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Recent Releases of https://github.com/awslabs/renate

https://github.com/awslabs/renate - Release 0.5.2

Minor release that upgrades versions of sagemaker, requests, Pillow, and transformers to account for vulnerabilities.

- Python
Published by wistuba almost 2 years ago

https://github.com/awslabs/renate - Release 0.5.1

Minor release that changes versions of Pillow and transformers library to account for untrusted data vulnerability in transformers<4.36.0 and arbitrary code execution in Pillow<10.2.0.

- Python
Published by wistuba over 2 years ago

https://github.com/awslabs/renate - v0.5.0

🤩 Highlights

In this release we focused on the addition of methods for continual learning that do not require storing data in memory. In particular, we implemented methods that can work in combination with pre-trained transformer models.

🌟 New Features

  • Logging additional metrics by @prabhuteja12 in https://github.com/awslabs/Renate/pull/448
  • S-Prompts for ViT and Text Transformers by @prabhuteja12 in https://github.com/awslabs/Renate/pull/388

🛢 Datasets

  • Adding CDDB dataset by @prabhuteja12 in https://github.com/awslabs/Renate/pull/442
  • Core50 dataset by @prabhuteja12 in https://github.com/awslabs/Renate/pull/447

📜 Documentation Updates

  • Documentation changes by @prabhuteja12 in https://github.com/awslabs/Renate/pull/450

🐛 Bug Fixes

  • CLEAR and TinyImageNet tests bugfixes by @prabhuteja12 in https://github.com/awslabs/Renate/pull/441
  • Fix CosineAnnealing issue in configs and add more configs by @wistuba in https://github.com/awslabs/Renate/pull/449
  • Fixing Issue of Avalanche Updater with Datasets that return PIL Images by @wistuba in https://github.com/awslabs/Renate/pull/457
  • Avoid In-Memory Dataset Copy for Avalanche by @wistuba in https://github.com/awslabs/Renate/pull/463
  • Update Flaky Tests by @wistuba in https://github.com/awslabs/Renate/pull/495
  • Speeding up unitests by @prabhuteja12 in https://github.com/awslabs/Renate/pull/432

Full Changelog: https://github.com/awslabs/Renate/compare/v0.4.0...v0.5.0

- Python
Published by 610v4nn1 over 2 years ago

https://github.com/awslabs/renate - Release 0.4.0

🤩 Highlights

Renate 0.4.0 adds multi-gpu training via deepspeed, data shift detectors, L2P as a new updater, and a couple of new datasets for benchmarking (WildTimeData, CLEAR, DomainNet, 4TextDataset).

🌟 New Features

  • MultiGPU training with deepspeed by @prabhuteja12 in https://github.com/awslabs/Renate/pull/218
  • Renate NLP Models and Benchmarking Support for Hugging Face by @wistuba in https://github.com/awslabs/Renate/pull/213 https://github.com/awslabs/Renate/pull/233
  • Covariate Shift Detectors by @lballes: MMD (https://github.com/awslabs/Renate/pull/237), KS (https://github.com/awslabs/Renate/pull/242)
  • New Updater: Learning to Prompt (L2P) by @prabhuteja12 in https://github.com/awslabs/Renate/pull/367
  • Upload custom files and folders with a SageMaker training Job by @wistuba in https://github.com/awslabs/Renate/pull/286
  • Custom Optimizer and LR schedulers by @wistuba in https://github.com/awslabs/Renate/pull/290
  • Flag to remove intermediate tasks' states by @prabhuteja12 in https://github.com/awslabs/Renate/pull/289
  • Make number of epochs "finetuning-equivalent" by @lballes in https://github.com/awslabs/Renate/pull/344
  • Add Micro Average Accuracy by @wistuba in https://github.com/awslabs/Renate/pull/323
  • Experimentation Tools by @wistuba in https://github.com/awslabs/Renate/pull/356

🛢 Datasets

  • Added 4 Wild Time Datasets by @wistuba in https://github.com/awslabs/Renate/pull/187
  • Enable CLEAR Datasets for Benchmarking by @prabhuteja12 in https://github.com/awslabs/Renate/pull/287
  • Add DomainNet Benchmark by @wistuba in https://github.com/awslabs/Renate/pull/357
  • Add benchmark made of multiple text datasets by @610v4nn1 in https://github.com/awslabs/Renate/pull/354
  • MultiText dataset Added to Benchmarking by @wistuba in https://github.com/awslabs/Renate/pull/366

📜 Documentation Updates

  • Add doc page and example for shift detection by @lballes in https://github.com/awslabs/Renate/pull/244
  • Add example of using renate in your own script by @lballes in https://github.com/awslabs/Renate/pull/274
  • Describe Installation of Dependencies for Benchmarking by @wistuba in https://github.com/awslabs/Renate/pull/313
  • Improve title for the NLP example by @610v4nn1 in https://github.com/awslabs/Renate/pull/416

🐛 Bug Fixes

  • Fix Offline-ER bug and change loss functions by @wistuba in https://github.com/awslabs/Renate/pull/273
  • Missing Argument Doesn't Allow for Remote Experiments by @wistuba in https://github.com/awslabs/Renate/pull/304
  • Fix Small Bug in Benchmarking Script and Add LR Scheduler to Experiment Config by @wistuba in https://github.com/awslabs/Renate/pull/305
  • Enable Downloading Large Files by @wistuba in https://github.com/awslabs/Renate/pull/337
  • Fix Scenario for CLEAR by @wistuba in https://github.com/awslabs/Renate/pull/339
  • Fix CLS-ER Loss by @wistuba in https://github.com/awslabs/Renate/pull/347
  • Fix weighting in OfflineER by @lballes in https://github.com/awslabs/Renate/pull/355
  • Fixing Bug with HPO by @wistuba in https://github.com/awslabs/Renate/pull/345
  • Adding a Datacollator to handle the wild time text datasets by @prabhuteja12 in https://github.com/awslabs/Renate/pull/338
  • Enable Offline-ER for NestedTensors by @wistuba in https://github.com/awslabs/Renate/pull/336
  • Refactor Offline-ER to work with collate_fn by @wistuba in https://github.com/awslabs/Renate/pull/390
  • Fixing the issue with Domainnet redownloading by @prabhuteja12 in https://github.com/awslabs/Renate/pull/389
  • CLEAR dataset download link update by @prabhuteja12 in https://github.com/awslabs/Renate/pull/431
  • Support Use of Joint and GDumb with Pre-Trained Models by @wistuba in https://github.com/awslabs/Renate/pull/362

🏗️ Code Refactoring

  • Remove obsolete set_transforms from memory buffer by @lballes in https://github.com/awslabs/Renate/pull/265
  • Missing dependency and problem with import by @wistuba in https://github.com/awslabs/Renate/pull/272
  • Using HuggingFace ViT implementation (#219) by @prabhuteja12 in https://github.com/awslabs/Renate/pull/303
  • Introduce RenateLightningModule by @wistuba in https://github.com/awslabs/Renate/pull/301
  • Cleanup iCarl by @wistuba in https://github.com/awslabs/Renate/pull/358
  • Abstracting prompting transformer for use in L2P and S-Prompt by @prabhuteja12 in https://github.com/awslabs/Renate/pull/420
  • Adding flags to expose gradient clipping args in Trainer by @prabhuteja12 in https://github.com/awslabs/Renate/pull/361
  • Wild Time Benchmarks and Small Memory Hack by @wistuba in https://github.com/awslabs/Renate/pull/363
  • Clean Up Learner Checkpoint and Fix Model Loading by @wistuba in https://github.com/awslabs/Renate/pull/365
  • Enable Custom Grouping for DataIncrementalScenario by @wistuba in https://github.com/awslabs/Renate/pull/368
  • Masking of logits of irrelevant classes by @prabhuteja12 in https://github.com/awslabs/Renate/pull/364
  • Modifies current text transformer implementation to a RenateBenchmarkingModule by @prabhuteja12 in https://github.com/awslabs/Renate/pull/380
  • Replace memory batch size with a fraction of the total batch size by @wistuba in https://github.com/awslabs/Renate/pull/359
  • Make offline ER us total batch size in first update by @lballes in https://github.com/awslabs/Renate/pull/381

🔧 Maintenance

  • Robust Integration Tests by @wistuba in https://github.com/awslabs/Renate/pull/214
  • Update Renate Config Example by @wistuba in https://github.com/awslabs/Renate/pull/226
  • Longer Experiments for GPUs by @wistuba in https://github.com/awslabs/Renate/pull/246
  • Using num_gpus_per_trial after SyneTune update by @prabhuteja12 in https://github.com/awslabs/Renate/pull/278
  • Implementing a buffer that handles dataset elements of different sizes by @prabhuteja12 in https://github.com/awslabs/Renate/pull/279
  • Run sagemaker tests from GitHub Actions by @wesk in https://github.com/awslabs/Renate/pull/275
  • Fix Security Problem with transformers by @wistuba in https://github.com/awslabs/Renate/pull/298

Full Changelog: https://github.com/awslabs/Renate/compare/v0.3.1...v0.4.0

- Python
Published by wistuba over 2 years ago

https://github.com/awslabs/renate - Release v0.3.1

What's Changed

  • Adding a missing dependency and fixing a case where a conditional requirement was unnecessarily required by @wistuba in https://github.com/awslabs/Renate/pull/284

Full Changelog: https://github.com/awslabs/Renate/compare/v0.3.0...v0.3.1

- Python
Published by wistuba almost 3 years ago

https://github.com/awslabs/renate - Release v0.3.0

What's Changed

  • Covariate shift detection by @lballes (https://github.com/awslabs/Renate/pull/237, https://github.com/awslabs/Renate/pull/242, https://github.com/awslabs/Renate/pull/244). Shift detection may help users decide when to update model. We now provide methods for covariate shift detection in renate.shift.
  • Wild Time benchmarking by @wistuba in https://github.com/awslabs/Renate/pull/187. Wild Time is a collection of datasets that exhibit temporal data distribution shifts. It is now available for benchmarking in Renate.
  • Improved NLP support by @wistuba (https://github.com/awslabs/Renate/pull/213, https://github.com/awslabs/Renate/pull/233). There's now a RenateModule for convenient usage of Hugging Face Transformers. NLP and models are now included in the benchmarking suite.
  • Bug fixes and minor improvements.

Full Changelog: https://github.com/awslabs/Renate/compare/v0.2.1...v0.3.0

- Python
Published by lballes about 3 years ago

https://github.com/awslabs/renate - Release v0.2.1

What's Changed

  • Update README.rst with paper ref by @610v4nn1
  • Add doc page explaining NLP example by @lballes
  • Bugfix, removed the need to specify the chunk id @wistuba

Full Changelog: https://github.com/awslabs/Renate/compare/v0.2.0...v0.2.1

- Python
Published by 610v4nn1 about 3 years ago

https://github.com/awslabs/renate - Release v0.2.0

Renate v0.2 is finally here! 🌟 In these 88 new commits we made a number of enhancements and fixes. It has been a great team effort and we are very happy to see that two more developers decided to contribute to Renate.

Highlights

  • Scalable data buffer (@lballes). Since replay-based methods are used in many practical applications, and having a larger memory buffer leads to better performance, we made sure Renate users will be able to use a replay-memory larger than the physical memory they have available on their machines. This will enable more folks to use Renate in practice, especially in combinations with large models and datasets.
  • Avalanche learning strategies are usable in Renate(@wistuba). Avalanche is a library for continual learning aiming at making research reproducible. While Renate focuses on real-world applications, it can still be useful to for users to compare with the training strategies implemented in Avalanche. To this purpose, Renate now allows the usage of Avalanche training strategies but not all the functionalities are available for Avalanche training strategies (see details here ).
  • Simplified interfaces (@610v4nn1, @wistuba). We simplified naming for attributes and methods to make the library more intuitive and easier to use. Usability is always among our priorities and we will be happy to get more feedback after these changes.
  • Additional tests (@wesk). We increased the amount of testing done for every PR and we are not running a number of quick training jobs. This will allow us to capture additional problems which may come from the interaction between different components of the library and which, usually, are not captured by unit tests.

There is way more to be discovered, from the examples using pre-trained text models (nlp_finetuning folder in the examples) to the additional Scenario classes created to test the algorithms in different environments.

New Contributors

  • @geoalgo made their first contribution in https://github.com/awslabs/Renate/pull/160
  • @wesk made their first contribution in https://github.com/awslabs/Renate/pull/188

Full Changelog

See the full changelog: https://github.com/awslabs/Renate/compare/v0.1.0...v0.2.0

- Python
Published by 610v4nn1 about 3 years ago

https://github.com/awslabs/renate - Initial Release

First public release of Renate. The library provides the ability to: * train and retrain neural network models * optimize the hyperparameters when training * run training jobs either locally or Amazon SageMaker

The package also contains documentation, examples, and scripts for experimentation.

Contributors (ordered by number of commits)

  • @martinferianc
  • @wistuba
  • @lballes
  • @610v4nn1
  • Beyza Ermis
  • Yantao Shen
  • Elman Mansimov
  • @mlblack

- Python
Published by wistuba over 3 years ago