code: def test_single_fc(data_shape, use_bias, flatten):
      class SingleFC(nn.HybridBlock):
          def __init__(self, use_bias, flatten, **kwargs):
              super(SingleFC, self).__init__(**kwargs)
              self.fc = nn.Dense(
                  units=64, use_bias=use_bias, flatten=flatten
              )
  
          def forward(self, x):
              return self.fc(x)
  
      attrs = {"fc": {}}
      net = SingleFC(use_bias, flatten)
      check_fusion(net, data_shape, attrs, check_quantization=flatten)
  
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 2 for calling a global function with example usage: test_single_fc(data_shape, use_bias, flatten) and returns: self