# xl0/lovely-tensors

Tensors, for human consumption

Repository: https://github.com/xl0/lovely-tensors
Canonical: https://ross.abutalabs.com/products/lovely-tensors
Homepage: https://xl0.github.io/lovely-tensors
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: deep-learning, library, pytorch, statistics, visualization
Last push: 2026-04-09T22:40:00+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 76, release rhythm 35, longevity 100
- inputs: {"age_days": 1426, "days_push": 146, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1392, forks 22 (observed 2026-08-28T04:04:36.114724+00:00)

## What it is
A Python library that provides human-friendly summaries of PyTorch tensors, showing shape, statistics, histograms, and NaN/Inf detection instead of raw number dumps. It integrates with Jupyter notebooks and can monkey-patch tensor repr for nicer output.

## Use cases
- debug pytorch tensors in jupyter notebooks
- show tensor shape and statistics instead of raw numbers
- detect nan or inf values in tensors
- visualize tensors as images or plots during debugging
- pretty-print tensors for human readability

## When to choose
- you debug PyTorch code in notebooks and want readable tensor output
- you need quick summaries of tensor shape, stats, and value ranges
- you want to spot NaN/Inf values at a glance

## When to avoid
- you need full numerical precision of tensor contents
- you work with NumPy/JAX only (use the sibling lovely-numpy or lovely-jax libraries)
- you need production logging rather than interactive debugging

## Facets
- artifact type: library
- maturity: active
- function: data-visualization, developer-tools
- domain: deep-learning, machine-learning, data-science, developer-tools
- platform: python, cross-platform
- tags: pytorch, tensors, jupyter, debugging, pretty-printing, statistics

## Member repositories
- xl0/lovely-tensors (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:36.114724+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:39:34.648901+00:00, confidence not recorded.
  - readme: https://github.com/xl0/lovely-tensors (fetched 2026-08-28T04:04:36.114724+00:00, sha dda4ab664b74)
  - homepage: https://xl0.github.io/lovely-tensors (fetched 2026-08-29T11:54:34.755189+00:00, sha 6dc5f58b27b7)
  - registry_pypi: https://pypi.org/pypi/lovely-tensors/json (fetched 2026-08-29T11:54:34.764612+00:00, sha 120dadd290c9)
- Data as of 2026-08-30T08:39:29.467469+00:00.