code: def transform(self, graph_module):
      for node in graph_module.graph.nodes:
          if node.op == "call_function" and node.target == operator.mul:
              node.target = operator.add
      return graph_module
  
imports: import operator
  import unittest
  import torch
  from parameterized import parameterized
  from transformers import AutoModel, AutoModelForImageClassification, AutoTokenizer, BertModel
  from transformers.models.bert.modeling_bert import BertSelfAttention
  from transformers.utils.fx import symbolic_trace
  from optimum.fx.optimization import ChangeTrueDivToMulByInverse, FuseBatchNorm1dInLinear, FuseBatchNorm2dInConv2d, FuseBiasInLinear, MergeLinears, ReversibleTransformation, Transformation, compose
  from optimum.fx.utils import are_fx_features_available
label_desc: Use image node_id 2 for calling the DummyTransformation obj's underlying member method code with example usage: obj.transform(graph_module) and returns: graph_module