lhoestq HF staff commited on
Commit
69ce3af
1 Parent(s): 956a6cf

Local paths in common voice (#3736)

Browse files

* Merge generators for local files and streaming

* add the streaming parameter to _split_generators

* update common_voice

* patrick's comment:
- pass streaming to _generate_examples
- separate in two methods

* add is_streaming attribute to the dl managers

* revert the streaming parameter being passed to _split_generators

Co-authored-by: anton-l <aglozhkov@gmail.com>

Commit from https://github.com/huggingface/datasets/commit/e3c8e2541573b42b8dc23a4a29e197537d309bca

Files changed (1) hide show
  1. common_voice.py +93 -17
common_voice.py CHANGED
@@ -15,6 +15,8 @@
15
  """ Common Voice Dataset"""
16
 
17
 
 
 
18
  import datasets
19
  from datasets.tasks import AutomaticSpeechRecognition
20
 
@@ -657,63 +659,135 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
657
 
658
  def _split_generators(self, dl_manager):
659
  """Returns SplitGenerators."""
660
- archive = dl_manager.download(_DATA_URL.format(self.config.name))
661
- path_to_data = "/".join(["cv-corpus-6.1-2020-12-11", self.config.name])
662
- path_to_clips = "/".join([path_to_data, "clips"])
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
663
 
664
  return [
665
  datasets.SplitGenerator(
666
  name=datasets.Split.TRAIN,
667
  gen_kwargs={
668
- "files": dl_manager.iter_archive(archive),
669
- "filepath": "/".join([path_to_data, "train.tsv"]),
 
670
  "path_to_clips": path_to_clips,
671
  },
672
  ),
673
  datasets.SplitGenerator(
674
  name=datasets.Split.TEST,
675
  gen_kwargs={
676
- "files": dl_manager.iter_archive(archive),
677
- "filepath": "/".join([path_to_data, "test.tsv"]),
 
678
  "path_to_clips": path_to_clips,
679
  },
680
  ),
681
  datasets.SplitGenerator(
682
  name=datasets.Split.VALIDATION,
683
  gen_kwargs={
684
- "files": dl_manager.iter_archive(archive),
685
- "filepath": "/".join([path_to_data, "dev.tsv"]),
 
686
  "path_to_clips": path_to_clips,
687
  },
688
  ),
689
  datasets.SplitGenerator(
690
  name="other",
691
  gen_kwargs={
692
- "files": dl_manager.iter_archive(archive),
693
- "filepath": "/".join([path_to_data, "other.tsv"]),
 
694
  "path_to_clips": path_to_clips,
695
  },
696
  ),
697
  datasets.SplitGenerator(
698
  name="validated",
699
  gen_kwargs={
700
- "files": dl_manager.iter_archive(archive),
701
- "filepath": "/".join([path_to_data, "validated.tsv"]),
 
702
  "path_to_clips": path_to_clips,
703
  },
704
  ),
705
  datasets.SplitGenerator(
706
  name="invalidated",
707
  gen_kwargs={
708
- "files": dl_manager.iter_archive(archive),
709
- "filepath": "/".join([path_to_data, "invalidated.tsv"]),
 
710
  "path_to_clips": path_to_clips,
711
  },
712
  ),
713
  ]
714
 
715
- def _generate_examples(self, files, filepath, path_to_clips):
716
  """Yields examples."""
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
717
  data_fields = list(self._info().features.keys())
718
 
719
  # audio is not a header of the csv files
@@ -722,7 +796,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
722
 
723
  all_field_values = {}
724
  metadata_found = False
725
- for path, f in files:
726
  if path == filepath:
727
  metadata_found = True
728
  lines = f.readlines()
@@ -752,5 +826,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
752
 
753
  # set audio feature
754
  result["audio"] = {"path": path, "bytes": f.read()}
 
 
755
 
756
  yield path, result
 
15
  """ Common Voice Dataset"""
16
 
17
 
18
+ import os
19
+
20
  import datasets
21
  from datasets.tasks import AutomaticSpeechRecognition
22
 
 
659
 
660
  def _split_generators(self, dl_manager):
661
  """Returns SplitGenerators."""
662
+ streaming = dl_manager.is_streaming
663
+ archive_path = dl_manager.download(_DATA_URL.format(self.config.name))
664
+ if streaming:
665
+ # Here we use iter_archive in streaming mode because dl_manager.download_and_extract
666
+ # doesn't work to stream TAR archives (we have to stream the files in the archive one by one).
667
+ #
668
+ # The iter_archive method returns an iterable of (path_within_archive, file_obj) for every
669
+ # file in the TAR archive.
670
+ #
671
+ archive_iterator = dl_manager.iter_archive(archive_path)
672
+ # we locate the data using the path within the archive
673
+ path_to_data = "/".join(["cv-corpus-6.1-2020-12-11", self.config.name])
674
+ path_to_clips = "/".join([path_to_data, "clips"])
675
+ metadata_filepaths = {
676
+ split: "/".join([path_to_data, f"{split}.tsv"])
677
+ for split in ["train", "test", "dev", "other", "validated", "invalidated"]
678
+ }
679
+ else:
680
+ # In non-streaming we can extract the archive locally as usual
681
+ extracted_dir = dl_manager.extract(archive_path)
682
+ archive_iterator = None
683
+ # we locate the data using the local path
684
+ path_to_data = os.path.join(extracted_dir, "cv-corpus-6.1-2020-12-11", self.config.name)
685
+ path_to_clips = os.path.join(path_to_data, "clips")
686
+ metadata_filepaths = {
687
+ split: os.path.join(path_to_data, f"{split}.tsv")
688
+ for split in ["train", "test", "dev", "other", "validated", "invalidated"]
689
+ }
690
 
691
  return [
692
  datasets.SplitGenerator(
693
  name=datasets.Split.TRAIN,
694
  gen_kwargs={
695
+ "streaming": streaming,
696
+ "archive_iterator": archive_iterator,
697
+ "filepath": metadata_filepaths["train"],
698
  "path_to_clips": path_to_clips,
699
  },
700
  ),
701
  datasets.SplitGenerator(
702
  name=datasets.Split.TEST,
703
  gen_kwargs={
704
+ "streaming": streaming,
705
+ "archive_iterator": archive_iterator,
706
+ "filepath": metadata_filepaths["test"],
707
  "path_to_clips": path_to_clips,
708
  },
709
  ),
710
  datasets.SplitGenerator(
711
  name=datasets.Split.VALIDATION,
712
  gen_kwargs={
713
+ "streaming": streaming,
714
+ "archive_iterator": archive_iterator,
715
+ "filepath": metadata_filepaths["dev"],
716
  "path_to_clips": path_to_clips,
717
  },
718
  ),
719
  datasets.SplitGenerator(
720
  name="other",
721
  gen_kwargs={
722
+ "streaming": streaming,
723
+ "archive_iterator": archive_iterator,
724
+ "filepath": metadata_filepaths["other"],
725
  "path_to_clips": path_to_clips,
726
  },
727
  ),
728
  datasets.SplitGenerator(
729
  name="validated",
730
  gen_kwargs={
731
+ "streaming": streaming,
732
+ "archive_iterator": archive_iterator,
733
+ "filepath": metadata_filepaths["validated"],
734
  "path_to_clips": path_to_clips,
735
  },
736
  ),
737
  datasets.SplitGenerator(
738
  name="invalidated",
739
  gen_kwargs={
740
+ "streaming": streaming,
741
+ "archive_iterator": archive_iterator,
742
+ "filepath": metadata_filepaths["invalidated"],
743
  "path_to_clips": path_to_clips,
744
  },
745
  ),
746
  ]
747
 
748
+ def _generate_examples(self, streaming, archive_iterator, filepath, path_to_clips):
749
  """Yields examples."""
750
+ if streaming:
751
+ yield from self._generate_examples_streaming(archive_iterator, filepath, path_to_clips)
752
+ else:
753
+ yield from self._generate_examples_non_streaming(filepath, path_to_clips)
754
+
755
+ def _generate_examples_non_streaming(self, filepath, path_to_clips):
756
+
757
+ data_fields = list(self._info().features.keys())
758
+
759
+ # audio is not a header of the csv files
760
+ data_fields.remove("audio")
761
+ path_idx = data_fields.index("path")
762
+
763
+ with open(filepath, encoding="utf-8") as f:
764
+ lines = f.readlines()
765
+ headline = lines[0]
766
+
767
+ column_names = headline.strip().split("\t")
768
+ assert (
769
+ column_names == data_fields
770
+ ), f"The file should have {data_fields} as column names, but has {column_names}"
771
+
772
+ for id_, line in enumerate(lines[1:]):
773
+ field_values = line.strip().split("\t")
774
+
775
+ # set absolute path for mp3 audio file
776
+ field_values[path_idx] = os.path.join(path_to_clips, field_values[path_idx])
777
+
778
+ # if data is incomplete, fill with empty values
779
+ if len(field_values) < len(data_fields):
780
+ field_values += (len(data_fields) - len(field_values)) * ["''"]
781
+
782
+ result = {key: value for key, value in zip(data_fields, field_values)}
783
+
784
+ # set audio feature
785
+ result["audio"] = field_values[path_idx]
786
+
787
+ yield id_, result
788
+
789
+ def _generate_examples_streaming(self, archive_iterator, filepath, path_to_clips):
790
+ """Yields examples in streaming mode."""
791
  data_fields = list(self._info().features.keys())
792
 
793
  # audio is not a header of the csv files
 
796
 
797
  all_field_values = {}
798
  metadata_found = False
799
+ for path, f in archive_iterator:
800
  if path == filepath:
801
  metadata_found = True
802
  lines = f.readlines()
 
826
 
827
  # set audio feature
828
  result["audio"] = {"path": path, "bytes": f.read()}
829
+ # set path to None since the path doesn't exist locally in streaming mode
830
+ result["path"] = None
831
 
832
  yield path, result