code: def _choose_module_key(self, sd):
      assert not (
          "module" in sd and "model" in sd
      ), "checkpoint has both 'model' and 'module' keys, not sure how to proceed"
      assert (
          "module" in sd or "model" in sd
      ), "checkpoint contains neither 'model' or 'module' keys, not sure how to proceed"
      if "module" in sd:
          return "module"
      elif "model" in sd:
          return "model"
  
imports: import torch
  import time
  import os
  from deepspeed import comm
  from deepspeed.utils.logging import log_dist
  from torch.nn.modules import Module
  from packaging import version
  from deepspeed.runtime.checkpoint_engine.torch_checkpoint_engine import TorchCheckpointEngine
  from deepspeed.utils.timer import SynchronizedWallClockTimer
  from ..runtime.state_dict_factory import SDLoaderFactory
  from ..runtime.weight_quantizer import WeightQuantization
  from ..module_inject.replace_module import replace_transformer_layer, generic_injection
  from ..comm.comm import init_distributed
  from ..pipe import PipelineModule
  from ..moe.utils import has_moe_layers
  from ..runtime.zero import GatheredParameters
  from ..module_inject import LinearAllreduce, LinearLayer, Normalize, ReplaceWithTensorSlicing
  from ..module_inject.replace_policy import DSPolicy
  from torch import nn
label_desc: Use image node_id 16 for calling the InferenceEngine obj's underlying member method code with example usage: obj._choose_module_key(sd) and returns: str, str