A 2D SparseTensor representing int64 values (most likely that are the
result of calling compute_and_apply_vocabulary on a tokenized string).
An int - the count of vocab used to turn the string into int64s
including any OOV buckets.
A bool indicating if the inverse document frequency should be
smoothed. If True, which is the default, then the idf is calculated as
1 + log((corpus size + 1) / (document frequency of term + 1)).
Otherwise, the idf is
1 +log((corpus size) / (document frequency of term)), which could
result in a division by zero error.
(Optional) A name for this operation.
Two SparseTensors with indices [index_in_batch, index_in_bag_of_words].
The first has values vocab_index, which is taken from input x.
The second has values tfidf_weight.