Tensorforce provides a TensorFlow library for applied reinforcement learning tasks.
Open source
24 alternativeseinops
einops provides readable tensor operations for PyTorch, JAX, TensorFlow, and other frameworks.
About einops
einops is an open-source Python library for tensor operations. It uses readable pattern strings to rearrange, reduce, and repeat tensor dimensions, and the project states support for numpy, PyTorch, JAX, MLX, and other frameworks, with TensorFlow named in the project description.
Beyond the three core functions, the library includes pack and unpack for combining tensors of different dimensionality, an einsum function that accepts multi-letter axis names, an EinMix linear layer, and framework-specific layer modules. Installation is through pip. Tutorials are available in four parts. The source does not state pricing or any usage limits.
Key features
- rearrange, reduce, and repeat functions for reshaping, transposing, and reducing tensors with string patterns.
- pack and unpack functions for combining tensors of different dimensionality into one and reversing it.
- einsum function that accepts multi-letter axis names and takes the pattern last.
- EinMix generic linear layer for MLP Mixer and similar architectures.
- Layer modules for PyTorch, TensorFlow, Flax, and Paddle that mirror the core functions.
- Recent updates added MLX and tinygrad backends and support for the array API standard.
Best for: Python developers working with multi-dimensional tensors in deep learning who want tensor reshaping code that is easier to read.
Good for
- Open-source project with its code published in a public GitHub repository.
- Three core functions cover reshaping, transposition, reduction, and repetition through one pattern syntax.
- Four tutorial parts are available, covering fundamentals, deep learning, packing and unpacking, and PyTorch code.
einops at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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einops FAQ
How do you install einops?
It installs with pip install einops. The source also notes that uv pip install einops works.
Which frameworks does einops support?
The project states support for numpy, PyTorch, JAX, MLX, and others. The project description also names TensorFlow.
Are there tutorials for learning einops?
Yes. The project lists four tutorial parts: einops fundamentals, einops for deep learning, packing and unpacking, and improving PyTorch code with einops.
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