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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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')