{"id":20609055,"url":"https://github.com/alexjc/pytrain","last_synced_at":"2025-04-15T04:30:43.971Z","repository":{"id":87350480,"uuid":"208804419","full_name":"alexjc/pytrain","owner":"alexjc","description":"🚃 Automated task/test framework for writing differentiable software.","archived":false,"fork":false,"pushed_at":"2021-01-18T17:28:30.000Z","size":249,"stargazers_count":7,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-28T15:51:57.797Z","etag":null,"topics":["deep-learning","differentiable-programming","python","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alexjc.png","metadata":{"files":{"readme":"README.rst","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":"2019-09-16T13:17:35.000Z","updated_at":"2025-01-11T23:02:27.000Z","dependencies_parsed_at":null,"dependency_job_id":"f33947df-ea6b-4aae-9731-59d472705031","html_url":"https://github.com/alexjc/pytrain","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexjc%2Fpytrain","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexjc%2Fpytrain/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexjc%2Fpytrain/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexjc%2Fpytrain/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alexjc","download_url":"https://codeload.github.com/alexjc/pytrain/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249006298,"owners_count":21197247,"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","differentiable-programming","python","pytorch"],"created_at":"2024-11-16T10:12:37.771Z","updated_at":"2025-04-15T04:30:43.962Z","avatar_url":"https://github.com/alexjc.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":".. image:: docs/logo.png\n\n.. image:: https://img.shields.io/badge/python-3.6%2B-blue\n\n**What It Does.** Like ``pytest`` supports you in writing better Python code through automated testing, ``pytrain`` helps you build differentiable programs by making it easy to create tasks and use them to optimize your programs.\n\n**How It Works.** You write differentiable components (e.g. using PyTorch) along with tasks they are expected to handle, and ``pytrain`` will optimize all the parameters involved and save them to disk as an automated process.\n\nInstallation\n============\n\n.. code:: bash\n\n    # Create a base environment\n    conda create -n myenv python=3.6\n    conda install pytorch -c pytorch\n\n    # Either install latest release 0.0.x, see GitHub for latest version number:\n    pip install https://github.com/alexjc/pytrain/releases/download/v0.0.x/pytrain-0.0.x.tar.gz\n\n    # Or clone the repository online:\n    git clone https://github.com/alexjc/pytrain.git\n\nUsage\n=====\n\n.. code:: bash\n\n    # Either launch from installed script:\n    pytrain -h\n    pytrain --path examples/\n\n    # Or run from current directory:\n    python -m pytrain -h\n    python -m pytrain --path examples/\n\n\nExamples\n========\n\nSee the ``#docs/`` folder or scripts in ``#examples/`` to get up and running.\n\nNOTE: This version 0.0.x is an `early prototype \u003chttps://www.youtube.com/watch?v=X5PUnVVtq-g\u003e`_ for the PyTorch Hackathon 2019.  Feedback and suggestions are the most welcome at this stage!\n\n.. image:: docs/console.gif\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexjc%2Fpytrain","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falexjc%2Fpytrain","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexjc%2Fpytrain/lists"}