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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 Dropout(x, *args, **kwargs):
 """ Same as `tf.layers.dropout`. However, for historical reasons, the first positional argument is interpreted as keep_prob rather than drop_prob. Explicitly use `rate=` keyword arguments to ensure things are consistent. """

    if 'is_training' in kwargs:
        kwargs['training'] = kwargs.pop('is_training')
    if len(args) > 0:
        if args[0] != 0.5:
            logger.warn(
                "The first positional argument to tensorpack.Dropout is the probability to keep, rather than to drop. "
                "This is different from the rate argument in tf.layers.Dropout due to historical reasons. "
                "To mimic tf.layers.Dropout, explicitly use keyword argument 'rate' instead")
        rate = 1 - args[0]
    elif 'keep_prob' in kwargs:
        assert 'rate' not in kwargs, "Cannot set both keep_prob and rate!"
        rate = 1 - kwargs.pop('keep_prob')
    elif 'rate' in kwargs:
        rate = kwargs.pop('rate')
    else:
        rate = 0.5

    if kwargs.get('training', None) is None:
        kwargs['training'] = get_current_tower_context().is_training

    if get_tf_version_tuple() <= (1, 12):
        return tf.layers.dropout(x, rate=rate, **kwargs)
    else:
        return tf.nn.dropout(x, rate=rate if kwargs['training'] else 0.)