Datasets:
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import datasets
_CITATION = ""
# You can copy an official description
_DESCRIPTION = """\
The dataset is based on the Hutter Prize (http://prize.hutter1.net) and contains the first 10^8 bytes of English Wikipedia in 2006 in XML
"""
_HOMEPAGE = "http://mattmahoney.net/dc/textdata.html"
_LICENSE = ""
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URLS = {"source": "http://mattmahoney.net/dc/enwik8.zip"}
class Enwik8(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("2.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="enwik8-standard",
version=VERSION,
description="This version of the dataset uses the standard split of 90M/5M/5M bytes, and yields a single text blob per split.",
)
]
DEFAULT_CONFIG_NAME = "enwik8-standard"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
}
),
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = _URLS["source"]
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, "enwik8"),
"split": "train",
"start_index": 0,
"end_index": 90_000_000,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": os.path.join(data_dir, "enwik8"),
"split": "validation",
"start_index": 90_000_000,
"end_index": 95_000_000,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": os.path.join(data_dir, "enwik8"),
"split": "test",
"start_index": 95_000_000,
"end_index": 100_000_000,
},
)
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, filepath, split, start_index, end_index):
with open(filepath, encoding="utf-8") as f:
yield 0, {"text": f.read()[start_index:end_index]}
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