class_docstr: Abstract base class for convolutional RNNs
class_docstr_tok: ["Abstract","base","class","for","convolutional","RNNs"]
code: def _num_gates(self):
      return len(self._gate_names)
  
imports: from math import floor
  from ...base import numeric_types
  from .rnn_cell import HybridRecurrentCell
  from ..parameter import Parameter
  from ...None import np, npx
  from ...util import use_np
label_desc: Use image node_id 4 for calling the _BaseConvRNNCell obj's underlying member method code with example usage: obj._num_gates() and returns: len