Datasets:

Modalities:
Text
ArXiv:
Libraries:
Datasets
File size: 9,632 Bytes
cb715ae
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
# Copyright 2023 Together Computer
#
# 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.

# Lint as: python3
"""RedPajama V2: Quality annotated Web Text Documents."""

import json

import datasets
import traceback
import os
import gzip

logger = datasets.logging.get_logger(__name__)

_DESCRIPTION = """\
RedPajama V2 is a dataset of web documents and their quality signals.
"""

with open("_CC_SNAPSHOT_IDS", "r") as f:
    _CC_SNAPSHOT_IDS = [line.strip() for line in f]

with open("_QUALITY_SIGNAL_TAGS", "r") as f:
    _QUALITY_SIGNAL_TAGS = [line.strip() for line in f]

_URL_BASE = 'https://data.together.xyz/redpajama-data-v2/v1.0.0'
_LANGUAGES = ("en", "de", "fr", "es", "it")
_DATA_DIR = os.environ.get('RED_PAJAMA_V2_DATA_DIR', None)

_LISTINGS_PATTERN = "urls/{language}-{snapshot}-{partition}.txt"


class RedPajamaDataV2Config(datasets.BuilderConfig):
    """BuilderConfig for RedPajama."""

    def __init__(self, *args, language, partition, snapshots, **kwargs):
        """BuilderConfig for RedPajama.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(RedPajamaDataV2Config, self).__init__(**kwargs)
        self.partition = partition
        self.snapshots = snapshots
        self.language = language


_BUILDER_CONFIGS = []

for lang in _LANGUAGES:
    _BUILDER_CONFIGS.extend(
        [
            # single snapshot
            RedPajamaDataV2Config(
                name=f'{lang}-head-middle-{snapshot}',
                partition='head-middle',
                snapshots=[snapshot],
                language=lang,
                version=datasets.Version("1.0.0", ""),
                description=f"RedPajamaV2 head-middle {lang}-{snapshot}",
            )
            for snapshot in _CC_SNAPSHOT_IDS
        ] + [
            # all snapshots
            RedPajamaDataV2Config(
                name=f'{lang}-head-middle-all',
                partition='head_middle',
                snapshots=_CC_SNAPSHOT_IDS,
                language=lang,
                version=datasets.Version("1.0.0", ""),
                description=f"RedPajamaV2 head-middle {lang}"
            )
        ]
    )

    _BUILDER_CONFIGS.extend(
        [
            # single snapshot
            RedPajamaDataV2Config(
                name=f'{lang}-tail-{snapshot}',
                partition='tail',
                snapshots=[snapshot],
                language=lang,
                version=datasets.Version("1.0.0", ""),
                description=f"RedPajamaV2 tail {lang}-{snapshot}",
            )
            for snapshot in _CC_SNAPSHOT_IDS
        ] + [
            # all snapshots
            RedPajamaDataV2Config(
                name=f'{lang}-tail-all',
                partition='tail',
                snapshots=_CC_SNAPSHOT_IDS,
                language=lang,
                version=datasets.Version("1.0.0", ""),
                description=f"RedPajamaV2 tail {lang}"
            )
        ]
    )


class RedPajamaV2(datasets.GeneratorBasedBuilder):
    """ RedPajama V2: Quality annotated Web Text Documents. """

    BUILDER_CONFIGS = _BUILDER_CONFIGS

    def _info(self):
        if self.config.partition == "tail":
            return datasets.DatasetInfo(
                description=_DESCRIPTION,
                features=datasets.Features(
                    {
                        "raw_content": datasets.Value("string"),
                        "doc_id": datasets.Value("string"),
                        "meta": datasets.Value("string"),
                    }
                ),
                supervised_keys=None,
            )
        else:
            return datasets.DatasetInfo(
                description=_DESCRIPTION,
                features=datasets.Features(
                    {
                        "raw_content": datasets.Value("string"),
                        "doc_id": datasets.Value("string"),
                        "meta": datasets.Value("string"),
                        "quality_signals": datasets.Value("string")
                    }
                ),
                supervised_keys=None,
            )

    def _split_generators(self, dl_manager):
        url_lists = dl_manager.download_and_extract({
            snapshot_id: _LISTINGS_PATTERN.format(
                language=self.config.language,
                snapshot=snapshot_id,
                partition=self.config.partition,
            )
            for snapshot_id in self.config.snapshots
        })

        listings_ids = {}

        for snapshot_id, listings_file in url_lists.items():
            with open(listings_file, encoding="utf-8") as f:
                listings_ids[snapshot_id] = [line.strip() for line in f]

        # mapping document type -> url for download
        if _DATA_DIR is not None:
            documents_files = None
            quality_signals_files = None
        else:
            # build urls pointing to documents
            document_urls = {
                snapshot_id: [
                    os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
                    for lst_id in listings_ids[snapshot_id]
                ]
                for snapshot_id in self.config.snapshots
            }

            documents_files = dl_manager.download(document_urls)

            # build urls pointing to quality signals
            if self.config.partition == "head_middle":
                quality_signals_urls = {
                    snapshot_id: [
                        os.path.join(
                            _URL_BASE,
                            f"quality_signals/{lst_id}.signals.json.gz"
                        )
                        for lst_id in listings_ids[snapshot_id]
                    ]
                    for snapshot_id in self.config.snapshots
                }

                quality_signals_files = dl_manager.download(
                    quality_signals_urls
                )
            else:
                quality_signals_files = {}

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "listings_ids": listings_ids,
                    "documents_files": {
                        snapshot_id: documents_files[snapshot_id]
                        for snapshot_id in self.config.snapshots
                    },
                    "quality_signals_files": {
                        snapshot_id: quality_signals_files.get(snapshot_id)
                        for snapshot_id in self.config.snapshots
                    }
                }
            )
        ]

    def _generate_examples(self, documents_files, quality_signals_files):
        """ This function returns examples """
        snapshots = list(documents_files.keys())

        key = 0
        for snapshot in snapshots:
            docs_files = documents_files[snapshot]
            if self.config.partition == "head_middle":
                qs_files = quality_signals_files[snapshot]
            else:
                qs_files = None

            assert len(docs_files) == len(qs_files)

            for doc_file, qs_file in zip(docs_files, qs_files):
                with gzip.open(doc_file, "rt", encoding="utf-8") as df:
                    with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
                        for row, (doc, qs) in enumerate(zip(df, qf)):

                            try:
                                doc = json.loads(doc)
                                qs = json.loads(qs)
                                doc_id = qs["id"]

                                meta = {
                                    "url": doc["url"],
                                    "source_domain": doc["source_domain"],
                                    "date_download": doc["date_download"],
                                    "digest": doc["digest"],
                                }

                                if self.config.partition == "tail":
                                    yield key, {
                                        "raw_content": doc["raw_content"],
                                        "doc_id": doc_id,
                                        "meta": json.dumps(meta),
                                    }
                                else:
                                    yield key, {
                                        "raw_content": doc["raw_content"],
                                        "doc_id": doc_id,
                                        "meta": json.dumps(meta),
                                        "quality_signals": json.dumps(
                                            qs["quality_signals"]
                                        ),
                                    }
                                key += 1
                            except Exception as e:
                                print(f'doc_file: {doc_file}')
                                print(f'qs_file: {qs_file}')
                                print(f'row: {row}')
                                traceback.print_exc()

                                raise e