| // Generated file (from: averpoolfloat.mod.py). Do not edit |
| void CreateModel(Model *model) { |
| OperandType type1(Type::INT32, {}); |
| OperandType type0(Type::TENSOR_QUANT8_ASYMM, 0.0f, 127.5f, {1, 2, 2, 1}); |
| // Phase 1, operands |
| auto op1 = model->addOperand(&type0); |
| auto cons1 = model->addOperand(&type1); |
| auto act = model->addOperand(&type1); |
| auto op3 = model->addOperand(&type0); |
| // Phase 2, operations |
| static int32_t cons1_init[] = {1}; |
| model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1); |
| static int32_t act_init[] = {0}; |
| model->setOperandValue(act, act_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_AVERAGE_POOL, {op1, cons1, cons1, cons1, cons1, cons1, act}, {op3}); |
| // Phase 3, inputs and outputs |
| model->setInputsAndOutputs( |
| {op1}, |
| {op3}); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| // Generated file (from: averpoolfloat.mod.py). Do not edit |
| // Begin of an example |
| { |
| //Input(s) |
| { // See tools/test_generator/include/TestHarness.h:MixedTyped |
| // int -> FLOAT32 map |
| {}, |
| // int -> INT32 map |
| {}, |
| // int -> QUANT8_ASYMM map |
| {{0, {1, 2, 3, 4}}} |
| }, |
| //Output(s) |
| { // See tools/test_generator/include/TestHarness.h:MixedTyped |
| // int -> FLOAT32 map |
| {}, |
| // int -> INT32 map |
| {}, |
| // int -> QUANT8_ASYMM map |
| {{0, {1, 2, 3, 4}}} |
| } |
| }, // End of an example |