code: def _get_target(device) -> str:
      if device.type is DeviceType.GPU:
          return str(tvm.target.cuda())
      else:
          return "llvm"
  
imports: import abc
  import os
  import uuid
  from abc import ABC
  from typing import Any, Tuple, Dict, Union
  from nebullvm.config import AUTO_TVM_PARAMS, AUTO_TVM_TUNING_OPTION
  from nebullvm.core.models import QuantizationType, ModelParams, DeviceType, Device
  from nebullvm.operations.optimizations.compilers.base import Compiler
  from nebullvm.operations.optimizations.compilers.quantizations.tvm import TVMCalibrator, quantize_apache_tvm
  from nebullvm.operations.optimizations.compilers.quantizations.utils import check_quantization
  from nebullvm.optional_modules.onnx import onnx
  from nebullvm.optional_modules.torch import Module, torch
  from nebullvm.optional_modules.tvm import tvm, IRModule, NDArray, XGBTuner, autotvm, relay, ExecutorFactoryModule
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.onnx import get_input_names
  from nebullvm.tools.pytorch import create_model_inputs_torch
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 7 for calling the ApacheTVMCompiler obj's underlying member method code with example usage: obj._get_target(device) and returns: str, str