Installation, using python 2.7 (python3 not supported).
pip install -r requirements.txt
Data should be prepared with spaces separating tokens
Example data is in ./data/coco*
Training is based on the pytorch word-language model example:
python main.py --data <data-directory> --save <save-path> --nsentences <no-train-sentences>
Applying a character-level pretrained salm to tag a sentence:
import data
import torch
import particle
corpus = data.Corpus('./data/coco_char_tag')
with open('./models/coco_char.pt', 'rb') as f:
model = torch.load(f, map_location=lambda storage, loc: storage)
# define a SynSiR setup with 100 particles
tagger = particle.CharTagger(model, corpus.dictionary, 100)
sentence = "the man throws the ball to the dog"
for word in sentence.split():
word += "_"
word = map(corpus.dictionary.word2idx.__getitem__, list(word))
# updates return log-likelihood (out-of-sample) of word
ll = tagger.update(word)
print taggerThe MIT License (MIT) Copyright (c) 2018 Zalando SE
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