lightning-bolts
Toolbox of models, callbacks, and datasets for AI/ML researchers. (by Lightning-Universe)
thinc
đź”® A refreshing functional take on deep learning, compatible with your favorite libraries (by explosion)
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lightning-bolts | thinc | |
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3 | 4 | |
1,640 | 2,787 | |
1.4% | 0.5% | |
7.5 | 6.9 | |
15 days ago | 5 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
lightning-bolts
Posts with mentions or reviews of lightning-bolts.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-10.
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Question about implementing RL algorithms
In the lightning-bolts repository, they implement the different RL algorithms, such as PPO and DQN, as different models. Would it make more sense to have the different algorithms be the Trainer instead? Inside each of the implementations, the model creates the same neural network with different training steps.
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[P] An elegant and strong PyTorch Trainer
This is also how lightning bolts tend to be defined: for example, you have https://github.com/Lightning-AI/lightning-bolts/blob/master/pl_bolts/models/rl/advantage_actor_critic_model.py for A3C, which itself is only the loss and training wrapper around the normal modules for critic and actor (see https://github.com/Lightning-AI/lightning-bolts/blob/52e4c503c671f4866339c1537cf6ae506e7c5cf5/pl_bolts/models/rl/common/networks.py#L147=)
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[D] How to organize deep learning projects on Github ?
Also PyTorch Lighting gives example in this repo https://github.com/PyTorchLightning/pytorch-lightning-bolts
thinc
Posts with mentions or reviews of thinc.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-28.
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
Agree, though I wouldn’t call PyTorch a drop-in for NumPy either. CuPy is the drop-in. Excepting some corner cases, you can use the same code for both. Thinc’s ops work with both NumPy and CuPy:
https://github.com/explosion/thinc/blob/master/thinc/backend...
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Tinygrad: A simple and powerful neural network framework
I love those tiny DNN frameworks, some examples that I studied in the past (I still use PyTorch for work related projects) :
thinc.by the creators of spaCy https://github.com/explosion/thinc
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good examples of functional-like python code that one can study?
thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable
- thinc - A refreshing functional take on deep learning, compatible with your favorite libraries