def MaxPooling(
        inputs,
        pool_size,
        strides=None,
        padding='valid',
        data_format='channels_last'):
    """
    Same as `tf.layers.MaxPooling2D`. Default strides is equal to pool_size.
    """
    if strides is None:
        strides = pool_size
    layer = tf.layers.MaxPooling2D(pool_size, strides, padding=padding, data_format=data_format)
    ret = layer.apply(inputs, scope=tf.get_variable_scope())
    return tf.identity(ret, name='output')
def MaxPooling ( inputs , pool_size , strides = None , padding = 'valid' , data_format = 'channels_last' ) : if strides is None : strides = pool_size layer = tf . layers . MaxPooling2D ( pool_size , strides , padding = padding , data_format = data_format ) ret = layer . apply ( inputs , scope = tf . get_variable_scope ( ) ) return tf . identity ( ret , name = 'output' )
Same as `tf.layers.MaxPooling2D`. Default strides is equal to pool_size.