Renate

Latest version: v0.5.2

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0.2.1

Not secure
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

0.2

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](https://renate.readthedocs.io/en/latest/getting_started/avalanche.html) ).
* **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

0.2.0

Not secure

0.1.0

Not secure
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

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