nnabla
thinc
nnabla | thinc | |
---|---|---|
1 | 4 | |
2,694 | 2,794 | |
0.3% | 0.5% | |
8.2 | 7.6 | |
14 days ago | 9 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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nnabla
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?
black - The uncompromising Python code formatter
quantulum3 - Library for unit extraction - fork of quantulum for python3
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
extending-jax - Extending JAX with custom C++ and CUDA code
shumai - Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight
dm-haiku - JAX-based neural network library
loop_tool - A thin, highly portable toolkit for efficiently compiling dense loop-based computation.
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.