code: def remove_dropout(model: nn.Module) -> nn.Module:
      """
      Removes all dropout layers from the module.
      """
      fx_model = fx.symbolic_trace(model)
  
      class DropoutRemover(torch.fx.Transformer):
          def call_module(
              self,
              target: Target,
              args: Tuple[Argument, ...],
              kwargs: Dict[str, Any],
          ) -> Any:
              if isinstance(self.submodules[target], nn.Dropout):
                  assert len(args) == 1
                  return args[0]
              else:
                  return super().call_module(target, args, kwargs)
  
      return DropoutRemover(fx_model).transform()
  
imports: import torch.fx
  from torch.fx.node import Argument, Target
  from torch.nn.utils.fusion import fuse_conv_bn_eval
  from typing import Type, Dict, Any, Tuple, Iterable, Optional, List, cast
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.fx.passes.shape_prop import ShapeProp
  import copy
  from collections import defaultdict
  import torch.utils.mkldnn
  import operator
  import time
  import logging
  from enum import Enum
label_desc: Use image node_id 5 for calling a global function with example usage: remove_dropout(model) and returns: DropoutRemover, args, super