def load_azureml_df(local_cache_path=None, file_split=Split.TRAIN, file_type="txt"):
    """
    Loads the SNLI dataset as AzureML dataflow object
    Download the dataset from "https://nlp.stanford.edu/projects/snli/snli_1.0.zip", unzip,
    and load.

    Args:
        local_cache_path (str): Path (directory or a zip file) to cache the downloaded zip file.
            If None, all the intermediate files will be stored in a temporary directory and removed
            after use.
        file_split (str): File split to load. One of (dev, test, train)
        file_type (str): File type to load. One of (txt, jsonl)

    Returns:
        AzureML dataflow: SNLI dataset

    """
    with download_path(local_cache_path) as path:
        filepath = os.path.join(path, "snli_1.0.zip")
        snlipath = _maybe_download_and_extract(filepath, file_split, file_type)

        # NOTE: this works for the txt format but not the jsonl format
        df = dprep.auto_read_file(snlipath)

    return df

    Loads the SNLI dataset as AzureML dataflow object
    Download the dataset from "https://nlp.stanford.edu/projects/snli/snli_1.0.zip", unzip,
    and load.

    Args:
        local_cache_path (str): Path (directory or a zip file) to cache the downloaded zip file.
            If None, all the intermediate files will be stored in a temporary directory and removed
            after use.
        file_split (str): File split to load. One of (dev, test, train)
        file_type (str): File type to load. One of (txt, jsonl)

    Returns:
        AzureML dataflow: SNLI dataset

    
utils_nlp/dataset/snli.py