// clang-format off // Generated file (from: expand_dims.mod.py). Do not edit void CreateModel(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param = model->addOperand(&type4); auto output = model->addOperand(&type1); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_relaxed(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param = model->addOperand(&type4); auto output = model->addOperand(&type1); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_relaxed(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_quant8(Model *model) { OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); OperandType type6(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param = model->addOperand(&type4); auto output = model->addOperand(&type6); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_quant8(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_int32(Model *model) { OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); OperandType type8(Type::TENSOR_INT32, {1, 2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param = model->addOperand(&type4); auto output = model->addOperand(&type8); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_int32(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_float16(Model *model) { OperandType type10(Type::TENSOR_FLOAT16, {1, 2, 2}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param = model->addOperand(&type4); auto output = model->addOperand(&type10); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_float16(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param = model->addOperand(&type4); auto output = model->addOperand(&type11); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_relaxed(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param = model->addOperand(&type4); auto output = model->addOperand(&type11); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_relaxed(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_quant8(Model *model) { OperandType type12(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param = model->addOperand(&type4); auto output = model->addOperand(&type12); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_quant8(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_int32(Model *model) { OperandType type13(Type::TENSOR_INT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param = model->addOperand(&type4); auto output = model->addOperand(&type13); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_int32(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_float16(Model *model) { OperandType type14(Type::TENSOR_FLOAT16, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param = model->addOperand(&type4); auto output = model->addOperand(&type14); // Phase 2, operations static int32_t param_init[] = {0}; model->setOperandValue(param, param_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param}, {output}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_float16(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_2(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type2(Type::TENSOR_FLOAT32, {2, 1, 2}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type2); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_relaxed_2(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type2(Type::TENSOR_FLOAT32, {2, 1, 2}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type2); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_relaxed_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_quant8_2(Model *model) { OperandType type15(Type::TENSOR_QUANT8_ASYMM, {2, 1, 2}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type15); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_quant8_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_int32_2(Model *model) { OperandType type16(Type::TENSOR_INT32, {2, 1, 2}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type16); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_int32_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_float16_2(Model *model) { OperandType type17(Type::TENSOR_FLOAT16, {2, 1, 2}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type17); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_float16_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_2(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type11); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_relaxed_2(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type11); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_relaxed_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_quant8_2(Model *model) { OperandType type12(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type12); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_quant8_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_int32_2(Model *model) { OperandType type13(Type::TENSOR_INT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type13); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_int32_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_float16_2(Model *model) { OperandType type14(Type::TENSOR_FLOAT16, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param1 = model->addOperand(&type4); auto output1 = model->addOperand(&type14); // Phase 2, operations static int32_t param1_init[] = {1}; model->setOperandValue(param1, param1_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param1}, {output1}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output1}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_float16_2(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_3(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type3(Type::TENSOR_FLOAT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type3); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_relaxed_3(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type3(Type::TENSOR_FLOAT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type3); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_relaxed_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_quant8_3(Model *model) { OperandType type18(Type::TENSOR_QUANT8_ASYMM, {2, 2, 1}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type18); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_quant8_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_int32_3(Model *model) { OperandType type19(Type::TENSOR_INT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type19); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_int32_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_float16_3(Model *model) { OperandType type20(Type::TENSOR_FLOAT16, {2, 2, 1}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type20); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_float16_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_3(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type11); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_relaxed_3(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type11); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_relaxed_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_quant8_3(Model *model) { OperandType type12(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type12); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_quant8_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_int32_3(Model *model) { OperandType type13(Type::TENSOR_INT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type13); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_int32_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_float16_3(Model *model) { OperandType type14(Type::TENSOR_FLOAT16, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param2 = model->addOperand(&type4); auto output2 = model->addOperand(&type14); // Phase 2, operations static int32_t param2_init[] = {2}; model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param2}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_float16_3(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_4(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type3(Type::TENSOR_FLOAT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type3); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_relaxed_4(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type3(Type::TENSOR_FLOAT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type3); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_relaxed_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_quant8_4(Model *model) { OperandType type18(Type::TENSOR_QUANT8_ASYMM, {2, 2, 1}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type18); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_quant8_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_int32_4(Model *model) { OperandType type19(Type::TENSOR_INT32, {2, 2, 1}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type19); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_int32_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_float16_4(Model *model) { OperandType type20(Type::TENSOR_FLOAT16, {2, 2, 1}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type20); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_float16_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_4(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type11); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_relaxed_4(Model *model) { OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); OperandType type11(Type::TENSOR_FLOAT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); // Phase 1, operands auto input0 = model->addOperand(&type0); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type11); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); // Phase 4: set relaxed execution model->relaxComputationFloat32toFloat16(true); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_relaxed_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_quant8_4(Model *model) { OperandType type12(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0}, 0.5f, 127); OperandType type4(Type::INT32, {}); OperandType type5(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 0.5f, 127); // Phase 1, operands auto input0 = model->addOperand(&type5); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type12); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_quant8_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_int32_4(Model *model) { OperandType type13(Type::TENSOR_INT32, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type7(Type::TENSOR_INT32, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type7); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type13); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_int32_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); } void CreateModel_dynamic_output_shape_float16_4(Model *model) { OperandType type14(Type::TENSOR_FLOAT16, {0, 0, 0}); OperandType type4(Type::INT32, {}); OperandType type9(Type::TENSOR_FLOAT16, {2, 2}); // Phase 1, operands auto input0 = model->addOperand(&type9); auto param3 = model->addOperand(&type4); auto output2 = model->addOperand(&type14); // Phase 2, operations static int32_t param3_init[] = {-1}; model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1); model->addOperation(ANEURALNETWORKS_EXPAND_DIMS, {input0, param3}, {output2}); // Phase 3, inputs and outputs model->identifyInputsAndOutputs( {input0}, {output2}); assert(model->isValid()); } inline bool is_ignored_dynamic_output_shape_float16_4(int i) { static std::set ignore = {}; return ignore.find(i) != ignore.end(); }