class_docstr: A torch.fx graph transformation.
  
  It  must implement the [`~optimum.fx.optimization.ReversibleTransformation.transform`] method, and be used as a
  callable.
class_docstr_tok: ["A","torch.fx","graph","transformation",".","It","must","implement","the","[","`","~optimum.fx.optimization.ReversibleTransformation.transform","`","]","method",",","and","be","used","as","a","callable","."]
docstr: Marks a node as transformed by this transformation.
  
  Args:
      node (`torch.fx.Node`):
          The node to mark as transformed.
docstr_tok: ["Marks","a","node","as","transformed","by","this","transformation",".","Args",":","node","(","`","torch.fx.Node","`",")",":","The","node","to","mark","as","transformed","."]
code: def mark_as_transformed(self, node: "Node"):
      """
      Marks a node as transformed by this transformation.
  
      Args:
          node (`torch.fx.Node`):
              The node to mark as transformed.
      """
      node_transformations = getattr(node, "transformations", set())
      node_transformations.add(self.signature)
      node.transformations = node_transformations
  
imports: import collections
  import copy
  import functools
  import itertools
  import operator
  import warnings
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, List
  import torch
  from transformers.file_utils import add_end_docstrings
  from transformers.utils.fx import _gen_constructor_wrapper
label_desc: Use image node_id 4 for calling the Transformation obj's underlying member method code with example usage: obj.mark_as_transformed(node) without return types