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sksq96/pytorch-summary

Model summary in PyTorch similar to `model.summary()` in Keras observed · 2026-08-28

github.com/sksq96/pytorch-summary · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3054
  • days_rel: n/a
  • days_push: 914
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

4053 stars · 409 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A PyTorch library providing a Keras-style model.summary() that prints layer types, output shapes, parameter counts, and memory estimates. It is now superseded by the maintained torchinfo package.

Use cases

  • print a keras-style summary of a pytorch model
  • count trainable parameters in a pytorch network
  • show layer output shapes for debugging a cnn
  • estimate model memory footprint in pytorch
  • inspect pytorch model architecture like keras model.summary()

When to avoid

  • you are starting a new project - use torchinfo instead
  • you need summaries of models with multiple inputs or complex control flow

Facets

library · maturity maintenance

machine-learning deep-learning developer-tools deep-learning machine-learning developer-tools python pytorch model-summary keras-style debugging neural-networks

1 source

Member repositories

RepositoryRoleHealth v2
sksq96/pytorch-summarymain32

For agents

markdown · JSON · MCP: product_card(name="sksq96/pytorch-summary")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem