{"id":13857073,"url":"https://github.com/RJT1990/mantra","last_synced_at":"2025-07-13T20:30:52.481Z","repository":{"id":66075481,"uuid":"146776545","full_name":"RJT1990/mantra","owner":"RJT1990","description":"A high-level, rapid development framework for machine learning projects","archived":false,"fork":false,"pushed_at":"2023-09-27T02:12:21.000Z","size":26475,"stargazers_count":345,"open_issues_count":9,"forks_count":20,"subscribers_count":16,"default_branch":"master","last_synced_at":"2024-11-14T05:07:59.211Z","etag":null,"topics":["deep-learning","machine-learning"],"latest_commit_sha":null,"homepage":null,"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/RJT1990.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","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":"2018-08-30T16:25:10.000Z","updated_at":"2024-07-09T23:21:53.000Z","dependencies_parsed_at":null,"dependency_job_id":"809bc669-6df3-4dfe-8158-577783fb71e7","html_url":"https://github.com/RJT1990/mantra","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RJT1990%2Fmantra","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RJT1990%2Fmantra/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RJT1990%2Fmantra/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RJT1990%2Fmantra/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RJT1990","download_url":"https://codeload.github.com/RJT1990/mantra/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225912590,"owners_count":17544207,"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","machine-learning"],"created_at":"2024-08-05T03:01:25.023Z","updated_at":"2024-11-22T14:32:07.582Z","avatar_url":"https://github.com/RJT1990.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\r\n    \u003cimg width=\"250\" src=\"docs/source/logo.png\"\u003e    \r\n\u003c/div\u003e\r\n\r\n-----------------------------------------\r\n\r\n[![CircleCI](https://circleci.com/gh/RJT1990/mantra.svg?style=shield\u0026circle-token=ef9ddee091dd77395273f8d59f6b6b5b091212c7)](https://circleci.com/gh/RJT1990/mantra)\r\n[![PyPI version](https://badge.fury.io/py/mantraml.svg)](https://badge.fury.io/py/mantraml)\r\n[![Gitter chat](https://badges.gitter.im/gitterHQ/gitter.png)](https://gitter.im/mantraml/Lobby)\r\n[![Documentation Status](https://readthedocs.org/projects/mantra/badge/?version=latest)](http://mantra.readthedocs.io/en/latest/?badge=latest)\r\n\r\n\r\n**Mantra** is used by deep learning practitioners to manage their development workflow. It automatically provisions cloud instances for training, tracks and versions experiments, has a UI for training and evaluating results, and works with frameworks like PyTorch and TensorFlow. \r\n\r\n**Key Features**:\r\n\r\n- Boilerplate classes for common dataset and model types\r\n- Command-line interface for training with parameter parsing\r\n- Automatic provisioning of cloud instances for remote training\r\n- UI for monitoring training, comparing experiments and storing media\r\n- Encapsulation of datasets and models by design, enabling easy sharing \r\n\r\nThis is an alpha release. All contributions are welcome - see [here](https://github.com/RJT1990/mantra/blob/master/CONTRIBUTING.md) for guidelines on how to contribute.\r\n\r\n[You can read the docs here](http://mantra.readthedocs.io/en/latest/).\r\n\r\n-----------------------------------------\r\n\r\n\u003cdiv align=\"center\"\u003e\r\n\u003cimg src=\"docs/source/ui.png\"\u003e\r\n\u003c/div\u003e\r\n\u003cbr\u003e\u003cbr\u003e\r\n\r\n## Get Started \r\n\r\n🚀 To launch your first Mantra project, execute the following to create a new project directory:\r\n\r\n```console\r\nmantra launch my_project \r\n```\r\n☁ Configure your cloud settings and API keys:\r\n\r\n```console\r\ncd my_project \r\nmantra cloud \r\n```\r\n💾 Get the example datasets and models from [here](https://github.com/RJT1990/mantra-examples):\r\n \r\n```console\r\nmantra import https://github.com/RJT1990/mantra-examples.git\r\n``` \r\n\r\n🤖 Here are the example models you can train:\r\n\r\n```console\r\nmantra train relativistic_gan --dataset decks --cloud --dev --image-dim 256 256\r\n```\r\n\r\n```console\r\nmantra train log_reg --dataset epl_data --target home_win --features feature_1 feature_2 feature_3 \r\n```\r\n\r\n🚂 During training, you can spin up the Mantra UI to track the progress:\r\n\r\n```console\r\nmantra ui\r\n```\r\n\r\n## Installation\r\n\r\nTo install mantra, you can use pip:\r\n\r\n```\r\npip install mantraml\r\n```\r\nYou should also have TensorFlow or PyTorch installed depending on which framework you intend to use.\r\n\r\nMantra is tested on Python 3.5+. It is not currently supported on Windows, but we'll look to get support in the near future.\r\n\r\n### AWS Dependencies\r\n\r\nYou will need to install AWS CLI as a dependency. \r\n\r\n1. Login to AWS through a browser, click your name in the menubar and click My Security Credentials.\r\n\r\n2. Create a new Access Key and make a note of the **Access Key ID** and **Secret Access Key**.\r\n\r\n3. From terminal enter the following:\r\n\r\n```console\r\njohnsmith@computer:~$ pip install awscli\r\njohnsmith@computer:~$ aws configure\r\n```\r\n\r\nOnce prompted, enter your AWS details and your default region (e.g. *us-east-1*).\r\n\r\n4. Now your credentials will be accessible by the **boto3** AWS SDK library, which will allow **Mantra** to be used to \r\nprovision cloud instances on your request.\r\n\r\n5. Use *mantra cloud* from your mantra project root to configure your cloud settings.\r\n\r\nYou should also ensure you are happy with the default instance settings in mantra - you can check this in the *settings.py* file in your project root. \r\n\r\n### Have Fun\r\n\r\n\u003e Arise! Awake! Approach the great and learn.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FRJT1990%2Fmantra","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FRJT1990%2Fmantra","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FRJT1990%2Fmantra/lists"}