code: def profile_model_time(self, use_cuda_events=True):
      if (
          not self.model_profile_enabled
          and not self._config.enable_cuda_graph
      ):
          self.module.register_forward_pre_hook(self._pre_forward_hook)
          self.module.register_forward_hook(self._post_forward_hook)
      self.model_profile_enabled = True
      self.use_cuda_events = use_cuda_events
      if self.use_cuda_events:
          self.timers = SynchronizedWallClockTimer()
  
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 2 for calling the InferenceEngine obj's underlying member method code with example usage: obj.profile_model_time(use_cuda_events) without return types