docstr: Given a call_module node, returns the module corresponding to this module call
docstr_tok: ["Given","a","call_module","node",",","returns","the","module","corresponding","to","this","module","call"]
code: def get_module(self, node: torch.fx.Node) -> Optional[nn.Module]:
      """Given a call_module node, returns the module corresponding to this module call"""
      if node.op != "call_module":
          return None
      module = self.tracer.root
      for t in cast(str, node.target).split("."):
          module = getattr(module, t)
      return module
  
file_path: fairscale/fairscale/experimental/nn/distributed_pipeline/trace.py
imports: import inspect
  import operator
  from typing import Dict, List, Optional, Tuple, cast
  from torch.distributed.nn import RemoteModule
  import torch.fx
  import torch.nn
  from .None import PipelineModulesGraph
label_desc: Use image node_id 2 for calling the GraphCreator obj's underlying member method code with example usage: obj.get_module(node) and returns: module, None