torch-einops-utils
Personal utility functions
Decision gist · record as of 2026-08-14
Yes, if you use PyTorch and einops regularly. Low install friction, active maintenance, permissive license, and no known vulnerabilities make it a safe addition. The Beta status and modest documentation suggest it's best suited for developers comfortable exploring a smaller utility library rather than a mature framework. Check the repository for specific functions that match your tensor manipulation needs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; torch and einops must be installed as runtime dependencies.
- Low install friction with a pure Python wheel.
- Active maintenance—released 3 days ago with a recent commit on 2026-08-11.
License · maintenance · safety
permissive license (permissive) — MIT License permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
last release 2026-08-11 (3 days) · last repo commit 2026-08-11 · 52 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 619,277 downloads/mo, #5,730 on PyPI
Alternatives
Verify before relying
pip install torch-einops-utils
import torch
from torch_einops_utils import ...
# Use utility functions with torch and einops- What specific utility functions are included and their scope of applicability to different ML tasks.
- Whether the package is stable enough for production use given its Beta development status.
What it is and what it does
torch-einops-utils is a lightweight utility library that wraps and extends einops and torch to simplify tensor operations in machine learning workflows. It depends on einops and torch as its only runtime dependencies, making it a thin convenience layer rather than a heavy framework. The package targets developers working with PyTorch who want faster, more readable tensor manipulation code.
Released on 2026-01-09 and actively maintained (most recent release 2026-08-11), the package is in Beta status and requires Python 3.9 or later. It carries no known security vulnerabilities and uses a permissive MIT License. With roughly 619277 monthly downloads and a position in the top 15000 PyPI packages, it has found modest adoption in the ML community.
Use it for
- Simplify tensor reshaping and dimension manipulation in PyTorch models using einops-based helpers.
- Accelerate prototyping of neural network layers by reducing boilerplate tensor operation code.
- Standardize tensor operations across a team's ML codebase with shared utility functions.
- Integrate einops patterns into existing PyTorch projects with minimal overhead.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you use PyTorch and einops regularly.
Low install friction, active maintenance, permissive license, and no known vulnerabilities make it a safe addition. The Beta status and modest documentation suggest it's best suited for developers comfortable exploring a smaller utility library rather than a mature framework. Check the repository for specific functions that match your tensor manipulation needs.
Install
torch-einops-utils on PyPI
Before you install
Low install friction with a pure Python wheel. Active maintenance—released 3 days ago with a recent commit on 2026-08-11. Repository has 52 stars and is not archived.
Requires Python 3.9 or later; torch and einops must be installed as runtime dependencies.
License in practice
MIT License permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
Quickstart
pip install torch-einops-utils
import torch
from torch_einops_utils import ...
# Use utility functions with torch and einopsVerify before relying
- What specific utility functions are included and their scope of applicability to different ML tasks.
- Whether the package is stable enough for production use given its Beta development status.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packageseinopstorch |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 619,277 / month, #5,730 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: torch_einops_utils-0.1.19-py3-none-any.whl
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See also einops-exts · tools · einops · torch · torchtnt · hoptorch · msbench-utils · rotary-embedding-torch · etils · arm-pytorch-utilities