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Maps a sequence of symbols to a sequence of embeddings.

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

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.

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

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