code: def test_convolution1(self):
      @torch.compile
      def foo(x, w, b):
          return aten.convolution(
              x + 1,
              w,
              b,
              stride=(2, 3),
              padding=(4, 5),
              dilation=(1, 1),
              transposed=False,
              output_padding=(0, 0),
              groups=1,
          )
  
      foo(
          torch.randn(2, 33, 34, 41, device="cuda"),
          torch.randn(34, 33, 3, 3, device="cuda"),
          torch.randn(34, device="cuda"),
      )
      # Autotuning checks correctness of each version
      self.assertEqual(
          counters["inductor"]["select_algorithm_autotune"], 1
      )
  
imports: import functools
  from unittest.mock import patch
  import torch
  import torch._dynamo.config
  import torch._inductor.config
  import torch._inductor.select_algorithm
  import torch.nn.functional
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.testing import expectedFailureDynamicWrapper
  from torch._dynamo.utils import counters
  from torch._inductor.autotune_process import TritonBenchmarkRequest
  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 14 for calling the TestSelectAlgorithm obj's underlying member method code with example usage: obj.test_convolution1() and returns: aten