// clang-format off // Generated file (from: mean_implicit.mod.py). Do not edit // clang-format off // Generated file (from: mean_implicit.mod.py). Do not edit // clang-format off // Generated file (from: mean_implicit.mod.py). Do not edit #include "../../TestGenerated.h" namespace mean_implicit { // Generated mean_implicit test #include "-" // Generated model constructor #include "-" } // namespace mean_implicit void CreateModel(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); OperandType type2(Type::TENSOR_FLOAT32, {2, 1}); OperandType type3(Type::TENSOR_FLOAT32, {1}); OperandType type4(Type::TENSOR_INT32, {1}); OperandType type5(Type::INT32, {}); OperandType type6(Type::TENSOR_INT32, {2}); // Phase 1, operands auto i0 = model->addOperand(&type0); auto param = model->addOperand(&type4); auto param1 = model->addOperand(&type5); auto o1 = model->addOperand(&type1); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_MEAN, {i0, param, param1}, {o1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {i0}, {o1}); assert(model->isValid()); } bool is_ignored(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } std::vector examples = { // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {4.0f, 6.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-1.0f, -2.0f, -3.0f, -4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-4.0f, -6.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example }; TEST_F(GeneratedTests, mean_implicit) { execute(mean_implicit::CreateModel, mean_implicit::is_ignored, mean_implicit::examples); } void CreateModel_2(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); OperandType type2(Type::TENSOR_FLOAT32, {2, 1}); OperandType type3(Type::TENSOR_FLOAT32, {1}); OperandType type4(Type::TENSOR_INT32, {1}); OperandType type5(Type::INT32, {}); OperandType type6(Type::TENSOR_INT32, {2}); // Phase 1, operands auto i0 = model->addOperand(&type0); auto param2 = model->addOperand(&type4); auto param3 = model->addOperand(&type5); auto o2 = model->addOperand(&type2); // Phase 2, operations static int32_t param2_init[] = {1}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); static int32_t param3_init[] = {1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_MEAN, {i0, param2, param3}, {o2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {i0}, {o2}); assert(model->isValid()); } bool is_ignored_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } std::vector examples_2 = { // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {3.0f, 7.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-1.0f, -2.0f, -3.0f, -4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-3.0f, -7.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example }; TEST_F(GeneratedTests, mean_implicit_2) { execute(mean_implicit::CreateModel_2, mean_implicit::is_ignored_2, mean_implicit::examples_2); } void CreateModel_3(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); OperandType type2(Type::TENSOR_FLOAT32, {2, 1}); OperandType type3(Type::TENSOR_FLOAT32, {1}); OperandType type4(Type::TENSOR_INT32, {1}); OperandType type5(Type::INT32, {}); OperandType type6(Type::TENSOR_INT32, {2}); // Phase 1, operands auto i0 = model->addOperand(&type0); auto param4 = model->addOperand(&type6); auto param5 = model->addOperand(&type5); auto o3 = model->addOperand(&type3); // Phase 2, operations static int32_t param4_init[] = {0, 1}; model->setOperandValue(param4, param4_init, sizeof(int32_t) * 2); static int32_t param5_init[] = {0}; model->setOperandValue(param5, param5_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_MEAN, {i0, param4, param5}, {o3}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {i0}, {o3}); assert(model->isValid()); } bool is_ignored_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } std::vector examples_3 = { // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {10.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example // Begin of an example { //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-1.0f, -2.0f, -3.0f, -4.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} }, //Output(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map {{0, {-10.0f}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map {} } }, // End of an example }; TEST_F(GeneratedTests, mean_implicit_3) { execute(mean_implicit::CreateModel_3, mean_implicit::is_ignored_3, mean_implicit::examples_3); } #include "../generated/tests/mean_implicit.mod.py.cpp"