{"id":13738180,"url":"https://github.com/eBay/AutoOpt","last_synced_at":"2025-05-08T16:32:36.410Z","repository":{"id":144913035,"uuid":"204528044","full_name":"eBay/AutoOpt","owner":"eBay","description":"Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent","archived":false,"fork":false,"pushed_at":"2020-08-04T05:00:19.000Z","size":262,"stargazers_count":44,"open_issues_count":0,"forks_count":12,"subscribers_count":9,"default_branch":"master","last_synced_at":"2024-08-04T03:12:01.590Z","etag":null,"topics":["hyperparameters","learning-rate","machine-learning","momentum","optimization","pytorch","sgd"],"latest_commit_sha":null,"homepage":"","language":"Python","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/eBay.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.TXT","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}},"created_at":"2019-08-26T17:36:00.000Z","updated_at":"2024-02-21T14:41:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"d4e3f95d-61b3-4da1-9a9a-a4376dff571d","html_url":"https://github.com/eBay/AutoOpt","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/eBay%2FAutoOpt","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eBay%2FAutoOpt/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eBay%2FAutoOpt/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/eBay%2FAutoOpt/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/eBay","download_url":"https://codeload.github.com/eBay/AutoOpt/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224746394,"owners_count":17363038,"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":["hyperparameters","learning-rate","machine-learning","momentum","optimization","pytorch","sgd"],"created_at":"2024-08-03T03:02:13.477Z","updated_at":"2024-11-15T07:30:30.094Z","avatar_url":"https://github.com/eBay.png","language":"Python","readme":"# AutoOpt\n\nThis package implements various optimizers with automatic and simultaneous\nadjustment of the learning rate and the momentum. The AutoOpt package can be used\nin a deep learning training instead of the regular optimizers that are available \nin the PyTorch framework. The mini-batch flow in a training is shown in the below \nfigure.\n\n![](docs/figures/system.png)\n\n## Installation\n\nThis package is built and tested in Python 3.6. Create\na `venv` and install the dependencies as follows:\n\n```bash\npython3 -m venv .env\nsource .env/bin/activate\npip install --upgrade pip\npip install torch torchvision\n```\n\nNow install the AutoOpt package from its source repository:\n\n```bash\npip install [autoopt-path]\n```\n\n## Examples\n\nPlease see the sample code provided in the `examples` folder to understand\nhow this package can be used in training of various ML models.\n\n## Citing AutoOpt paper\n\nPlease cite the \n[AutoOpt paper](https://arxiv.org/pdf/1908.07607.pdf) \nif you are using it in a scientific publication.\n\n```bibtex\n@inproceedings{9053316,\n  author={T. {Lancewicki} and S. {Kopru}},\n  booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, \n  title={Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient-based Optimization Methods}, \n  year={2020},\n  volume={},\n  number={},\n  pages={3127-3131}\n}\n```\n\n## License\n\nCopyright 2019 eBay Inc.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this \nfile except in compliance with the License. You may obtain a copy of the License at\n\nhttps://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software distributed under the\nLicense is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,\neither express or implied. See the License for the specific language governing permissions\nand limitations under the License.\n\n## Third Party Code Attribution\n\nThis software contains code licensed by third parties.\nSee LICENSE.txt.\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FeBay%2FAutoOpt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FeBay%2FAutoOpt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FeBay%2FAutoOpt/lists"}