File size: 5,298 Bytes
513c770 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 |
# coding=utf-8
# 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.
"""Cleaned Indonesian split of the KoPI corpus."""
import json
import glob
import gzip
import textwrap
import datasets
import zstandard as zstd
logger = datasets.logging.get_logger(__name__)
_CITATION = """
"""
_DESCRIPTION = """\
"""
_HOMEPAGE = "https://huggingface.co/datasets/munggok/KoPI"
_LICENSE = "CC0"
_BASE_URL = {
"train":"https://huggingface.co/datasets/munggok/KoPI/resolve/main/data/kopi-{index:012d}.json.zst",
"val":"https://huggingface.co/datasets/munggok/KoPI/resolve/main/data/kopi-val-{index:012d}.json.zst"
}
_CONFIGS = {
"tiny": {"train": 10, "validation": 1},
"small": {"train": 30, "validation": 2},
"medium": {"train": 55, "validation": 2},
"large": {"train": 75, "validation": 3},
"full": {"train": 107, "validation": 4}
}
class KoPIConfig(datasets.BuilderConfig):
"""BuilderConfig for the Clean KoPI corpus."""
def __init__(self, **kwargs):
"""BuilderConfig for Clean KoPI corpus.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super().__init__(**kwargs)
class KoPI(datasets.GeneratorBasedBuilder):
"""KoPI corpus."""
BUILDER_CONFIGS = [
KoPIConfig(
name="tiny",
version=datasets.Version("1.0.0"),
description=textwrap.dedent(
f"""\
Tiny version only using 10 shard
"""
)
),
KoPIConfig(
name="small",
version=datasets.Version("1.0.0"),
description=textwrap.dedent(
f"""\
small version only using 30 shard
"""
)
),
KoPIConfig(
name="medium",
version=datasets.Version("1.0.0"),
description=textwrap.dedent(
f"""\
medion version only using 50 shard
"""
)
),
KoPIConfig(
name="large",
version=datasets.Version("1.0.0"),
description=textwrap.dedent(
f"""\
large version only using 75 shard
"""
)
),
KoPIConfig(
name="full",
version=datasets.Version("1.0.0"),
description=textwrap.dedent(
f"""\
The full cleaned version of KoPI corpus.
Estimated size of compressed files: 53GB
"""
)
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
"url": datasets.Value("string"),
"timestamp": datasets.Value("string"),
"meta": datasets.Value("string"),
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
train = [_BASE_URL["train"].format(index=k + 1) for k in range(107)][0:_CONFIGS[self.config.name]['train']]
validation = [_BASE_URL["val"].format(index=k + 108) for k in range(4)][0:_CONFIGS[self.config.name]['validation']]
train_downloaded_files = dl_manager.download(train)
validation_downloaded_files = dl_manager.download(validation)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": validation_downloaded_files}
),
]
def _generate_examples(self, filepaths):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
id_ = 0
for filepath in filepaths:
logger.info(f"Generating examples from {filepath}")
with zstd.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
for line in f:
if line:
example = json.loads(line)
if example.get('meta') is not None:
yield id_, {'text':example['text'],'url':example['url'],'timestamp':example['timestamp'],'meta': example['meta']}
id_ += 1
else:
yield id_, {'text':example['text'],'url':example['url'],'timestamp':example['timestamp'],'meta': "None"}
id_ += 1
|