Doubts about the input format when training a SDP model. #85
Description
Hi,
I'm trying to train a SDP model and reading the Usage section of the README.md:
>>> sdp = Parser.load('biaffine-sdp-en')
>>> sdp.predict([[('I','I','PRP'), ('saw','see','VBD'), ('Sarah','Sarah','NNP'), ('with','with','IN'),
('a','a','DT'), ('telescope','telescope','NN'), ('.','_','.')]],
verbose=False)[0]
1 I I PRP _ _ _ _ 2:ARG1 _
2 saw see VBD _ _ _ _ 0:root|4:ARG1 _
3 Sarah Sarah NNP _ _ _ _ 2:ARG2 _
4 with with IN _ _ _ _ _ _
5 a a DT _ _ _ _ _ _
6 telescope telescope NN _ _ _ _ 4:ARG2|5:BV _
7 . _ . _ _ _ _ _ _
The 9th column is 0:root|4:ARG1. I'm using the UD CoNLL-U files for English (EWT) and the 9th column is like 21:nmod:near so if I try to train a SDP model I get the error:
File "/home/iago/SuPar/supar/utils/field.py", line 359, in <genexpr>
for row in self.preprocess(chart)
File "/home/iago/SuPar/supar/utils/field.py", line 171, in preprocess
sequence = self.fn(sequence)
File "/home/iago/SuPar/supar/utils/transform.py", line 177, in get_labels
edge, label = pair.split(':')
ValueError: too many values to unpack (expected 2)
Because I think it expects something like 0:root|4:ARG1 instead of 21:nmod:near. Does SuPar have a function to transform the UD CoNLL-U files to that format? I'm trying to train the model through the command line, not through code with:
python -m supar.cmds.biaffine_sdp train --build --device 0 --conf config/biaffine.sdp.ini \
--n-embed 300 --encoder bert --unk '' \
--embed data/Embeddings/English/cc.en.300.vec \
--train data/Corpus/English-EWT/en_ewt-ud-train.conllu \
--dev data/Corpus/English-EWT/en_ewt-ud-dev.conllu \
--test data/Corpus/English-EWT/en_ewt-ud-test.conllu \
--path models/English-EWT/Model_1
Regards.