{"id":15414866,"url":"https://github.com/adrien-lagesse/ngmb","last_synced_at":"2026-02-24T09:03:19.596Z","repository":{"id":255762225,"uuid":"853562064","full_name":"adrien-lagesse/ngmb","owner":"adrien-lagesse","description":"The ngmb(Noisy Graph Matching Benchmark) package simplifies benchmarking GNNs on the graph alignement task (graph matching) with correlated pairs of graphs.","archived":false,"fork":false,"pushed_at":"2025-01-25T11:11:47.000Z","size":939,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-21T08:44:54.466Z","etag":null,"topics":["benchmark","combinatorial-optimization","deep-learning","geometric-deep-learning","graph-neural-networks","machine-learning","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/adrien-lagesse.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-06T23:11:49.000Z","updated_at":"2024-09-11T17:01:02.000Z","dependencies_parsed_at":null,"dependency_job_id":"e8816443-243c-4f49-87c1-194a44306afe","html_url":"https://github.com/adrien-lagesse/ngmb","commit_stats":{"total_commits":4,"total_committers":2,"mean_commits":2.0,"dds":0.25,"last_synced_commit":"3ff362ea83b5609a72aba6a0743ffb37d3b1f4f2"},"previous_names":["adrien-lagesse/ngmb"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/adrien-lagesse/ngmb","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-lagesse%2Fngmb","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-lagesse%2Fngmb/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-lagesse%2Fngmb/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-lagesse%2Fngmb/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/adrien-lagesse","download_url":"https://codeload.github.com/adrien-lagesse/ngmb/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-lagesse%2Fngmb/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29777609,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-24T04:54:30.205Z","status":"ssl_error","status_checked_at":"2026-02-24T04:53:58.628Z","response_time":75,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["benchmark","combinatorial-optimization","deep-learning","geometric-deep-learning","graph-neural-networks","machine-learning","pytorch"],"created_at":"2024-10-01T17:05:05.897Z","updated_at":"2026-02-24T09:03:19.553Z","avatar_url":"https://github.com/adrien-lagesse.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Benchmarking GNNs by aligning graphs\n\nThe `ngmb` (**Noisy Graph Matching Benchmark**) package simplifies benchmarking GNNs on the graph alignement task (graph matching) with correlated pairs of graphs.\nIt is based on PyTorch and the default models are written using the Pytorch Geometric package.\n\nSeveral functionalities are provided:\n- Generating Graph Matching Datasets (from synthetic data or pre-existing datasets used by the GNN community).\n- A set of pre-generated and fixed Graph Matching Datasets.\n- A framework to benchmark different GNNs architecture against Graph Matching Datasets.\n- Using GNNs trained on the benchmark datasets to generate high quality Graph Positional Encodings.\n\n# Graph Matching problem for benchmarking\n\n## Dataset generation\n\nWe provide several command line application to generate graph matching datasets:\n\n- **gm-generate-er** : Generate Erdos-Renyi GM datasets.\n- **gm-generate-aqsol** : Generate GM datasets based on the AQSOL dataset\n- **gm-generate-karateclub** : Generate GM datasets based on the KarateClub Benchmark dataset.\n- **gm-generate-corafull** : Generate GM datasets based on the CoraFull Benchmark dataset.\n- **gm-generate-ogbn-arxiv** : Generate GM datasets based on the OGBN-Arxiv Benchmark dataset.\n- **gm-generate-pcqm4mv2** : Generate GM datasets based on the PCQM4Mv2 Benchmark dataset.\n\nTo know more about them run:\n\n`gm-generate-er --help`\n\n`gm-generate-aqsol --help`\n\n`gm-generate-karateclub --help`\n\n`gm-generate-corafull --help`\n\n`gm-generate-ogbn-arxiv --help`\n\n`gm-generate-pcqm4mv2 --help`\n\n\nOnce you have a dataset, you can print key statistics with `gm-data-stats`\n\n## Training\n\n### Architectures in the library (`ngmb.models`)\n\nUse the `gm-train` command line tool to train a Siamese Graph Matching model. (run `gm-train --help` for more information and see `scripts/train-siamese-gm.sh` for an example).\n\n### Custom architectures\n\nUse the API.\n\n\n# Running the Repo\n\nWe use [Rye](https://rye.astral.sh/) to manage the python project. See the documentation for a complete guide.\n\n### Quick installation (Linux and MacOS)\n\n`curl -sSf https://rye.astral.sh/get | bash`\n\n`echo 'source \"$HOME/.rye/env\"' \u003e\u003e ~/.profile    # For Bash`\n\n`echo 'source \"$HOME/.rye/env\"' \u003e\u003e ~/.zprofile   # For ZSH`\n\nYou may have to restart you shell.\n\n### Cloning the repo\n\n`git clone https://github.com/adrien-lagesse/ngmb.git`\n\n`cd ngmb`\n\n`rye sync`\n\n`rye list`\n\nYou sould have a list of all the dependencies of the project.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadrien-lagesse%2Fngmb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadrien-lagesse%2Fngmb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadrien-lagesse%2Fngmb/lists"}