{"id":16472505,"url":"https://github.com/nhynes/em","last_synced_at":"2025-03-23T11:32:47.473Z","repository":{"id":71680015,"uuid":"86722170","full_name":"nhynes/em","owner":"nhynes","description":"Tool for managing deep learning experiments","archived":false,"fork":false,"pushed_at":"2017-12-22T21:48:27.000Z","size":26,"stargazers_count":13,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-18T20:06:40.858Z","etag":null,"topics":["deep-learning","git","pytorch"],"latest_commit_sha":null,"homepage":null,"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/nhynes.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":"2017-03-30T16:03:28.000Z","updated_at":"2020-02-13T18:23:38.000Z","dependencies_parsed_at":"2023-05-14T03:30:19.913Z","dependency_job_id":null,"html_url":"https://github.com/nhynes/em","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nhynes%2Fem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nhynes%2Fem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nhynes%2Fem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nhynes%2Fem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nhynes","download_url":"https://codeload.github.com/nhynes/em/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245097158,"owners_count":20560311,"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","git","pytorch"],"created_at":"2024-10-11T12:17:23.611Z","updated_at":"2025-03-23T11:32:47.461Z","avatar_url":"https://github.com/nhynes.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# experiment manager\n\n`em` is a tool that facilitates deep learning experimentation using a [Git worktree](https://git-scm.com/docs/git-worktree) workflow.\n\nThe use case is when you want to test a number of small changes that are not worth implementing as into full-fledged options but must still be recorded, nonetheless.\n`em` allows this by creating a separate worktree for each experiment; this work tree is essentially a snapshot of the configuration at the time the experiment was run.\nAdditionally, since each experiment has its own branch, interesting options can be merged back into the main branch.\n\nFor instance,\n```\nem proj test_proj\ncd test_proj\ngit add -A \u0026\u0026 git commit -m \"Initial commit.\"\necho \"print('hello, world!')\" \u003e main.py\nem run testing   # hello world!\nem show testing  # {'created': 1490891521.6767356, 'status': 'completed'}\nem clean testing\n```\n\n## Requirements and Installation\n\nYou will need\n* Python \u003e= 3.6\n* libgit2 \u003e= 0.26\n* pygit2 \u003e= 0.26\n* `pip install daemon`\n\n## Usage\n\n`em --help`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnhynes%2Fem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnhynes%2Fem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnhynes%2Fem/lists"}