tf.contrib.layers.embed_sequence

Maps a sequence of symbols to a sequence of embeddings.

tf.contrib.layers.embed_sequence(
    ids, vocab_size=None, embed_dim=None, unique=False, initializer=None,
    regularizer=None, trainable=True, scope=None, reuse=None
)

Typical use case would be reusing embeddings between an encoder and decoder.

Args
ids	[batch_size, doc_length] Tensor of type int32 or int64 with symbol ids.
vocab_size	Integer number of symbols in vocabulary.
embed_dim	Integer number of dimensions for embedding matrix.
unique	If True, will first compute the unique set of indices, and then lookup each embedding once, repeating them in the output as needed.
initializer	An initializer for the embeddings, if None default for current scope is used.
regularizer	Optional regularizer for the embeddings.
trainable	If True also add variables to the graph collection GraphKeys.TRAINABLE_VARIABLES (see tf.Variable).
scope	Optional string specifying the variable scope for the op, required if reuse=True.
reuse	If True, variables inside the op will be reused.

Returns
Tensor of [batch_size, doc_length, embed_dim] with embedded sequences.

Raises
ValueError	if embed_dim or vocab_size are not specified when reuse is None or False.