(value, name)
return tf.nn.max_pool(value, ksize=[1, 2, 2, 1],
                        strides=[1, 2, 2, 1], padding='SAME', name=name)
max_pool_2x2 downsamples a feature map by 2X.
max_pool_2x2 downsamples a feature map by 2X.
max_pool_2x2 downsamples a feature map by 2X .
def _max_pool_2x2(value, name):
  """max_pool_2x2 downsamples a feature map by 2X."""
  return tf.nn.max_pool(value, ksize=[1, 2, 2, 1],
                        strides=[1, 2, 2, 1], padding='SAME', name=name)
def _max_pool_2x2 ( value , name ) : return tf . nn . max_pool ( value , ksize = [ 1 , 2 , 2 , 1 ] , strides = [ 1 , 2 , 2 , 1 ] , padding = 'SAME' , name = name )