loop_tool
thinc
| loop_tool | thinc | |
|---|---|---|
| 4 | 4 | |
| 145 | 2,794 | |
| - | 0.5% | |
| 0.0 | 7.6 | |
| over 1 year ago | 7 days ago | |
| C++ | Python | |
| MIT License | MIT License |
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loop_tool
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Tinygrad: A simple and powerful neural network framework
I've done some work in the past in representations and you actually can represent Conv and MatMul in more primitive ways. I ended up writing an IR called loop_tool that exposes this stuff pretty nicely:
https://github.com/facebookresearch/loop_tool/blob/main/pyth...
The idea is basically this: https://news.ycombinator.com/item?id=28883086
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Interactive Loop Optimization
I just finished adding a basic WASM[1] backend + basic JavaScript frontend[2]. I'm in the process of adding in-browser optimization[3] and will hope to have a demo some time this week!
[1] https://github.com/facebookresearch/loop_tool/blob/main/src/...
[2] https://github.com/facebookresearch/loop_tool/blob/main/java...
[3] https://github.com/facebookresearch/loop_tool/blob/main/test...
- Loop_tool: A toolkit for loop-based computation
- Loop_tool tutorial – a lazy symbolic linear algebra toolkit
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?
shumai - Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight
quantulum3 - Library for unit extraction - fork of quantulum for python3
black - The uncompromising Python code formatter
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
extending-jax - Extending JAX with custom C++ and CUDA code
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
dm-haiku - JAX-based neural network library
nnabla - Neural Network 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.