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Releases: baal-org/baal

Baal 2.0: Experiment API

11 Jun 15:47
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Quite a large update with a renewed experience for researchers: Experiment API.

Nonetheless, production users will benefit from EPIG, the new SotA in Active Learning!

Experiment API
The new experiment object will simplify your experiments by reducing it to a 1-liner.

Experiment API

EPIG
Contribution from @reeshipaul @Dref360 and @fbickfordsmith, EPIG is the new state-of-the-art in Bayesian Active Learning.
It better estimates the predictive uncertainty than PowerBALD and considers the labeled training set.

EPIG

Stopping Criterion
A new object that helps you stop an experiment when reaching your labeling budget or a plateau in uncertainty/performance.

Stopping criterion

Breaking Changes

  • Arguments in ModelWrapper.*_on_dataset have been for the most part moved to TrainingArguments and are included in ModelWrapper constructor. Visit the documentation for more details.

What's Changed

Full Changelog: v1.9.2...v2.0.0

v1.9.2

04 Apr 17:31
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What's Changed

Full Changelog: v1.9.1...v1.9.2

v1.9.1 Heuristic Aliases!

02 Oct 19:58
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v1.9.0

15 Sep 21:57
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What's Changed

Full Changelog: v1.8.0...v1.9.0

V1.8.0

13 Jul 22:01
56d3767
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New features

  • MCCachingModule: Cache computation between Monte Carlo iteration link. Special thanks to @pieterblok for introducing this capability!
  • We can now evaluation every x epochs in ModelWrapper.train_and_test_on_datasets.

What's Changed

  • Fix doc for NLP example by @Dref360 in #241
  • #246 Fix issue where training was not kept consistent by @Dref360 in #249
  • Baal in Production Notebook | Classification | NLP | Hugging Face by @nitish1295 in #245
  • Add code walkthrough for CIFAR10 by @Dref360 in #253
  • Deprecate shuffle prop in favor of PowerSampling by @Dref360 in #260
  • docs: use correct link to experiment script by @arthur-thuy in #267
  • added setting to skip x epochs when using train_and_test_on_datasets by @studentWUR in #258
  • Add caching mechanism for MCDropout by @Dref360 in #268
  • Improve get_indices_for_active_step by caching the result according t… by @Dref360 in #269

New Contributors

Deprecation

We will deprecate shuffle_prop in favor of PowerSampling. Look here to know more about PowerBALD!

Full Changelog: v1.7.0...v1.8.0

v1.7.0

28 Oct 21:55
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Large release where we added support for torchmetrics, moved to mkdocs and made the app more robust!

We also updated our visual identity, huge thanks to @Donasolo for the new logos!

What's Changed

New Contributors

Full Changelog: v1.6.0...v1.7.0

v1.6.0

03 May 12:50
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What's Change

Full Changelog: v1.5.2...v1.6.0

V1.5.2

12 Apr 13:02
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What's Changed

  • Better indexing support arrow dataset by @parmidaatg in #183
  • Raises an error instead of a warning when label has no label by @Dref360 in #187
  • #192 Use configure instead of configure_once to remove warnings by @Dref360 in #193
  • #190 Fix MRO for Lightning examples and deprecate said example by @Dref360 in #191
  • Can easily unpatch modules and use as a context manager #198 #194 :
mc_dropout_model = MCDropoutModule(your_model)
# this is stochastic
predictions = [mc_dropout_model(input) for _ in range(ITERATIONS)]

model = mc_dropout_model.unpatch()
# this is deterministic
output = model(input)


# Context manager
with MCDropoutModule(your_model) as model:
    # this is stochastic
    predictions = [model(input) for _ in range(ITERATIONS)]
# this is deterministic
output = model(input)

Full Changelog: 1.5.1...v1.5.2

v1.5.1

17 Dec 20:29
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What's Changed

  • Solve bug where a dataset wouldnt be able to label by @Dref360 in #178

Full Changelog: 1.5.0...1.5.1

v1.5.0

13 Dec 13:46
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What's Changed

Deprecated

  1. We now deprecate our PL integration in favor of Lightning Flash. More information to come.
  2. We renamed n_data_to_label to query_size to match academic papers notation.

Full Changelog: 1.4.0...1.5.0