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Maps a sequence of symbols to a vector per example by averaging embeddings.

ids [batch_size, doc_length] Tensor or SparseTensor 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.
sparse_lookup bool, if True, converts ids to a SparseTensor and performs a sparse embedding lookup. This is usually faster, but not desirable if padding tokens should have an embedding. Empty rows are assigned a special embedding.
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.

Encoding Tensor [batch_size, embed_dim] produced by averaging embeddings.

ValueError If embed_dim or vocab_size are not specified.