Deephyper

Latest version: v0.10.0

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0.3.0

This new release help us move toward a more stable version of DeepHyper.

* Refactored the [DeepHyper Documentation](http://deephyper.readthedocs.io)
* Developed notebook tutorials
* Decoupled the command line and Python interfaces
* Refactored the `Evaluator` interface with `evaluator.submit/gather`
* Added `deephyper.ensemble` for ensembles with uncertainty quantification
* Removed `deephyper.post`

0.2.5

General

Full API documentation

The DeepHyper API is now fully documented at [DeepHyper API](https://deephyper.readthedocs.io/en/latest/api/deephyper.html)

Tensorflow-Probability as a new dependency

[TensorFlow Probability](https://www.tensorflow.org/probability) is now part of DeepHyper default set of dependencies

Automated submission with Ray at ALCF

It is now possible to directly submit with `deephyper ray-submit ...` for DeepHyper at the ALCF. This feature is only available on ThetaGPU for now but can be extended to other systems by following [this script](https://github.com/deephyper/deephyper/blob/c7608e0c61bd805c109145744b567cbb6cf01673/deephyper/core/cli/ray_submit.py).

ThetaGPU at ALCF

* New installation documentation is available at [Installation ThetaGPU (ALCF)](https://deephyper.readthedocs.io/en/latest/install/thetagpu.html)
* A new user guide is available at [Running on ThetaGPU (ALCF)](https://deephyper.readthedocs.io/en/latest/user_guides/thetagpu.html) to understand how to run manually and automatically DeepHyper on ThetaGPU.

New documentation for auto-sklearn search with DeepHyper

The access to auto-sklearn features was changed to `deephyper.sklearn` and a new documentation is available for this feature at [User guide: AutoSklearn](https://deephyper.readthedocs.io/en/latest/user_guides/autosklearn.html)

New command lines for DeepHyper Analytics

The `deephyper-analytics` command was modified and enhanced with new features. The see the full updated documentation follow [DeepHyper Analytics Tools](https://deephyper.readthedocs.io/en/latest/user_guides/analytics.html).

The `topk` command is now available to have quick feedback from the results of an experiment:

$ deephyper-analytics topk combo_8gpu_8_agebo/infos/results.csv -k 2
'0':
arch_seq: '[229, 0, 22, 1, 1, 53, 29, 1, 119, 1, 0, 116, 123, 1, 273, 0, 1, 388]'
batch_size: 59

0.2.1

Minor bug corrections

0.2.0

* Compatible with Tensorflow 2.
* Horovod compatibility with Balsam evaluator for Theta.
* Horovod and Balsam are now optional installations.
* Update of the AMBS algorithm for Hyperparameter search for better scalability.
* Removing the PPO search for Neural Architecture Search.
* Creating the `SpaceFactory` interface for the `deepspace` package which provides ready to go neural architecture search spaces.
* Local distribution of jobs with Ray and multiprocessors CPUs.

0.1.13

New NAS Algorithm

* Aging Evolution with Bayesian Optimization (AgEBO)

New AMBS implementation

* Previous AMBS renamed to `ambsv1`
* New implementation of AMBS for better scaling capabilities

Data-Parallelism settings for Balsam and Horovod

Graph convolution layers with message passin

0.1.12

A release for the creation of a DOI on Zeno.

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