code: def test_mixed_mm_bad_cases(self):
      def fn(a, b):
          return torch.mm(a, b.to(a.dtype))
  
      args_list = [
          (
              torch.randn(8, 8, device="cuda", dtype=torch.float16),
              torch.randint(
                  -128, 127, (2, 8), dtype=torch.int8, device="cuda"
              ).t(),
          ),
          (
              torch.randn(8, 8, device="cuda", dtype=torch.bfloat16),
              torch.randint(
                  0, 255, (2, 8), dtype=torch.uint8, device="cuda"
              ).t(),
          ),
      ]
  
      for args in args_list:
          self._test_mixed_impl(fn, args, True, True)
  
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 8 for calling the TestPatternMatcher obj's underlying member method code with example usage: obj.test_mixed_mm_bad_cases() and returns: torch