class_docstr: Fully connected predictor.
  Fully connected predictor is used to ignore spatial information and will
  output fixed-sized predictions.
  
  
  Parameters
  ----------
  num_output : int
      Number of fully connected outputs.
  activation : str, optional
      Optional activation after conv, e.g. 'relu'.
  use_bias : bool
      Use bias in convolution. It is not necessary if BatchNorm is followed.
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code: def hybrid_forward(self, F, x):
      return self.predictor(x)
  
file_path: gluon-cv/gluoncv/nn/predictor.py
imports: from __future__ import absolute_import
  import mxnet
  from mxnet.gluon import HybridBlock
  from mxnet.gluon import nn
label_desc: Use image node_id 2 for calling the FCPredictor obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: self