class_docstr: Consensus used in temporal segment networks.
  
  Parameters
  ----------
  nclass : number of classses
  num_segments : number of segments
  kwargs : arguments goes to mxnet.gluon.nn.Consensus
class_docstr_tok: ["Consensus","used","in","temporal","segment","networks",".","Parameters","--","--","--","--","--","nclass",":","number","of","classses","num_segments",":","number","of","segments","kwargs",":","arguments","goes","to","mxnet.gluon.nn.Consensus"]
code: def hybrid_forward(self, F, x):
      reshape_out = x.reshape((-1, self.num_segments, self.nclass))
      consensus_out = reshape_out.mean(axis=1)
      return consensus_out
  
imports: from __future__ import absolute_import
  from mxnet import initializer
  from mxnet.gluon import nn, contrib
  from mxnet.gluon.nn import BatchNorm, HybridBlock
label_desc: Use image node_id 2 for calling the Consensus obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: consensus_out