code: def test_addmm_symbolic_scalar(self):
      def fn(m1, m2):
          bias = m1.size(0)
          return (
              torch.add(bias, torch.mm(m1, m2)),
              torch.mm(m1, m2) + bias,
          )
  
      m1 = torch.randn(16, 16, device="cuda")
      m2 = torch.randn(16, 16, device="cuda")
  
      counters.clear()
      expect = fn(m1, m2)
      actual = torch.compile(fn, dynamic=True)(m1, m2)
      self.assertEqual(expect, actual)
      self.assertEqual(counters["inductor"]["pattern_matcher_count"], 0)
  
imports: import copy
  import unittest
  import torch
  import torch._dynamo.config
  import torch._inductor.config
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import count_calls, counters
  from torch._higher_order_ops.out_dtype import out_dtype
  from torch._inductor.fx_passes import joint_graph
  from torch._inductor.fx_passes.serialized_patterns.central_index import get_serialized_pattern
  from torch._inductor.pattern_matcher import _TargetExpr, Arg, CallFunction, gen_pattern, KeywordArg, Match, PatternExpr, PatternMatcherPass, PatternPrettyPrinter, register_graph_pattern, stable_topological_sort
  from torch._inductor.utils import run_and_get_code
  from torch._inductor.virtualized import V
  from torch.testing import FileCheck
  from torch.testing._internal.common_cuda import SM80OrLater
  from torch.testing._internal.common_utils import IS_LINUX, skipIfRocm
  from torch.testing._internal.inductor_utils import HAS_CUDA
label_desc: Use image node_id 17 for calling the TestPatternMatcher obj's underlying member method code with example usage: obj.test_addmm_symbolic_scalar() and returns: torch,  unknown