| // Generated from split_int32_1.mod.py |
| // DO NOT EDIT |
| // clang-format off |
| #include "TestGenerated.h" |
| |
| namespace generated_tests::split_int32_1 { |
| |
| void CreateModel(Model *model) { |
| OperandType type0(Type::TENSOR_INT32, {6}); |
| OperandType type1(Type::INT32, {}); |
| OperandType type2(Type::TENSOR_INT32, {2}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto axis = model->addOperand(&type1); |
| auto num_splits = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type2); |
| auto output1 = model->addOperand(&type2); |
| auto output2 = model->addOperand(&type2); |
| // Phase 2, operations |
| static int32_t axis_init[] = {0}; |
| model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); |
| static int32_t num_splits_init[] = {3}; |
| model->setOperandValue(num_splits, num_splits_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_SPLIT, {input0, axis, num_splits}, {output0, output1, output2}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0}, |
| {output0, output1, output2}); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace generated_tests::split_int32_1 |
| namespace generated_tests::split_int32_1 { |
| |
| void CreateModel_dynamic_output_shape(Model *model) { |
| OperandType type0(Type::TENSOR_INT32, {6}); |
| OperandType type1(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_INT32, {0}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto axis = model->addOperand(&type1); |
| auto num_splits = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type3); |
| auto output1 = model->addOperand(&type3); |
| auto output2 = model->addOperand(&type3); |
| // Phase 2, operations |
| static int32_t axis_init[] = {0}; |
| model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); |
| static int32_t num_splits_init[] = {3}; |
| model->setOperandValue(num_splits, num_splits_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_SPLIT, {input0, axis, num_splits}, {output0, output1, output2}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0}, |
| {output0, output1, output2}); |
| 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::split_int32_1 |
| namespace generated_tests::split_int32_1 { |
| |
| void CreateModel_relaxed(Model *model) { |
| OperandType type0(Type::TENSOR_INT32, {6}); |
| OperandType type1(Type::INT32, {}); |
| OperandType type2(Type::TENSOR_INT32, {2}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto axis = model->addOperand(&type1); |
| auto num_splits = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type2); |
| auto output1 = model->addOperand(&type2); |
| auto output2 = model->addOperand(&type2); |
| // Phase 2, operations |
| static int32_t axis_init[] = {0}; |
| model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); |
| static int32_t num_splits_init[] = {3}; |
| model->setOperandValue(num_splits, num_splits_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_SPLIT, {input0, axis, num_splits}, {output0, output1, output2}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0}, |
| {output0, output1, output2}); |
| // Phase 4: set relaxed execution |
| model->relaxComputationFloat32toFloat16(true); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored_relaxed(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace generated_tests::split_int32_1 |
| namespace generated_tests::split_int32_1 { |
| |
| void CreateModel_relaxed_dynamic_output_shape(Model *model) { |
| OperandType type0(Type::TENSOR_INT32, {6}); |
| OperandType type1(Type::INT32, {}); |
| OperandType type3(Type::TENSOR_INT32, {0}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto axis = model->addOperand(&type1); |
| auto num_splits = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type3); |
| auto output1 = model->addOperand(&type3); |
| auto output2 = model->addOperand(&type3); |
| // Phase 2, operations |
| static int32_t axis_init[] = {0}; |
| model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); |
| static int32_t num_splits_init[] = {3}; |
| model->setOperandValue(num_splits, num_splits_init, sizeof(int32_t) * 1); |
| model->addOperation(ANEURALNETWORKS_SPLIT, {input0, axis, num_splits}, {output0, output1, output2}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0}, |
| {output0, output1, output2}); |
| // Phase 4: set relaxed execution |
| model->relaxComputationFloat32toFloat16(true); |
| assert(model->isValid()); |
| } |
| |
| bool is_ignored_relaxed_dynamic_output_shape(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace generated_tests::split_int32_1 |