lambda-packs
thinc
| lambda-packs | thinc | |
|---|---|---|
| 1 | 4 | |
| 1,106 | 2,789 | |
| - | 0.3% | |
| 4.0 | 7.6 | |
| 6 months ago | 9 days ago | |
| Python | Python | |
| MIT License | MIT License |
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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.
lambda-packs
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Using TensorFlow and the Serverless Framework for deep learning and image recognition
As a hobby, I port a lot of libraries to make the serverless friendly. You can look at them here. They all have an MIT license, so feel free to modify and use them for your project.
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?
equilib - 🌎→🗾Equirectangular (360/panoramic) image processing library for Python with minimal dependencies only using Numpy and PyTorch
quantulum3 - Library for unit extraction - fork of quantulum for python3
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
extending-jax - Extending JAX with custom C++ and CUDA code
Photomosaic-Creator - This script allows you to create a photomosaic from a set of images.
dm-haiku - JAX-based neural network library
external_documentation_redirect - Python external documentation redirect for JetBrains IDEs
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.