AutoDL-Projects
Hyperactive
| AutoDL-Projects | Hyperactive | |
|---|---|---|
| 3 | 8 | |
| 1,546 | 490 | |
| - | - | |
| 1.8 | 7.7 | |
| about 2 years ago | 5 months ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
AutoDL-Projects
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Forward pass computation for GDAS NAS coding
https://github.com/D-X-Y/AutoDL-Projects/issues/99#issuecomment-835802887
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Backpropagation for Network Architecture Search (NAS)
However in GDAS, there are multiple parallel edges in between two nodes.
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Gumbel-Max implementation
Could anyone explain how this Gumbel-Max code implementation works ?
Hyperactive
- Hyperactive Version 4.5 Released
- Hyperactive: An optimization and data collection toolbox for AutoML
- Hyperactive: Optimize computationally expensive models with powerful algorithms
- Show HN: Hyperactive – A highly versatile AutoML Toolbox
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Hyperactive – Easy Neural Architecture Search for Deep Learning in Python
Check out the Neural Architecture Search Tutorial here: https://nbviewer.jupyter.org/github/SimonBlanke/hyperactive-...
Neural Architecture Search is just one of many optimization applications you can work on with Hyperactive. Check out the examples in the official github repository: https://github.com/SimonBlanke/Hyperactive/tree/master/examp...
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Gradient-Free-Optimizers A collection of modern optimization methods in Python
Gradient-Free-Optimizers is a lightweight optimization package that serves as a backend for Hyperactive: https://github.com/SimonBlanke/Hyperactive
Hyperactive can do parallel computing with multiprocessing or joblib, or a custom wrapper-function.
What are some alternatives?
makeZFS_armbian - RockPro64 Based NAS setup guide with ZFS
mango - Parallel Hyperparameter Tuning in Python
archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
optuna-examples - Examples for https://github.com/optuna/optuna
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Auto_ViML - Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.