class_docstr: NASNet Cell class that is used as a 'layer' in image architectures.
class_docstr_tok: ["NASNet","Cell","class","that","is","used","as","a","'layer","'","in","image","architectures","."]
docstr: Runs the beginning of the conv cell before the predicted ops are run.
docstr_tok: ["Runs","the","beginning","of","the","conv","cell","before","the","predicted","ops","are","run","."]
code: def _cell_base(self, net, prev_layer):
      """Runs the beginning of the conv cell before the predicted ops are run."""
      num_filters = self._filter_size
  
      # Check to be sure prev layer stuff is setup correctly
      prev_layer = self._reduce_prev_layer(prev_layer, net)
  
      net = (
          tf.nn.relu6(net)
          if self._use_bounded_activation
          else tf.nn.relu(net)
      )
      net = slim.conv2d(net, num_filters, 1, scope="1x1")
      net = slim.batch_norm(net, scope="beginning_bn")
      # num_or_size_splits=1
      net = [net]
      net.append(prev_layer)
      return net
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the NasNetABaseCell obj's underlying member method code with example usage: obj._cell_base(net, prev_layer) and returns: net