code: def test_symint_pattern_matching(self):
      import torch._inductor.config as config
      from torch._inductor.pattern_matcher import (
          fwd_only,
          PatternMatcherPass,
          register_replacement,
      )
  
      saved_graph = None
  
      class _CustomPass(PatternMatcherPass):
          def __init__(self):
              super().__init__()
  
          def __call__(self, g: torch.fx.graph.Graph):
              self.apply(g)
              nonlocal saved_graph
              saved_graph = g
  
      with config.patch(
          # leave custom pass only in post_grad_passes()
          pattern_matcher=False,
          # define pattern match as custom post grad opt pass
          post_grad_custom_pre_pass=None,
          post_grad_custom_post_pass=_CustomPass(),
      ):
  
          def add(x, y):
              return x + y
  
          # testing that
          def sym_minus(x, y):
              return (x - (-y.size(0))) - (y * -1) - y.size(0)
  
          device = "cpu"
          my_args = [
              torch.empty([8, 1], device=device),
              torch.empty([10], device=device),
          ]
  
          invoked = False
  
          def extra_check(match):
              nonlocal invoked
              invoked = True
              return True
  
          register_replacement(
              add,
              sym_minus,
              my_args,
              fwd_only,
              [config.post_grad_custom_post_pass],
              extra_check=extra_check,
          )
  
          @torch.compile(dynamic=True)
          def foo(x, y):
              return x + y
  
          x = torch.rand([8, 1])
          y = torch.rand([10])
  
          self.assertEqual(foo(x, y), x + y)
  
          self.assertTrue(invoked)
          # we trace out the y.sym_size in replacement
          FileCheck().check("sym_size_int").check_same(
              "num_users=2"
          ).check_same("target=torch.ops.aten.sym_size").run(
              str(saved_graph)
          )
  
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 26 for calling the TestPatternMatcher obj's underlying member method code with example usage: obj.test_symint_pattern_matching() and returns: unknown, unknown, True, unknown