Changelog

Version 1.0.0 - 2022-06-14

First stable release.

Changed

  • Datasets:

    • SklearnDataset now checks if the dimensions of the features and labels match.

  • Query Strategies:

  • Documentation:

    • The documentation is now available in full width.

  • Repository:

    • Versions in this can now be referenced using the respective Zenodo DOI.

[1.0.0b4] - 2022-05-04

Added

  • General:

    • We now have a concept for optional dependencies which allows components to rely on soft dependencies, i.e. python dependencies which can be installed on demand (and only when certain functionality is needed).

  • Datasets:

    • The Dataset interface now has a clone() method that creates an identical copy of the respective dataset.

  • Query Strategies:

Changed

  • Datasets:

    • Separated the previous DatasetView implementation into interface (DatasetView) and implementation (SklearnDatasetView).

    • Added clone() method which creates an identical copy of the dataset.

  • Query Strategies:

    • EmbeddingBasedQueryStrategy now only embeds instances that are either in the label or in the unlabeled pool (and no longer the entire dataset).

  • Code examples:

    • Code structure was unified.

    • Number of iterations can now be passed via an cli argument.

  • small_text.integrations.pytorch.utils.data:

    • Method get_class_weights() now scales the resulting multi-class weights so that the smallest class weight is equal to 1.0.

[1.0.0b3] - 2022-03-06

Added

Changed

  • Cleaned up and unified argument naming: The naming of variables related to datasets and indices has been improved and unified. The naming of datasets had been inconsistent, and the previous x_ notation for indices was a relict of earlier versions of this library and did not reflect the underlying object anymore.

    • PoolBasedActiveLearner:

      • attribute x_indices_labeled was renamed to indices_labeled

      • attribute x_indices_ignored was unified to indices_ignored

      • attribute queried_indices was unified to indices_queried

      • attribute _x_index_to_position was named to _index_to_position

      • arguments x_indices_initial, x_indices_ignored, and x_indices_validation were renamed to indices_initial, indices_ignored, and indices_validation. This affects most methods of the PoolBasedActiveLearner.

    • QueryStrategy

      • old: query(self, clf, x, x_indices_unlabeled, x_indices_labeled, y, n=10)

      • new: query(self, clf, dataset, indices_unlabeled, indices_labeled, y, n=10)

    • StoppingCriterion

      • old: stop(self, active_learner=None, predictions=None, proba=None, x_indices_stopping=None)

      • new: stop(self, active_learner=None, predictions=None, proba=None, indices_stopping=None)

  • Renamed environment variable which sets the small-text temp folder from ALL_TMP to SMALL_TEXT_TEMP

[1.0.0b2] - 2022-02-22

Bugfix release.

Fixed

  • Fix links to the documentation in README.md and notebooks.

[1.0.0b1] - 2022-02-22

First beta release with multi-label functionality and stopping criteria.

Added

  • Added a changelog.

  • All provided classifiers are now capable of multi-label classification.

Changed

  • Documentation has been overhauled considerably.

  • PoolBasedActiveLearner: Renamed incremental_training kwarg to reuse_model.

  • SklearnClassifier: Changed __init__(clf) to __init__(model, num_classes, multi_Label=False)

  • SklearnClassifierFactory: __init__(clf_template, kwargs={}) to __init__(base_estimator, num_classes, kwargs={}).

  • Refactored KimCNNClassifier and TransformerBasedClassification.

Removed

  • Removed device kwarg from PytorchDataset.__init__(), PytorchTextClassificationDataset.__init__() and TransformersDataset.__init__().