import os
from torchtext.utils import download_from_url, extract_archive
from torchtext.data.datasets_utils import (
    _RawTextIterableDataset,
    _wrap_split_argument,
    _add_docstring_header,
    _find_match,
    _create_dataset_directory,
    _create_data_from_csv,
)

URL = 'https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbNUpYQ2N3SGlFaDg'

MD5 = '620c8ae4bd5a150b730f1ba9a7c6a4d3'

NUM_LINES = {
    'train': 560000,
    'test': 38000,
}

_PATH = 'yelp_review_polarity_csv.tar.gz'

DATASET_NAME = "YelpReviewPolarity"


@_add_docstring_header(num_lines=NUM_LINES, num_classes=2)
@_create_dataset_directory(dataset_name=DATASET_NAME)
@_wrap_split_argument(('train', 'test'))
def YelpReviewPolarity(root, split):
    dataset_tar = download_from_url(URL, root=root,
                                    path=os.path.join(root, _PATH),
                                    hash_value=MD5, hash_type='md5')
    extracted_files = extract_archive(dataset_tar)

    path = _find_match(split + '.csv', extracted_files)
    return _RawTextIterableDataset(DATASET_NAME, NUM_LINES[split],
                                   _create_data_from_csv(path))

from torchtext._internal.module_utils import is_module_available
from typing import Union, Tuple

if is_module_available("torchdata"):
    from torchdata.datapipes.iter import FileOpener, GDriveReader, IterableWrapper

from torchtext.data.datasets_utils import (
    _wrap_split_argument,
    _add_docstring_header,
    _create_dataset_directory,
)

import os

URL = 'https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbNUpYQ2N3SGlFaDg'

MD5 = '620c8ae4bd5a150b730f1ba9a7c6a4d3'

NUM_LINES = {
    'train': 560000,
    'test': 38000,
}

_PATH = 'yelp_review_polarity_csv.tar.gz'

DATASET_NAME = "YelpReviewPolarity"

_EXTRACTED_FILES = {
    'train': os.path.join('yelp_review_polarity_csv', 'train.csv'),
    'test': os.path.join('yelp_review_polarity_csv', 'test.csv'),
}


@_add_docstring_header(num_lines=NUM_LINES, num_classes=2)
@_create_dataset_directory(dataset_name=DATASET_NAME)
@_wrap_split_argument(('train', 'test'))
def YelpReviewPolarity(root: str, split: Union[Tuple[str], str]):
    if not is_module_available("torchdata"):
        raise ModuleNotFoundError("Package `torchdata` not found. Please install following instructions at `https://github.com/pytorch/data`")

    url_dp = IterableWrapper([URL])

    cache_dp = url_dp.on_disk_cache(
        filepath_fn=lambda x: os.path.join(root, _PATH),
        hash_dict={os.path.join(root, _PATH): MD5}, hash_type="md5"
    )
    cache_dp = GDriveReader(cache_dp).end_caching(mode="wb", same_filepath_fn=True)
    cache_dp = FileOpener(cache_dp, mode="b")

    extracted_files = cache_dp.read_from_tar()

    filter_extracted_files = extracted_files.filter(lambda x: _EXTRACTED_FILES[split] in x[0])

    return filter_extracted_files.parse_csv().map(fn=lambda t: (int(t[0]), " ".join(t[1:])))

migrate YelpReviewPolarity to datapipes. (#1509)