content: import logging
  
  import torch
  from torch_tensorrt.dynamo._settings import CompilationSettings
  from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
      clean_up_graph_after_modifications,
      get_tensor_placeholders,
  )
  
  logger = logging.getLogger(__name__)
  
  
  def repair_input_as_output(
      gm: torch.fx.GraphModule, settings: CompilationSettings
  ) -> torch.fx.GraphModule:
      """Repair scenarios where inputs are also outputs of the graph
  
      TRT does not allow such cases, so we insert a clone (identity) layer
      """
      modified_graph = False
  
      # Extract graph placeholder Tensors
      placeholders = get_tensor_placeholders(gm)
  
      for placeholder in placeholders:
          # If any placeholder has any users which are direct graph outputs
          if len(placeholder.users) >= 1 and any(
              user.op == "output" for user in placeholder.users
          ):
              modified_graph = True
  
              # Get direct graph outputs which are direct uses of placeholders
              direct_outputs = [user for user in placeholder.users if user.op == "output"]
  
              # Insert clone node for placeholder to ensure placeholder is not a direct output
              with gm.graph.inserting_after(placeholders[-1]):
                  cloned_placeholder = gm.graph.call_function(
                      torch.ops.aten.clone.default,
                      args=(placeholder,),
                  )
  
              # Replace placeholder as output with cloned version
              for output in direct_outputs:
                  output.replace_input_with(placeholder, cloned_placeholder)
  
      if modified_graph:
          gm = clean_up_graph_after_modifications(gm)
          logger.debug(f"Graph after repair_input_as_output:\n{gm.graph}")
  
      return gm
  