Conditional Random Field (CRF) Sequence Decoder

The current example for Name Entity Extraction is given as the following model definition:

input_features:
    -
        name: utterance
        type: text
        level: word
        encoder: rnn
        cell_type: lstm
        reduce_output: null
        preprocessing:
          word_format: space

output_features:
    -
        name: tag
        type: sequence
        decoder: tagger

This works ok, but if Ludwig had a CRF-Decoding layer, one could build state-of-the-art Bi-LSTM+CRF models (like https://arxiv.org/pdf/1508.01991.pdf) in a single simple Ludwig model definition. Any chance CRF decoding is coming to Ludwig any time soon?

[jenishah]

Working on it

[w4nderlust]

Add a class CRFTagger in sequence_decoders ?

Yes that would be great. Consider that we are planning to move to TF2 soon, so at the moment you can use the contrib package, but make sure that you’ll be able to port to the addons package.