Using Tensorflow Data Services makes sequence modelling much easier

I have switched my sentiment model to use the very nice features of TFDS for sequence preprocessing. So instead of writing my own vocab, word_to_index dictionary, encoding and padding my text, I can just use the canned ones in tfds. 


from tensorflow.keras.preprocessing.text import Tokenizer

from tensorflow.keras.preprocessing.sequence import pad_sequences


As always the code is in the git repo. 

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