horovod
thinc
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| horovod | thinc | |
|---|---|---|
| 1 | 4 | |
| 11,889 | 2,789 | |
| - | 0.5% | |
| 9.4 | 7.6 | |
| over 2 years ago | 3 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | 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.
horovod
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[P] Cost of distributed deep learning on AWS
Code for https://arxiv.org/abs/1802.05799 found: https://github.com/uber/horovod
thinc
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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
What are some alternatives?
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
quantulum3 - Library for unit extraction - fork of quantulum for python3
rxray - Ray distributed computing integration for RxPY
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
seq2seq - A general-purpose encoder-decoder framework for Tensorflow
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
extending-jax - Extending JAX with custom C++ and CUDA code
ray_snowflake - Ray Data Connector for Snowflake
dm-haiku - JAX-based neural network library
client - DagsHub client libraries
AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.