test the model

main.py

def test_model(model, test_dataset):
    test_loader = data.DataLoader(test_dataset)
    model.eval()
    with torch.no_grad():
        all_tags = []
        all_tag_scores = []
        for sample, tags in tqdm.tqdm(test_loader):
            sample = sample[0]
            tags = tags[0]

            tag_scores = model(sample)

            all_tags.extend(tags.numpy())
            all_tag_scores.extend(tag_scores.numpy())

        all_tags = numpy.array(all_tags)
        all_tag_scores = numpy.array(all_tag_scores).argmax(axis=1)
        accuracy = accuracy_score(all_tags, all_tag_scores)
        pr = precision_score(all_tags, all_tag_scores)
        recall = recall_score(all_tags, all_tag_scores)
        f1 = f1_score(all_tags, all_tag_scores)

        print("accuracy: {}".format(accuracy))
        print("pr: {}".format(pr))
        print("recall: {}".format(recall))
        print("f1: {}".format(f1))