code: def test_matmul_dropout(self, device):
      def fwd(a, b):
          x = a @ b
          x = torch.nn.functional.dropout(x, 0.1)
          return x
  
      def fn(a, b):
          x = fwd(a, b).sum()
          x.backward()
          return a.grad
  
      N = 128
      a = torch.randn(N, N, device=device, requires_grad=True)
      b = torch.randn(N, N, device=device)
  
      opt_fn = torch.compile(fn)
      reset_rng_state()
      ref = fn(a, b)
      reset_rng_state()
      act = opt_fn(a, b)
  
      if N <= 8:
          print(f"ref\n{ref}\nact\n{act}")
      torch.testing.assert_close(ref, act, atol=1e-1, rtol=1e-1)
  
imports: import os
  import unittest
  from typing import Callable, List, Optional
  import torch
  from torch import multiprocessing
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.testing import reset_rng_state
  from torch._dynamo.utils import counters
  from torch._inductor import config
  from torch._inductor.autotune_process import BenchmarkRequest, CUDA_VISIBLE_DEVICES, TuningProcessPool
  from torch._inductor.graph import GraphLowering
  from torch._inductor.ir import Buffer, FixedLayout
  from torch._inductor.kernel.mm_plus_mm import aten_mm_plus_mm
  from torch._inductor.select_algorithm import AlgorithmSelectorCache, ChoiceCaller, TritonTemplateCaller
  from torch._inductor.utils import run_and_get_code
  from torch._inductor.virtualized import V
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing import FileCheck
  from torch.testing._internal.common_cuda import SM75OrLater, SM90OrLater
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, skipIfRocm
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
label_desc: Use image node_id 26 for calling the TestMaxAutotune obj's underlying member method code with example usage: obj.test_matmul_dropout(device) and returns: x, a