Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 01:32 UTC

TylerYep / torchinfo

View model summaries in PyTorch!

Python · Jupyter NotebookMIT★ 2,945 stars⑂ 138 forkssince Mar 2020View on GitHub ↗

TylerYep/torchinfo holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Engineering Quality (76/100) and lowest on Sustainability & Governance (58/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

77
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

77
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

Tyler YepPersonal account
134 followers62 public repossince Mar 2016Robinhood

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPItorchinfo1.8.0-321186 days agotorchpytorchtorchsummarytorch-summarysummarykerasdeep-learningmltorchinfotorch-infovisualizemodelstatisticslayerstats

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

63Moderate · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
9/36Commit cadence13/52 weeks with commits
18/18Commit volume104 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year104
human_commit_share0.84
days_since_last_push2
active_weeks_last_year13
How it's scored
27/27Ships releases31 releases published
0/36Release recencylatest release 1,186 days ago
19.8/27Release cadencea release every ~56.6 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count31
latest_release_tagv1.8.0
releases_from_tagsno
days_since_latest_release1,186
mean_days_between_releases56.6

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

66Good · 17% of overall
How it's scored
56.3/60Stars2,945 stars
17.8/25Forks138 forks
6.4/15Watchers15 watchers
Inputs used
forks138
stars2,945
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, codecov.io, github.com, shields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

58Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
3.8/22.5Commit distributiontop contributor authored 83% of commits
13.5/13.5Contributor breadth26 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled26
top_contributor_share0.832
How it's scored
32.1/42Issue resolution76% of issues closed
27.3/30PR acceptance192/211 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-ReviewFound 3/4 approved changesets -- score normalized to 7
Inputs used
merged_prs192
open_issues42
closed_issues136
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.764
closed_unmerged_prs19
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
15.3/25Owner reach134 followers of TylerYep
25/25Track record62 public repos, account ~10 yr old
Inputs used
followers134
owner_typeUser
is_verified
owner_loginTylerYep
public_repos62
account_age_days3,794
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 1,186 days ago
20/20Version history32 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagestorchinfo
ecosystemspypi
any_deprecatedno
min_days_since_publish1,186

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests14 out of 14 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics9 topics
0/10Wiki
Inputs used
topicspytorch, torchsummary, torch, keras, visualization, torchvision, torch-summary, torchinfo, python
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

70Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.5/2.5CI-Tests14 out of 14 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-ReviewFound 3/4 approved changesets -- score normalized to 7
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
3.5/5SASTSAST tool is not run on all commits -- score normalized to 7
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.2
Excluded from scoring (no data or not applicable): Packaging. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages81
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 81 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

67Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
36.8/40Legible commit history58 of 84 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.69
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingtorchinfo/py.typed
10/10Reproducible environmentlockfile
10/10Demonstrated agent practice20 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance6 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configstorchinfo/py.typed
agent_commit_share0.2
toolchain_manifests
dependency_bot_commit_share0.06
How it's scored
27/45Type-checkable codePython with type-check config (torchinfo/py.typed)
55/55Manageable file sizes0/19 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes31,509
source_files_sampled19
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

2,945GitHub stars
26contributors
104commits, last 12 months
2days since last push
31releases
1bus factor
42open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 138 ⇿
0Stars
138Forks
27Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

025507510012515013832020-052023-062026-06
Major 0Minor 5Patch 21

Each point covers 6 days.

OpenSSF Scorecard 6.2 / 10
6.2aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-13 01:31 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests14 out of 14 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 3/4 approved changesets -- score normalized to 7
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
7SASTSAST tool is not run on all commits -- score normalized to 7
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPItorchpyproject.toml
PyPItorchvisionpyproject.toml
PyPInumpypyproject.toml
All dependencies 81

Full resolved dependency set from the GitHub dependency graph: 3 direct and 78 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy2.4.4direct
PyPItorch2.13.0direct
PyPItorchvision0.28.0direct
PyPIannotated-doc0.0.4indirect
PyPIanyio4.13.0indirect
PyPIcertifi2026.4.22indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.3.3indirect
PyPIcodecov2.1.13indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.5indirect
PyPIcuda-bindings13.2.0indirect
PyPIcuda-pathfinder1.5.4indirect
PyPIcuda-toolkit13.0.3.0indirect
PyPIdistlib0.4.0indirect
PyPIfilelock3.29.0indirect
PyPIfsspec2026.4.0indirect
PyPIh110.16.0indirect
PyPIhf-xet1.4.3indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhuggingface-hub1.13.0indirect
PyPIidentify2.6.19indirect
PyPIidna3.15indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIlibrt0.9.0indirect
PyPImarkdown-it-py4.0.0indirect
PyPImarkupsafe3.0.3indirect
PyPImdurl0.1.2indirect
PyPImpmath1.3.0indirect
PyPImypy1.20.2indirect
PyPImypy-extensions1.1.0indirect
PyPInetworkx3.6.1indirect
PyPInodeenv1.10.0indirect
PyPInvidia-cublas13.1.1.3indirect
PyPInvidia-cuda-cupti13.0.85indirect
PyPInvidia-cuda-nvrtc13.0.88indirect
PyPInvidia-cuda-runtime13.0.96indirect
PyPInvidia-cudnn-cu139.20.0.48indirect
PyPInvidia-cufft12.0.0.61indirect
PyPInvidia-cufile1.15.1.6indirect
PyPInvidia-curand10.4.0.35indirect
PyPInvidia-cusolver12.0.4.66indirect
PyPInvidia-cusparse12.6.3.3indirect
PyPInvidia-cusparselt-cu130.8.1indirect
PyPInvidia-nccl-cu132.29.7indirect
PyPInvidia-nvjitlink13.0.88indirect
PyPInvidia-nvshmem-cu133.4.5indirect
PyPInvidia-nvtx13.0.85indirect
PyPIpackaging26.2indirect
PyPIpathspec1.1.1indirect
PyPIpillow12.3.0indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.0indirect
PyPIpygments2.20.0indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-discovery1.2.2indirect
PyPIpyyaml6.0.3indirect
PyPIregex2026.4.4indirect
PyPIrequests2.33.1indirect
PyPIrich15.0.0indirect
PyPIruff0.15.12indirect
PyPIsafetensors0.7.0indirect
PyPIsetuptools83.0.0indirect
PyPIshellingham1.5.4indirect
PyPIsympy1.14.0indirect
PyPItokenizers0.22.2indirect
PyPItqdm4.67.3indirect
PyPItransformers5.7.0indirect
PyPItriton3.7.1indirect
PyPItyper0.25.1indirect
PyPItypes-requests2.33.0.20260408indirect
PyPItypes-setuptools82.0.0.20260408indirect
PyPItypes-tqdm4.67.3.20260408indirect
PyPItyping-extensions4.15.0indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.3.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 81 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.