import tensorflow as tf

        if inputs.get_shape().ndims != 2:
            raise ValueError('inputs must be of size batch_size * batch_sentence_length')

        self.inputs = inputs

        with tf.variable_scope(name):
            self.embeddings = tf.get_variable(
                name='embeddings',
                shape=(vocabulary_size, embedding_size),
                initializer=embeddings_initializer,
                dtype=LayersConfig.tf_dtype,
                **(embeddings_kwargs or {})
