xl0/lovely-tensors
Tensors, for human consumption
When working with PyTorch, JAX, or NumPy, it's often hard to quickly understand what's inside a tensor while debugging. This tool transforms raw tensor output into a concise summary showing its shape, size, value distribution, and special values like NaNs or infinities. It's designed for data scientists, machine learning engineers, and researchers who frequently inspect numerical data structures.
1,360 stars. Used by 3 other packages. Actively maintained with 1 commit in the last 30 days. Available on PyPI.
Use this if you need a quick, human-readable summary of your numerical tensors (PyTorch, JAX, or NumPy) during development or debugging, including visual representations of data distributions.
Not ideal if you need to deeply inspect every individual value of a large tensor, or if you are not working with PyTorch, JAX, or NumPy tensors.
Stars
1,360
Forks
22
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
1
Dependencies
2
Reverse dependents
3
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