Shortcuts

Source code for torchtext.datasets.enwik9

import os

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, HttpReader, IterableWrapper


URL = "http://mattmahoney.net/dc/enwik9.zip"

MD5 = "3e773f8a1577fda2e27f871ca17f31fd"

_PATH = "enwik9.zip"

NUM_LINES = {"train": 13147026}

DATASET_NAME = "EnWik9"


[docs]@_create_dataset_directory(dataset_name=DATASET_NAME) def EnWik9(root: str): """EnWik9 dataset 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=lambda x: os.path.join(root, _PATH), hash_dict={os.path.join(root, _PATH): 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=lambda x: os.path.join(root, os.path.splitext(_PATH)[0]) ) cache_decompressed_dp = FileOpener(cache_decompressed_dp, mode="b").read_from_zip() cache_decompressed_dp = cache_decompressed_dp.end_caching( mode="wb", same_filepath_fn=True ) data_dp = FileOpener(cache_decompressed_dp, mode="b") return data_dp.readlines(decode=True, return_path=False)

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources