code: def test_neg_conv_bn(data_shape):
      # conv + bn can't be fusion case
      # eg.1
      # conv --------- > bn
      #  |
      #  |
      #  -------------> [custom op]
      class NegConvBN(nn.HybridBlock):
          def __init__(self, **kwargs):
              super(NegConvBN, self).__init__(**kwargs)
              self.conv1 = nn.Conv2D(
                  channels=64,
                  kernel_size=(3, 3),
                  strides=(1, 1),
                  use_bias=False,
              )
              self.bn1 = nn.BatchNorm()
              self.pool = nn.AvgPool2D(pool_size=(4, 4))
              self.tailneg = TailNegBlock()
  
          def forward(self, x):
              conv = self.conv1(x)
              bn = self.bn1(conv)
              pool = self.pool(conv)
  
              return self.tailneg(bn, pool)
  
      attrs = []
      excluded_attrs = []
      net = NegConvBN()
      check_neg_fusion(net, attrs, excluded_attrs, data_shape)
  
imports: import copy
  import mxnet
  import pytest
  from subgraph_common import check_fusion, check_neg_fusion, check_quantize
  from subgraph_common import CustomNormalInit, DATA_SHAPE, RELU6, TailNegBlock
  from subgraph_common import DATA_SHAPE, SG_PASS_NAME, QUANTIZE_SG_PASS_NAME
  from mxnet.contrib import quantization
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_almost_equal, assert_almost_equal_with_err
label_desc: Use image node_id 20 for calling a global function with example usage: test_neg_conv_bn(data_shape) and returns: self