| // clang-format off |
| // Generated file (from: tile_3.mod.py). Do not edit |
| void CreateModel(Model *model) { |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3}); |
| OperandType type1(Type::TENSOR_INT32, {3}); |
| OperandType type2(Type::TENSOR_FLOAT32, {2, 6, 3}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto multipliers = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type2); |
| // Phase 2, operations |
| model->addOperation(ANEURALNETWORKS_TILE, {input0, multipliers}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, multipliers}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| void CreateModel_relaxed(Model *model) { |
| OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3}); |
| OperandType type1(Type::TENSOR_INT32, {3}); |
| OperandType type2(Type::TENSOR_FLOAT32, {2, 6, 3}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type0); |
| auto multipliers = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type2); |
| // Phase 2, operations |
| model->addOperation(ANEURALNETWORKS_TILE, {input0, multipliers}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, multipliers}, |
| {output0}); |
| // Phase 4: set relaxed execution |
| model->relaxComputationFloat32toFloat16(true); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_relaxed(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| void CreateModel_float16(Model *model) { |
| OperandType type1(Type::TENSOR_INT32, {3}); |
| OperandType type3(Type::TENSOR_FLOAT16, {1, 2, 3}); |
| OperandType type4(Type::TENSOR_FLOAT16, {2, 6, 3}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type3); |
| auto multipliers = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type4); |
| // Phase 2, operations |
| model->addOperation(ANEURALNETWORKS_TILE, {input0, multipliers}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, multipliers}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_float16(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| void CreateModel_quant8(Model *model) { |
| OperandType type1(Type::TENSOR_INT32, {3}); |
| OperandType type5(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3}, 0.5f, 127); |
| OperandType type6(Type::TENSOR_QUANT8_ASYMM, {2, 6, 3}, 0.5f, 127); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type5); |
| auto multipliers = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type6); |
| // Phase 2, operations |
| model->addOperation(ANEURALNETWORKS_TILE, {input0, multipliers}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, multipliers}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_quant8(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| void CreateModel_int32(Model *model) { |
| OperandType type1(Type::TENSOR_INT32, {3}); |
| OperandType type7(Type::TENSOR_INT32, {1, 2, 3}); |
| OperandType type8(Type::TENSOR_INT32, {2, 6, 3}); |
| // Phase 1, operands |
| auto input0 = model->addOperand(&type7); |
| auto multipliers = model->addOperand(&type1); |
| auto output0 = model->addOperand(&type8); |
| // Phase 2, operations |
| model->addOperation(ANEURALNETWORKS_TILE, {input0, multipliers}, {output0}); |
| // Phase 3, inputs and outputs |
| model->identifyInputsAndOutputs( |
| {input0, multipliers}, |
| {output0}); |
| assert(model->isValid()); |
| } |
| |
| inline bool is_ignored_int32(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |