{"id":14958165,"url":"https://github.com/dmlc/gnnlens2","last_synced_at":"2025-10-28T14:35:03.995Z","repository":{"id":41233944,"uuid":"401296053","full_name":"dmlc/GNNLens2","owner":"dmlc","description":"Visualization tool for Graph Neural Networks","archived":false,"fork":false,"pushed_at":"2022-09-20T06:40:00.000Z","size":21889,"stargazers_count":249,"open_issues_count":5,"forks_count":27,"subscribers_count":11,"default_branch":"main","last_synced_at":"2025-04-06T01:08:54.420Z","etag":null,"topics":["deep-learning","dgl","explainability","graph-neural-networks","graph-representation-learning","graph-visualization","pytorch","visualization","xai"],"latest_commit_sha":null,"homepage":"","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dmlc.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}},"created_at":"2021-08-30T10:00:29.000Z","updated_at":"2025-04-02T07:46:10.000Z","dependencies_parsed_at":"2022-07-10T16:03:08.881Z","dependency_job_id":null,"html_url":"https://github.com/dmlc/GNNLens2","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmlc%2FGNNLens2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmlc%2FGNNLens2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmlc%2FGNNLens2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmlc%2FGNNLens2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dmlc","download_url":"https://codeload.github.com/dmlc/GNNLens2/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247419860,"owners_count":20936012,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["deep-learning","dgl","explainability","graph-neural-networks","graph-representation-learning","graph-visualization","pytorch","visualization","xai"],"created_at":"2024-09-24T13:16:24.194Z","updated_at":"2025-10-28T14:35:03.920Z","avatar_url":"https://github.com/dmlc.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"resources/logo.png\" width=30% height=30%\u003e\n\n\u003cimg src=\"resources/README.png\"\u003e\n\nGNNLens2 is an interactive visualization tool for graph neural networks (GNN). It allows seamless integration with [deep graph library (DGL)](https://github.com/dmlc/dgl) and can meet your various visualization requirements for presentation, analysis and model explanation. It is an open source version of [GNNLens](https://arxiv.org/abs/2011.11048) with simplification and extension.\n\nA **video demo** is available [here](https://www.youtube.com/watch?v=eBI_lyzsg3M). Switch the video quality for the best viewing experience.\n\n## Installation\n\n### Requirements\n\n- [PyTorch](https://pytorch.org/)\n- [DGL](https://www.dgl.ai/pages/start.html)\n- Flask-CORS\n\nYou can install Flask-CORS with\n\n```bash\npip install -U flask-cors\n```\n\n### Installation for the latest stable version\n\n```bash\npip install Flask==2.0.3\npip install gnnlens\n```\n\n### Installation from source\n\nIf you want to try experimental features, you can install from source as follows:\n\n```bash\ngit clone https://github.com/dmlc/GNNLens2.git\ncd GNNLens2/python\npython setup.py install\n```\n\n### Verifying successful installation\n\nOnce you have installed the package, you can verify the success of installation with\n\n```python\nimport gnnlens\n\nprint(gnnlens.__version__)\n# 0.1.0\n```\n\n## Tutorials\n\nWe provide a set of tutorials to get you started with the library:\n- [Tutorial 1: Graph structure](resources/tutorials/tutorial_1_graph.md)\n- [Tutorial 2: Ground truth and predicted node labels](resources/tutorials/tutorial_2_nlabel.md)\n- [Tutorial 3: Edge weights and attention](resources/tutorials/tutorial_3_eweight.md)\n- [Tutorial 4: Weighted subgraphs and explanation methods](resources/tutorials/tutorial_4_subgraph.md)\n\n## Team\n\n**HKUST VisLab**: [Zhihua Jin](https://github.com/jnzhihuoo1), [Huamin Qu](http://huamin.org/)\n\n**AWS Shanghai AI Lab**: [Mufei Li](https://github.com/mufeili), [Wanru Zhao](https://github.com/Ryan0v0) (work done during internship), [Jian Zhang](https://github.com/zhjwy9343), [Minjie Wang](https://jermainewang.github.io/)\n\n**SMU**: [Yong Wang](http://yong-wang.org/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmlc%2Fgnnlens2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdmlc%2Fgnnlens2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmlc%2Fgnnlens2/lists"}