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v4.4.0

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@Conchylicultor Conchylicultor released this 28 Jul 12:29
v4.4.0
76f8591

API:

  • Add PartialDecoding support, to decode only a subset of the features (for performances)
  • Catalog now expose links to KnowYourData visualisations
  • tfds.as_numpy supports datasets with None
  • Dataset generated with disable_shuffling=True are now read in generation order.
  • Loading datasets from files now supports custom tfds.features.FeatureConnector
  • tfds.testing.mock_data now supports
    • non-scalar tensors with dtype tf.string
    • builder_from_files and path-based community datasets
  • File format automatically restored (for datasets generated with tfds.builder(..., file_format=)).
  • Many new reinforcement learning datasets
  • Various bug fixes and internal improvements like:
    • Dynamically set number of worker thread during extraction
    • Update progression bar during download even if downloads are cached

Dataset creation:

  • Add tfds.features.LabeledImage for semantic segmentation (like image but with additional info.features['image_label'].name label metadata)
  • Add float32 support for tfds.features.Image (e.g. for depth map)
  • All FeatureConnector can now have a None dimension anywhere (previously restricted to the first position).
  • tfds.features.Tensor() can have arbitrary number of dynamic dimension (Tensor(..., shape=(None, None, 3, None)))
  • tfds.features.Tensor can now be serialised as bytes, instead of float/int values (to allow better compression): Tensor(..., encoding='zlib')
  • Add script to add TFDS metadata files to existing TF-record (see doc).
  • New guide on common implementation gotchas

Thank you all for your support and contribution!

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