b01dbb875df263184060a27ebd9a829a20703119,torchnlp/datasets/snli.py,,snli_dataset,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,10

Before Change

                    "premise_transitions": get_transitions(line["sentence1_binary_parse"]),
                    "hypothesis_transitions": get_transitions(line["sentence2_binary_parse"])
                })
        ret.append(Dataset(examples))

    if len(ret) == 1:
        return ret[0]

After Change

    download_file_maybe_extract(url=url, directory=directory, check_files=check_files)

    get_transitions = lambda parse: ["reduce" if t == ")" else "shift" for t in parse if t != "("]
    ret = []
    splits = [(train, train_filename), (dev, dev_filename), (test, test_filename)]
    splits = [f for (requested, f) in splits if requested]
    for filename in splits:
        full_path = os.path.join(directory, extracted_name, filename)

Instances