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Maurice Weber commited on
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a706d31
2 Parent(s): eee2123 ada48bd

Merge branch 'deduplicate_flag'

Browse files
RedPajama-Data-V2.py CHANGED
@@ -19,10 +19,11 @@ import json
19
 
20
  import datasets
21
  import traceback
22
- import os
23
  import gzip
24
  from typing import List
25
 
 
 
26
  logger = datasets.logging.get_logger(__name__)
27
 
28
  _DESCRIPTION = """\
@@ -31,7 +32,8 @@ RedPajama V2: an Open Dataset for Training Large Language Models
31
 
32
  _URL_BASE = 'https://data.together.xyz/redpajama-data-v2/v1.0.0'
33
  _LANGUAGES = ("en", "de", "fr", "es", "it")
34
- _LISTINGS_PATTERN = "listings/{language}-{snapshot}-{partition}.txt"
 
35
 
36
  _CC_SNAPSHOT_IDS = (
37
  "2014-15",
@@ -166,35 +168,42 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
166
  )
167
 
168
  def _split_generators_sample(self, dl_manager):
169
- # fetch documents
170
- sample_listings = dl_manager.download_and_extract(
171
  "sample/sample_listings.txt"
172
  )
173
- with open(sample_listings, "r") as fd:
174
- listings = [line.strip() for line in fd]
175
 
176
  # fetch documents
 
177
  documents_files = dl_manager.download({
178
- "head_middle": [
179
- f"sample/documents/{lst}.json.gz" for lst in listings
180
- ]
181
  })
182
 
183
  # fetch quality signals
 
184
  quality_signals_files = dl_manager.download({
185
- "head_middle": [
186
- f"sample/quality_signals/{lst}.signals.json.gz"
187
- for lst in listings
188
- ]
 
 
 
 
 
189
  })
190
 
191
  return [
192
  datasets.SplitGenerator(
193
  name=datasets.Split.TRAIN,
194
  gen_kwargs={
195
- "listings_ids": {"head_middle": listings},
196
  "documents_files": documents_files,
197
- "quality_signals_files": quality_signals_files
 
198
  }
199
  )
200
  ]
@@ -204,66 +213,75 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
204
  languages = getattr(self.config, 'languages', _LANGUAGES)
205
  partition = getattr(self.config, 'partition', 'all')
206
 
207
- partitions = {
208
- "all": ["head_middle", "tail"]
209
- }.get(partition, [partition])
210
-
211
- # nested structure: partition -> urls
212
- listings_files_urls = {}
213
- for part in partitions:
214
- listings_files_urls[part] = []
215
- for snapshot_id in snapshots:
216
- for lang in languages:
217
- listings_files_urls[part].append(
218
- _LISTINGS_PATTERN.format(
219
- language=lang,
220
- snapshot=snapshot_id,
221
- partition=part,
222
- )
223
- )
224
-
225
- # fetch listings from hub
226
- listings_files = dl_manager.download_and_extract(listings_files_urls)
227
-
228
- # fetch listings
229
- listings_ids = {}
230
- for part, part_listings_files in listings_files.items():
231
- listings_ids[part] = []
232
- for listings_file in part_listings_files:
233
- with open(listings_file, encoding="utf-8") as f:
234
- listings_ids[part].extend([
235
- line.strip() for line in f
236
- ])
237
-
238
- # build urls pointing to documents and quality signals
239
- document_urls = {}
240
  quality_signals_urls = {}
241
- for part, part_listings_ids in listings_ids.items():
242
- document_urls[part] = []
243
- quality_signals_urls[part] = []
244
- for lst_id in part_listings_ids:
245
- document_urls[part].append(
246
- os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
247
- )
248
- if part != "head_middle":
249
- continue
250
-
251
- quality_signals_urls[part].append(
252
- os.path.join(
253
- _URL_BASE, f"quality_signals/{lst_id}.signals.json.gz"
254
- )
255
- )
256
-
257
- documents_files = dl_manager.download(document_urls)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
258
  quality_signals_files = dl_manager.download(quality_signals_urls)
259
 
 
 
 
 
260
  return [
261
  datasets.SplitGenerator(
262
  name=datasets.Split.TRAIN,
263
  gen_kwargs={
264
- "listings_ids": listings_ids,
265
  "documents_files": documents_files,
266
- "quality_signals_files": quality_signals_files
 
267
  }
268
  )
269
  ]
@@ -275,71 +293,88 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
275
  return self._split_generators_full(dl_manager)
276
 
277
  def _generate_examples(
278
- self, listings_ids, documents_files, quality_signals_files
 
279
  ):
280
  key = 0
281
- for part in documents_files.keys():
282
- part_docs_files = documents_files[part]
283
- part_qs_files = quality_signals_files[part]
284
- part_listings_ids = listings_ids[part]
285
-
286
- if len(part_qs_files) == 0:
287
- for sample in self._handle_tail_partition(
288
- part, part_docs_files, part_listings_ids
289
- ):
290
- yield key, sample
291
- key += 1
292
  continue
293
 
294
- for sample in self._handle_head_middle_partition(
295
- part, part_docs_files, part_qs_files, part_listings_ids
296
  ):
297
  yield key, sample
298
  key += 1
299
 
300
- def _handle_tail_partition(self, part, docs_files, listings_ids):
301
- for doc_file, listing_id in zip(docs_files, listings_ids):
 
 
 
 
 
 
302
  with gzip.open(doc_file, "rt", encoding="utf-8") as df:
303
  for row, doc in enumerate(df):
304
- doc_id = f"{listing_id}.json.gz/{row}"
305
  try:
306
- yield self.handle_record(part, doc_id, doc, None)
307
  except Exception as e:
308
- print(f'doc_file: {doc_file}')
309
- print(f'row: {row}')
310
  traceback.print_exc()
311
- raise e
312
 
313
- def _handle_head_middle_partition(
314
- self, part, docs_files, qs_files, listings_ids
 
 
 
 
 
 
315
  ):
316
- assert len(docs_files) == len(qs_files)
317
-
318
- listings_ids = listings_ids[:len(docs_files)]
319
-
320
- for doc_file, qs_file, listings_id in zip(
321
- docs_files, qs_files, listings_ids
322
- ):
323
- try:
324
- with gzip.open(doc_file, "rt", encoding="utf-8") as df:
325
- with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
326
- for row, (doc, qs) in enumerate(zip(df, qf)):
327
- doc_id = f"{listings_id}.json.gz/{row}"
328
- try:
329
- yield self.handle_record(part, doc_id, doc, qs)
330
- except Exception as e:
331
- print(f'failed handling row {row} in '
332
- f'{doc_file} ({qs_file})')
333
- traceback.print_exc()
334
- continue
335
- except gzip.BadGzipFile as e:
336
- # skip broken gzip files
337
- print(f'BadGzipFile: {doc_file, qs_file}')
338
- traceback.print_exc()
339
- continue
 
 
 
 
 
 
 
 
 
 
340
 
341
  @staticmethod
342
- def handle_record(part, doc_id, doc, qs):
343
  doc = json.loads(doc)
344
  qs = json.loads(qs) if qs is not None else {}
345
 
@@ -352,11 +387,12 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
352
  "digest": doc["digest"],
353
  }
354
 
355
- quality_signals = json.dumps(qs.get("quality_signals", {}))
 
356
 
357
  return {
358
  "raw_content": doc["raw_content"],
359
  "doc_id": doc_id,
360
  "meta": json.dumps(meta),
361
- "quality_signals": quality_signals,
362
  }
 
19
 
20
  import datasets
21
  import traceback
 
22
  import gzip
23
  from typing import List
24
 
25
+ import pyarrow.parquet as pq
26
+
27
  logger = datasets.logging.get_logger(__name__)
28
 
29
  _DESCRIPTION = """\
 
32
 
33
  _URL_BASE = 'https://data.together.xyz/redpajama-data-v2/v1.0.0'
34
  _LANGUAGES = ("en", "de", "fr", "es", "it")
35
+ _MISSING_FILES_PATTERN = "urls/missing-{component}.txt"
36
+ _NUM_SHARDS = 5000
37
 
38
  _CC_SNAPSHOT_IDS = (
39
  "2014-15",
 
168
  )
169
 
170
  def _split_generators_sample(self, dl_manager):
171
+ # fetch list of base tags
172
+ sample_base_tags_fp = dl_manager.download_and_extract(
173
  "sample/sample_listings.txt"
174
  )
175
+ with open(sample_base_tags_fp, "r") as fd:
176
+ sample_base_tags = [line.strip() for line in fd]
177
 
178
  # fetch documents
179
+ logger.info(f"Downloading {len(sample_base_tags)} documents files.")
180
  documents_files = dl_manager.download({
181
+ base_tag: f"sample/documents/{base_tag}.json.gz"
182
+ for base_tag in sample_base_tags
 
183
  })
184
 
185
  # fetch quality signals
186
+ logger.info(f"Downloading {len(sample_base_tags)} quality signals files.")
187
  quality_signals_files = dl_manager.download({
188
+ base_tag: f"sample/quality_signals/{base_tag}.signals.json.gz"
189
+ for base_tag in sample_base_tags
190
+ })
191
+
192
+ # fetch ids of duplicates
193
+ logger.info(f"Downloading {len(sample_base_tags)} duplicates ids files.")
194
+ duplicates_ids_files = dl_manager.download({
195
+ base_tag: f"sample/duplicates/{base_tag}.duplicates.parquet"
196
+ for base_tag in sample_base_tags
197
  })
198
 
199
  return [
200
  datasets.SplitGenerator(
201
  name=datasets.Split.TRAIN,
202
  gen_kwargs={
203
+ "base_tags": sample_base_tags,
204
  "documents_files": documents_files,
205
+ "quality_signals_files": quality_signals_files,
206
+ "duplicates_ids_files": duplicates_ids_files
207
  }
208
  )
209
  ]
 
213
  languages = getattr(self.config, 'languages', _LANGUAGES)
214
  partition = getattr(self.config, 'partition', 'all')
215
 
216
+ if partition == 'all':
217
+ partitions = ['head', 'middle', 'tail']
218
+ elif partition == 'head_middle':
219
+ partitions = ['head', 'middle']
220
+ elif partition == 'tail':
221
+ partitions = [partition]
222
+ else:
223
+ raise ValueError(f'invalid partition: {partition}')
224
+
225
+ # fetch list of missing files (e.g., missing duplicates or corrupted documents and
226
+ # quality signal files)
227
+ missing_files_paths = dl_manager.download_and_extract({
228
+ component: _MISSING_FILES_PATTERN.format(component=component)
229
+ for component in ("documents", "signals", "duplicates")
230
+ })
231
+
232
+ missing_files = {}
233
+ for component, missing_file in missing_files_paths.items():
234
+ with open(missing_file) as f:
235
+ missing_files[component] = set(line.strip() for line in f)
236
+
237
+ # build list of urls to fetch
238
+ documents_urls = {}
 
 
 
 
 
 
 
 
 
 
239
  quality_signals_urls = {}
240
+ duplicates_ids_urls = {}
241
+ base_tags = []
242
+
243
+ for lang in languages:
244
+ for snapshot in snapshots:
245
+ for part in partitions:
246
+ for n in range(_NUM_SHARDS):
247
+ base_tag = f"{snapshot}/{n:04d}/{lang}_{part}"
248
+ base_tags.append(base_tag)
249
+
250
+ # documents
251
+ url = f"{_URL_BASE}/documents/{base_tag}.json.gz"
252
+ if url not in missing_files["documents"]:
253
+ documents_urls[base_tag] = url
254
+
255
+ # quality signals
256
+ url = f"{_URL_BASE}/quality_signals/{base_tag}.signals.json.gz"
257
+ if url not in missing_files["signals"]:
258
+ quality_signals_urls[base_tag] = url
259
+
260
+ # duplicates
261
+ url = f"{_URL_BASE}/duplicates/{base_tag}.duplicates.parquet"
262
+ if url not in missing_files["duplicates"]:
263
+ duplicates_ids_urls[base_tag] = url
264
+
265
+ # download documents files
266
+ logger.info(f"Downloading {len(documents_urls)} documents files.")
267
+ documents_files = dl_manager.download(documents_urls)
268
+
269
+ # download quality signals files
270
+ logger.info(f"Downloading {len(quality_signals_urls)} quality signals files.")
271
  quality_signals_files = dl_manager.download(quality_signals_urls)
272
 
273
+ # download duplicates ids files
274
+ logger.info(f"Downloading {len(duplicates_ids_urls)} duplicates ids files.")
275
+ duplicates_ids_files = dl_manager.download(duplicates_ids_urls)
276
+
277
  return [
278
  datasets.SplitGenerator(
279
  name=datasets.Split.TRAIN,
280
  gen_kwargs={
281
+ "base_tags": base_tags,
282
  "documents_files": documents_files,
283
+ "quality_signals_files": quality_signals_files,
284
+ "duplicates_ids_files": duplicates_ids_files
285
  }
286
  )
287
  ]
 
293
  return self._split_generators_full(dl_manager)
294
 
295
  def _generate_examples(
296
+ self, base_tags, documents_files, quality_signals_files,
297
+ duplicates_ids_files
298
  ):
299
  key = 0
300
+ for base_tag in base_tags:
301
+ doc_file = documents_files.get(base_tag)
302
+ qs_file = quality_signals_files.get(base_tag)
303
+ dupe_file = duplicates_ids_files.get(base_tag)
304
+
305
+ if doc_file is None:
 
 
 
 
 
306
  continue
307
 
308
+ for sample in self.__get_generator(
309
+ base_tag, doc_file, qs_file, dupe_file
310
  ):
311
  yield key, sample
312
  key += 1
313
 
314
+ def __get_generator(self, base_tag, doc_file, qs_file, dupe_file):
315
+ if "_tail" in base_tag:
316
+ yield from self._handle_tail(base_tag, doc_file, qs_file, dupe_file)
317
+ else:
318
+ yield from self._handle_head_middle(base_tag, doc_file, qs_file, dupe_file)
319
+
320
+ def _handle_tail(self, base_tag, doc_file, qs_file, dupe_file):
321
+ try:
322
  with gzip.open(doc_file, "rt", encoding="utf-8") as df:
323
  for row, doc in enumerate(df):
324
+ doc_id = f"{base_tag}.json.gz/{row}"
325
  try:
326
+ yield self.handle_record("tail", doc_id, doc, None, None)
327
  except Exception as e:
328
+ logger.warning(f'failed handling row {row} in {doc_file}')
 
329
  traceback.print_exc()
330
+ continue
331
 
332
+ except gzip.BadGzipFile as e:
333
+ # skip broken gzip files
334
+ print(f'BadGzipFile: {doc_file, qs_file}')
335
+ traceback.print_exc()
336
+ return
337
+
338
+ def _handle_head_middle(
339
+ self, base_tag, doc_file, qs_file, dupe_file
340
  ):
341
+ if qs_file is None:
342
+ yield from self._handle_tail(base_tag, doc_file, None, None)
343
+ return
344
+
345
+ # load duplicates
346
+ try:
347
+ with open(dupe_file, "rb") as df:
348
+ duplicates = set(pq.read_table(
349
+ df, columns=["doc_id"], use_pandas_metadata=False
350
+ )["doc_id"].to_pylist())
351
+ except Exception as e:
352
+ logger.warning(f'no duplicate ids found for {base_tag}')
353
+ duplicates = set()
354
+
355
+ try:
356
+ with gzip.open(doc_file, "rt", encoding="utf-8") as df:
357
+ with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
358
+ for row, (doc, qs) in enumerate(zip(df, qf)):
359
+ doc_id = f"{base_tag}.json.gz/{row}"
360
+
361
+ try:
362
+ yield self.handle_record(
363
+ "head_middle", doc_id, doc, qs, is_duplicate=doc_id in duplicates
364
+ )
365
+ except Exception as e:
366
+ logger.warning(f'failed handling row {row} in {doc_file} ({qs_file})')
367
+ traceback.print_exc()
368
+ continue
369
+
370
+ except gzip.BadGzipFile as e:
371
+ # skip broken gzip files
372
+ print(f'BadGzipFile: {doc_file, qs_file}')
373
+ traceback.print_exc()
374
+ return
375
 
376
  @staticmethod
377
+ def handle_record(part, doc_id, doc, qs, is_duplicate=None):
378
  doc = json.loads(doc)
379
  qs = json.loads(qs) if qs is not None else {}
380
 
 
387
  "digest": doc["digest"],
388
  }
389
 
390
+ quality_signals = qs.get("quality_signals", {})
391
+ quality_signals["is_duplicate"] = is_duplicate
392
 
393
  return {
394
  "raw_content": doc["raw_content"],
395
  "doc_id": doc_id,
396
  "meta": json.dumps(meta),
397
+ "quality_signals": json.dumps(quality_signals),
398
  }
urls/missing-documents.txt ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2014-52/2811/en_head.json.gz
2
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2014-52/3215/en_middle.json.gz
3
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2014-52/4251/en_head.json.gz
4
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2015-40/0914/it_head.json.gz
5
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2015-40/0964/it_head.json.gz
6
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2015-40/1315/it_head.json.gz
7
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2015-40/2650/it_head.json.gz
8
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/documents/2017-04/4965/it_middle.json.gz
urls/missing-duplicates.txt ADDED
@@ -0,0 +1,324 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-15/3397/en_head.duplicates.parquet
2
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-15/4248/en_middle.duplicates.parquet
3
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-23/3652/en_middle.duplicates.parquet
4
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-35/2797/en_head.duplicates.parquet
5
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-35/3141/en_middle.duplicates.parquet
6
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-42/0301/en_head.duplicates.parquet
7
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-42/0477/en_head.duplicates.parquet
8
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-42/4119/en_middle.duplicates.parquet
9
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-49/0242/en_head.duplicates.parquet
10
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-49/0361/de_middle.duplicates.parquet
11
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-49/0376/it_head.duplicates.parquet
12
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/0646/it_head.duplicates.parquet
13
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/1940/es_middle.duplicates.parquet
14
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/2697/fr_head.duplicates.parquet
15
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/2811/en_head.duplicates.parquet
16
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/3134/en_middle.duplicates.parquet
17
+ https://data.together.xyz/redpajama-data-v2/v1.0.0/duplicates/2014-52/3215/en_middle.duplicates.parquet
18
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