code: def test_subgraph_rewriter_nodes_with_kwargs(self):
      class M(torch.nn.Module):
          def __init__(self) -> None:
              super().__init__()
              self.w0 = torch.nn.Parameter(torch.empty([128, 128]))
              self.b0 = torch.nn.Parameter(torch.empty([128]))
  
          def forward(self, in0):
              lin_res = torch.nn.functional.linear(
                  in0, self.w0, bias=self.b0
              )
              mul_res = in0 * lin_res
              sum_res = mul_res + in0
              return sum_res
  
      def pattern(a, b, bias):
          lin_res = torch.nn.functional.linear(a, b, bias=bias)
          mul_res = a * lin_res
          return lin_res, mul_res
  
      def replacement(a, b, bias):
          lin_res, mul_res = wrapped_gemm_bias_mul(a, b, bias)
          return lin_res, mul_res
  
      traced = symbolic_trace(M())
      matches = subgraph_rewriter.replace_pattern(
          traced, pattern, replacement
      )
  
      self.assertEqual(len(matches), 1)
  
      found_repalcement_node = False
      for node in traced.graph.nodes:
          if node.target == wrapped_gemm_bias_mul:
              found_repalcement_node = True
              break
  
      self.assertTrue(found_repalcement_node)
  
imports: import os
  import sys
  import torch
  from torch.fx import symbolic_trace, subgraph_rewriter
  from torch.fx.annotate import annotate
  from torch.fx.experimental.rewriter import RewritingTracer
  from torch.testing._internal.jit_utils import JitTestCase
label_desc: Use image node_id 21 for calling the TestSubgraphRewriter obj's underlying member method code with example usage: obj.test_subgraph_rewriter_nodes_with_kwargs() and returns: lin_res,  mul_res, lin_res,  mul_res, sum_res