code: def _post_forward_hook(self, module, input, output):
      if self.use_cuda_events:
          self.timers(INFERENCE_MODEL_TIMER).stop()
          elapsed_time = self.timers(INFERENCE_MODEL_TIMER).elapsed(
              reset=True
          )
      else:
          torch.cuda.synchronize()
          self._end = time.time()
          elapsed_time = self._end - self._start
      self._model_times.append(elapsed_time)
  
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 6 for calling the InferenceEngine obj's underlying member method code with example usage: obj._post_forward_hook(module, input, output) without return types