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import os
from functools import partial
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import _create_dataset_directory
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, IterableWrapper
from torchtext._download_hooks import HttpReader
URL = "http://mattmahoney.net/dc/enwik9.zip"
MD5 = "3e773f8a1577fda2e27f871ca17f31fd"
_PATH = "enwik9.zip"
NUM_LINES = {"train": 13147026}
DATASET_NAME = "EnWik9"
def _filepath_fn(root, _=None):
return os.path.join(root, _PATH)
def _extracted_filepath_fn(root, _=None):
return os.path.join(root, os.path.splitext(_PATH)[0])
@_create_dataset_directory(dataset_name=DATASET_NAME)
def EnWik9(root: str):
"""EnWik9 dataset
.. warning::
using datapipes is still currently subject to a few caveats. if you wish
to use this dataset with shuffling, multi-processing, or distributed
learning, please see :ref:`this note <datapipes_warnings>` for further
instructions.
For additional details refer to http://mattmahoney.net/dc/textdata.html
Number of lines in dataset: 13147026
Args:
root: Directory where the datasets are saved. Default: os.path.expanduser('~/.torchtext/cache')
:returns: DataPipe that yields raw text rows from WnWik9 dataset
:rtype: 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_compressed_dp = url_dp.on_disk_cache(
filepath_fn=partial(_filepath_fn, root),
hash_dict={_filepath_fn(root): MD5},
hash_type="md5",
)
cache_compressed_dp = HttpReader(cache_compressed_dp).end_caching(mode="wb", same_filepath_fn=True)
cache_decompressed_dp = cache_compressed_dp.on_disk_cache(filepath_fn=partial(_extracted_filepath_fn, root))
cache_decompressed_dp = FileOpener(cache_decompressed_dp, mode="b").load_from_zip()
cache_decompressed_dp = cache_decompressed_dp.end_caching(mode="wb", same_filepath_fn=True)
data_dp = FileOpener(cache_decompressed_dp, encoding="utf-8")
return data_dp.readlines(return_path=False).shuffle().set_shuffle(False).sharding_filter()
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