miniF2F VS einops

Compare miniF2F vs einops and see what are their differences.


Formal to Formal Mathematics Benchmark (by openai)


Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others) (by arogozhnikov)
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miniF2F einops
4 19
258 7,971
3.5% -
0.0 7.4
9 months ago 9 days ago
Objective-C++ Python
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.


Posts with mentions or reviews of miniF2F. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-11.


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 2024-04-27.

What are some alternatives?

When comparing miniF2F and einops you can also consider the following projects:

tensor_annotations - Annotating tensor shapes using Python types

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

torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.

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

FL - FL language specification and reference implementations

kymatio - Wavelet scattering transforms in Python with GPU acceleration

dex-lang - Research language for array processing in the Haskell/ML family

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.

jaxtyping - Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays.

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.

hasktorch - Tensors and neural networks in Haskell

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