{"id":18850893,"url":"https://github.com/igitugraz/l2l","last_synced_at":"2025-04-14T09:51:13.762Z","repository":{"id":37706192,"uuid":"83444969","full_name":"IGITUGraz/L2L","owner":"IGITUGraz","description":"Learning to Learn: Gradient-free Optimization framework","archived":false,"fork":false,"pushed_at":"2021-07-13T18:07:32.000Z","size":7615,"stargazers_count":36,"open_issues_count":15,"forks_count":23,"subscribers_count":17,"default_branch":"master","last_synced_at":"2025-03-27T23:11:11.224Z","etag":null,"topics":["ai","l2l","learning-to-learn","machine-learning","optimization","optimization-algorithms"],"latest_commit_sha":null,"homepage":"https://igitugraz.github.io/L2L/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/IGITUGraz.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-02-28T14:56:32.000Z","updated_at":"2023-09-01T17:30:42.000Z","dependencies_parsed_at":"2022-09-14T04:00:35.204Z","dependency_job_id":null,"html_url":"https://github.com/IGITUGraz/L2L","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/IGITUGraz%2FL2L","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IGITUGraz%2FL2L/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IGITUGraz%2FL2L/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IGITUGraz%2FL2L/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/IGITUGraz","download_url":"https://codeload.github.com/IGITUGraz/L2L/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248859618,"owners_count":21173337,"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":["ai","l2l","learning-to-learn","machine-learning","optimization","optimization-algorithms"],"created_at":"2024-11-08T03:32:25.263Z","updated_at":"2025-04-14T09:51:13.737Z","avatar_url":"https://github.com/IGITUGraz.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"L2L Gradient-free Optimization Framework\n++++++++++++++++++++++++++++++++++++++++\n\nAbout\n*****\n\nThe L2L (Learning-to-learn) gradient-free optimization framework contains well documented and tested implementations of various gradient free optimization algorithms. It also defines an API that makes it easy to optimize (hyper-)parameters for any task (optimizee). All the implementations in this package are parallel and can run across different cores and nodes (but equally well on a single core).\n\nNOTE: The L2L framework is currently in **BETA**\n\nGetting Started\n***************\n\n\nIf you are developing a new Optimizee or want to try out a new Optimizee with the Optimizers in the L2L package, install\nL2L as a python package. See section `Installing the L2L Package`_ for details on how to install the package (this\nautomatically installs all requirements). \n\nDocumentation is available at `\u003chttps://igitugraz.github.io/L2L/\u003e`_.\n\n\nInstalling the L2L Package\n**************************\n\nFrom the Top-Level directory of the directory, run the following command:\n\n    pip3 install --editable . --process-dependency-links [--user]\n\n*The `--user` flag is to be used if you wish to install in the user path as opposed\nto the root path (e.g. when one does not have sudo access)*\n\nThe above will install the package by creating symlinks to the code files in the \nrelevant directory containing python modules. This means that you can change any\nof the code files and see the changes reflected in the package immediately (i.e.\nwithout requiring a reinstall). In order to uninstall one may run the following:\n\n    pip3 uninstall Learning-to-Learn\n\n*Note that if the setup was done using sudo access, then the uninstall must also\nbe done using sudo access*\n\nHaving installed this package, we now have access to the top level `l2l` module\nwhich contains all the relevant modules relevant for using the l2l package.\n\nThis should also install the `sphinx` package which should now enable you to build\nthe documentation as specified below.\n\n\nBuilding Documentation\n**********************\nRun the following command from the `doc` directory\n\n    make html \n\nAnd open the documentation with \n\n   firefox _build/html/index.html\n\nAll further (and extensive) documentation is in the html documentation!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figitugraz%2Fl2l","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Figitugraz%2Fl2l","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figitugraz%2Fl2l/lists"}