einops VS torchtyping

Compare einops vs torchtyping and see what are their differences.

einops

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others) (by arogozhnikov)

torchtyping

Type annotations and dynamic checking for a tensor's shape, dtype, names, etc. (by patrick-kidger)
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einops torchtyping
17 7
7,809 1,328
- -
8.2 3.2
about 2 months ago 9 months ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.

einops

Posts with mentions or reviews of einops. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-03.

torchtyping

Posts with mentions or reviews of torchtyping. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-11.
  • [D] Have their been any attempts to create a programming language specifically for machine learning?
    12 projects | /r/MachineLearning | 11 Feb 2023
    Not really an answer to your question, but there are Python packages that try to solve the problem of tensor shapes that you mentioned, e.g. https://github.com/patrick-kidger/torchtyping or https://github.com/deepmind/tensor_annotations
  • What's New in Python 3.11?
    14 projects | news.ycombinator.com | 26 Jun 2022
    I disagree. I've had a serious attempt at array typing using variadic generics and I'm not impressed. Python's type system has numerous issues... and now they just apply to any "ArrayWithNDimensions" type as well as any "ArrayWith2Dimenensions" type.

    Variadic protocols don't exist; many operations like stacking are inexpressible; the synatx is awful and verbose; etc. etc.

    I've written more about this here as part of my TorchTyping project: [0]

    [0] https://github.com/patrick-kidger/torchtyping/issues/37#issu...

  • [D] Anyone using named tensors or a tensor annotation lib productively?
    2 projects | /r/MachineLearning | 18 Apr 2022
    FWIW I'm the author of torchtyping so happy to answer any questions about that. :) I think people are using it!
  • [D] Ideal deep learning library
    9 projects | /r/MachineLearning | 5 Jan 2022
    The one thing I really *really* wish got more attention was named tensors and the tensor type system. Tensor misalignment errors are a constant source of silently-failing bugs. While 3rd party libraries have attempted to fill this gap, it really needs better native support. In particular it seems like bad form to me for programmers to have to remember the specific alignment and broadcasting rules, and then have to apply them to an often poorly documented order of tensor indices. I'd really like to see something like tsalib's warp operator made part of the main library and generalized to arbitrary function application, like a named-tensor version of fold. But preferably using notation closer to that of torchtyping.
  • [P] torchtyping -- documentation + runtime type checking of tensor shapes (and dtypes, ...)
    2 projects | /r/MachineLearning | 7 Apr 2021
    Hello everyone. I'm excited to announce torchtyping, as a way to document -- and check -- that PyTorch tensors have the correct shape (dtype, names, layout, ...).
    2 projects | /r/MachineLearning | 7 Apr 2021
    Yes it does work with numerical literals! It support using integers to specify an absolute size, strings to specify names for dimensions that should all be consistently sized (and optionally also checks named tensors), "..." to indicate batch dimensions, and so on. See the full list here.

What are some alternatives?

When comparing einops and torchtyping you can also consider the following projects:

extending-jax - Extending JAX with custom C++ and CUDA code

opt_einsum - ⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.

jaxtyping - Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/

equinox - Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

kymatio - Wavelet scattering transforms in Python with GPU acceleration

tsalib - Tensor Shape Annotation Library (numpy, tensorflow, pytorch, ...)

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.

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

3d-ken-burns - an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.