d889aa1e7d7669372293f45883bcf96b864737e1,examples/imdb_cnn.py,,main,#Any#,80

Before Change

    //train_y = train_y[:1000]
    print("Parse data")
    train_X = list(tqdm.tqdm(nlp.pipe(train_X)))
    dev_X = list(tqdm.tqdm(nlp.pipe(dev_X)))
    n_sent = sum([len(list(doc.sents)) for doc in train_X])
    print("%d sentences" % n_sent)

    hpsearch = BestFirstFinder(

After Change

    train_X, train_y = zip(*train)
    test_X, test_y = zip(*test)
    train_y = Model.ops.asarray(to_categorical(train_y, nb_classes=2))
    test_y = Model.ops.asarray(to_categorical(test_y, nb_classes=2))
    
    //train_X = train_X[:2000]
    //test_X = test_X[:2000]

Instances