PPO-PyTorch
pytorch-accelerated
| PPO-PyTorch | pytorch-accelerated | |
|---|---|---|
| 2 | 1 | |
| 1,493 | 160 | |
| - | - | |
| 2.8 | 3.7 | |
| 5 months ago | 15 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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PPO-PyTorch
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Where does the loss function for Policy Gradient come from?
It's just very convient implementation wise, in just a few lines you can get the "loss": (from https://github.com/nikhilbarhate99/PPO-PyTorch/blob/master/PPO.py)
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A2C/PPO with continuous action space
In some methods, like the one here, the actor network has two heads, one for the mean and one for the variance. In other methods, like the one here, the network only outputs the mean, while the variance is pre-defined and is decaying throughout the training.
pytorch-accelerated
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I highly and genuinely recommend Fast.ai course to beginners
I would love to know your thoughts on PyTorch Lightning vs. other, even more lightweight libraries, if you have the time. PL strikes me as being less idiosyncratic than FastAI, but I'm still not sure whether it would be better in engineering work to go even more lightweight (when I'm not just writing the code myself) -- something that offers up just optimizations and a trainer, a la MosaicML's [Composer](https://github.com/mosaicml/composer) or Chris Hughes's [pytorch-accelerated](https://github.com/Chris-hughes10/pytorch-accelerated) .
What are some alternatives?
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
composer - Supercharge Your Model Training
l2rpn-baselines - L2RPN Baselines a repository to host baselines for l2rpn competitions.
pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
Pytorch-PCGrad - Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
avalanche - Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
nos - Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas - Effortless optimization at its finest!
nes-torch - Minimal PyTorch Library for Natural Evolution Strategies
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
autonomous-learning-library - A PyTorch library for building deep reinforcement learning agents.
Machine-Learning-Collection - A resource for learning about Machine learning & Deep Learning