code: def __init__(
      self,
      conv_class,
      bn_class,
      use_bias,
      in_channels,
      out_channels,
      device,
      **kwargs,
  ):
      super().__init__()
      self.conv = conv_class(
          in_channels, out_channels, bias=use_bias, **kwargs
      ).to(device)
      self.bn = bn_class(out_channels).to(device)
  
imports: import copy
  import importlib
  import itertools
  import os
  import sys
  import unittest
  import torch
  from torch import nn
  from torch._dynamo.test_case import TestCase
  from torch._dynamo.utils import counters
  from torch._inductor import config
  from torch.testing._internal.common_utils import IS_CI, IS_WINDOWS, TEST_WITH_ASAN
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
  from inductor.test_torchinductor import copy_tests
label_desc: Use image node_id 1 to create a new ConvOp object from inherited base classes: nn with example: obj = ConvOp(conv_class, bn_class, use_bias, in_channels, out_channels, device)