |
| |
| void CreateModel_dynamic_output_shape(Model *model) { |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); |
| OperandType type1(Type::INT32, {}); |
| OperandType type2(Type::TENSOR_FLOAT32, {0, 0, 0, 0}); |
| // Phase 1, operands |
| auto op1 = model->addOperand(&type0); |
| auto op2 = model->addOperand(&type0); |
| auto act = model->addOperand(&type1); |
| auto op3 = model->addOperand(&type2); |
| // Phase 2, operations |
| static int32_t act_init[] = {0}; |
| model->setOperandValue(act, act_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {op1, op2}, |
| {op3}); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored_dynamic_output_shape(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace generated_tests::mul |