import tensorflow as tf

    --------
    >>> batch_size = 8
    >>> x = tf.placeholder(tf.int32, shape=(batch_size, ))
    >>> net = tl.layers.EmbeddingInputlayer(inputs=x, vocabulary_size=1000, embedding_size=50, name='embed')
    ... (8, 50)

    """

    def __init__(
            self,
            inputs=None,
            vocabulary_size=80000,
            embedding_size=200,
            E_init=tf.random_uniform_initializer(-0.1, 0.1),
            E_init_args=None,
            name='embedding',
    ):
        if E_init_args is None:
            E_init_args = {}

        super(EmbeddingInputlayer, self).__init__(prev_layer=None, name=name)
        logging.info("EmbeddingInputlayer %s: (%d, %d)" % (self.name, vocabulary_size, embedding_size))

        self.inputs = inputs

        with tf.variable_scope(name):
