code: def test_bn2d_eltwise(self, dtype):
      class M(nn.Module):
          def __init__(self, eltwise_fn):
              super().__init__()
              self.eltwise = eltwise_fn
              self.bn = nn.BatchNorm2d(32)
  
          def forward(self, x):
              x = self.bn(x)
              x = self.eltwise(x)
              return x
  
      for eltwise in ["relu"]:
          eltwise_fn = get_eltwise_fn(eltwise)
          m = M(eltwise_fn).eval()
          x = torch.rand(1, 32, 28, 28)
          _, graph = self.checkTrace(m, [x], dtype)
          self.assertGraphContainsExactly(graph, LLGA_FUSION_GROUP, 1)
          self.assertFused(graph, ["aten::" + eltwise])
  
imports: import sys
  import torch
  import unittest
  import itertools
  import torch.nn
  from functools import wraps
  from concurrent import futures
  import torch.nn.functional
  import torch.fx.experimental.optimization
  from torch.testing._internal.jit_utils import JitTestCase
  from torch.testing._internal.common_utils import run_tests, TEST_SCIPY, IS_WINDOWS, IS_MACOS
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes
label_desc: Use image node_id 7 for calling the TestFusionPattern obj's underlying member method code with example usage: obj.test_bn2d_eltwise(dtype) and returns: x