code: def test_fc_reshape(data_shape, use_bias, out_type, flatten, module):
      class FC_Reshape(nn.HybridBlock):
          def __init__(self, use_bias, flatten, **kwargs):
              super(FC_Reshape, self).__init__(**kwargs)
              self.fc = nn.Dense(
                  units=64, use_bias=use_bias, flatten=flatten
              )
  
          def forward(self, x):
              out = self.fc(x)
              if module == mx.npx:
                  attrs = {"newshape": (1, -1)}
              else:
                  attrs = {"shape": (1, -1)}
                  out = out.as_nd_ndarray()
              out = getattr(module, "reshape")(out, **attrs)
              return out.as_np_ndarray()
  
      net = FC_Reshape(use_bias, flatten)
      check_quantize(net, data_shape, out_type, 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 3 for calling a global function with example usage: test_fc_reshape(data_shape, use_bias, out_type, flatten, module) and returns: out