fe498b3d5e1e29fb756c203d50e217e8f258e561,examples/training/train_parser.py,,main,#Any#Any#Any#,41

Before Change

            random.shuffle(TRAIN_DATA)
            losses = {}
            for words, heads, deps in TRAIN_DATA:
                doc = Doc(nlp.vocab, words=words)
                gold = GoldParse(doc, heads=heads, deps=deps)
                nlp.update([doc], [gold], sgd=optimizer, losses=losses)
            print(losses)

    // test the trained model

After Change

    // add labels to the parser
    for _, annotations in TRAIN_DATA:
        for dep in annotations.get("deps", []):
            parser.add_label(dep)

    // get names of other pipes to disable them during training

Instances