code: def test_neg_fc_relu(data_shape, use_bias, flatten):
      # fc + relu can't be fusion case
      # eg.1
      # fc -----------> relu
      #  |
      #  |
      #  ---------------> [custom op]
      class NegFCReLU(nn.HybridBlock):
          def __init__(self, use_bias, flatten, **kwargs):
              super(NegFCReLU, self).__init__(**kwargs)
              self.fc = nn.Dense(
                  units=64, use_bias=use_bias, flatten=flatten
              )
              self.act1 = nn.Activation("relu")
              self.act2 = nn.Activation("sigmoid")
              self.tail_neg = TailNegBlock()
  
          def forward(self, x):
              fc_out = self.fc(x)
              return self.tail_neg(self.act1(fc_out), self.act2(fc_out))
  
      attrs, excluded_attrs = [], []
      net = NegFCReLU(use_bias, flatten)
      check_neg_fusion(
          net, attrs, excluded_attrs, data_shape, name="fc"
      )
  
imports: import mxnet
  import pytest
  from subgraph_common import check_fusion, check_neg_fusion, check_neg_fusion_quantized, check_quantize
  from subgraph_common import CustomNormalInit, DATA_SHAPE, TailNegBlock
  from mxnet.contrib import quantization
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_almost_equal_with_err
label_desc: Use image node_id 6 for calling a global function with example usage: test_neg_fc_relu(data_shape, use_bias, flatten) and returns: self