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Maurice Weber commited on
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eee2123
1 Parent(s): 2cae54f

Revert "add dedupe flag"

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This reverts commit 2cae54f422505166bf6529ab2d2835fe2e1723b1.

Files changed (1) hide show
  1. RedPajama-Data-V2.py +13 -61
RedPajama-Data-V2.py CHANGED
@@ -23,8 +23,6 @@ import os
23
  import gzip
24
  from typing import List
25
 
26
- import pyarrow.parquet as pq
27
-
28
  logger = datasets.logging.get_logger(__name__)
29
 
30
  _DESCRIPTION = """\
@@ -190,22 +188,13 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
190
  ]
191
  })
192
 
193
- # fetch ids of duplicates
194
- duplicates_ids_files = dl_manager.download({
195
- "head_middle": [
196
- f"sample/duplicates/{lst}.duplicates.parquet"
197
- for lst in listings
198
- ]
199
- })
200
-
201
  return [
202
  datasets.SplitGenerator(
203
  name=datasets.Split.TRAIN,
204
  gen_kwargs={
205
  "listings_ids": {"head_middle": listings},
206
  "documents_files": documents_files,
207
- "quality_signals_files": quality_signals_files,
208
- "duplicates_ids_files": duplicates_ids_files
209
  }
210
  )
211
  ]
@@ -246,21 +235,16 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
246
  line.strip() for line in f
247
  ])
248
 
249
- # build urls pointing to documents, quality signals and duplicate ids
250
  document_urls = {}
251
  quality_signals_urls = {}
252
- duplicates_ids_urls = {}
253
  for part, part_listings_ids in listings_ids.items():
254
-
255
  document_urls[part] = []
256
  quality_signals_urls[part] = []
257
- duplicates_ids_urls[part] = []
258
-
259
  for lst_id in part_listings_ids:
260
  document_urls[part].append(
261
  os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
262
  )
263
-
264
  if part != "head_middle":
265
  continue
266
 
@@ -270,15 +254,8 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
270
  )
271
  )
272
 
273
- duplicates_ids_urls[part].append(
274
- os.path.join(
275
- _URL_BASE, f"duplicates/{lst_id}.duplicates.parquet"
276
- )
277
- )
278
-
279
  documents_files = dl_manager.download(document_urls)
280
  quality_signals_files = dl_manager.download(quality_signals_urls)
281
- duplicates_ids_files = dl_manager.download(duplicates_ids_urls)
282
 
283
  return [
284
  datasets.SplitGenerator(
@@ -286,8 +263,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
286
  gen_kwargs={
287
  "listings_ids": listings_ids,
288
  "documents_files": documents_files,
289
- "quality_signals_files": quality_signals_files,
290
- "duplicates_ids_files": duplicates_ids_files
291
  }
292
  )
293
  ]
@@ -299,15 +275,13 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
299
  return self._split_generators_full(dl_manager)
300
 
301
  def _generate_examples(
302
- self, listings_ids, documents_files, quality_signals_files,
303
- duplicates_ids_files
304
  ):
305
  key = 0
306
  for part in documents_files.keys():
307
  part_docs_files = documents_files[part]
308
  part_qs_files = quality_signals_files[part]
309
  part_listings_ids = listings_ids[part]
310
- part_duplicates_ids_files = duplicates_ids_files[part]
311
 
312
  if len(part_qs_files) == 0:
313
  for sample in self._handle_tail_partition(
@@ -318,9 +292,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
318
  continue
319
 
320
  for sample in self._handle_head_middle_partition(
321
- part, part_docs_files, part_qs_files,
322
- part_duplicates_ids_files, part_listings_ids
323
-
324
  ):
325
  yield key, sample
326
  key += 1
@@ -331,7 +303,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
331
  for row, doc in enumerate(df):
332
  doc_id = f"{listing_id}.json.gz/{row}"
333
  try:
334
- yield self.handle_record(part, doc_id, doc, None, None)
335
  except Exception as e:
336
  print(f'doc_file: {doc_file}')
337
  print(f'row: {row}')
@@ -339,41 +311,22 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
339
  raise e
340
 
341
  def _handle_head_middle_partition(
342
- self, part, docs_files, qs_files, dupes_files, listings_ids,
343
  ):
344
  assert len(docs_files) == len(qs_files)
345
 
346
  listings_ids = listings_ids[:len(docs_files)]
347
 
348
- for doc_file, qs_file, dupe_file, listings_id in zip(
349
- docs_files, qs_files, dupes_files, listings_ids
350
  ):
351
- # load duplicates
352
- try:
353
- with open(dupe_file, "rb") as df:
354
- duplicates = set(pq.read_table(
355
- df, columns=["doc_id"], use_pandas_metadata=False
356
- )["doc_id"].to_pylist())
357
- except Exception as e:
358
- print(f'failed loading duplicate ids from {dupe_file}.')
359
- duplicates = set()
360
-
361
  try:
362
  with gzip.open(doc_file, "rt", encoding="utf-8") as df:
363
  with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
364
  for row, (doc, qs) in enumerate(zip(df, qf)):
365
  doc_id = f"{listings_id}.json.gz/{row}"
366
-
367
- if doc_id in duplicates:
368
- is_duplicate = True
369
- else:
370
- is_duplicate = False
371
-
372
  try:
373
- yield self.handle_record(
374
- part, doc_id, doc, qs,
375
- is_duplicate=is_duplicate
376
- )
377
  except Exception as e:
378
  print(f'failed handling row {row} in '
379
  f'{doc_file} ({qs_file})')
@@ -386,7 +339,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
386
  continue
387
 
388
  @staticmethod
389
- def handle_record(part, doc_id, doc, qs, is_duplicate=None):
390
  doc = json.loads(doc)
391
  qs = json.loads(qs) if qs is not None else {}
392
 
@@ -399,12 +352,11 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
399
  "digest": doc["digest"],
400
  }
401
 
402
- quality_signals = qs.get("quality_signals", {})
403
- quality_signals["is_duplicate"] = is_duplicate
404
 
405
  return {
406
  "raw_content": doc["raw_content"],
407
  "doc_id": doc_id,
408
  "meta": json.dumps(meta),
409
- "quality_signals": json.dumps(quality_signals),
410
  }
 
23
  import gzip
24
  from typing import List
25
 
 
 
26
  logger = datasets.logging.get_logger(__name__)
27
 
28
  _DESCRIPTION = """\
 
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
  ]
 
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
 
 
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(
 
263
  gen_kwargs={
264
  "listings_ids": listings_ids,
265
  "documents_files": documents_files,
266
+ "quality_signals_files": quality_signals_files
 
267
  }
268
  )
269
  ]
 
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(
 
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
 
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}')
 
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})')
 
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
  "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
  }