[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-2481":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":18,"compositeScore":19,"rankGlobal":9,"rankLanguage":9,"license":20,"archived":21,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":25,"readmeContent":26,"aiSummary":27,"trendingCount":15,"starSnapshotCount":15,"syncStatus":28,"lastSyncTime":29,"discoverSource":30},2481,"magenta","magenta\u002Fmagenta","Magenta: Music and Art Generation with Machine Intelligence","",null,"Python",19789,3775,735,381,0,7,20,1,45,"Apache License 2.0",true,false,"main",[],"2026-06-12 02:00:41","# Status\n\nThis repository is currently inactive (archived, read only) and serves only as a supplement some of our papers. We have transitioned to using individual repositories for new projects. For our current work, see the [Magenta website](https:\u002F\u002Fg.co\u002Fmagenta) and [Magenta GitHub Organization](https:\u002F\u002Fgithub.com\u002Fmagenta).\n\n# Magenta\n\n\u003Cimg src=\"magenta-logo-bg.png\" height=\"75\">\n\n[![Build Status](https:\u002F\u002Fgithub.com\u002Fmagenta\u002Fmagenta\u002Fworkflows\u002Fbuild\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fmagenta\u002Fmagenta\u002Factions?query=workflow%3Abuild)\n [![PyPI version](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Fmagenta.svg)](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Fmagenta)\n\n**Magenta** is a research project exploring the role of machine learning\nin the process of creating art and music.  Primarily this\ninvolves developing new deep learning and reinforcement learning\nalgorithms for generating songs, images, drawings, and other materials. But it's also\nan exploration in building smart tools and interfaces that allow\nartists and musicians to extend (not replace!) their processes using\nthese models.  Magenta was started by some researchers and engineers\nfrom the [Google Brain team](https:\u002F\u002Fresearch.google.com\u002Fteams\u002Fbrain\u002F),\nbut many others have contributed significantly to the project. We use\n[TensorFlow](https:\u002F\u002Fwww.tensorflow.org) and release our models and\ntools in open source on this GitHub.  If you’d like to learn more\nabout Magenta, check out our [blog](https:\u002F\u002Fmagenta.tensorflow.org),\nwhere we post technical details.  You can also join our [discussion\ngroup](https:\u002F\u002Fgroups.google.com\u002Fa\u002Ftensorflow.org\u002Fforum\u002F#!forum\u002Fmagenta-discuss).\n\nThis is the home for our Python TensorFlow library. To use our models in the browser with [TensorFlow.js](https:\u002F\u002Fjs.tensorflow.org\u002F), head to the [Magenta.js](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Fmagenta-js) repository.\n\n## Getting Started\n\nTake a look at our [colab notebooks](https:\u002F\u002Fmagenta.tensorflow.org\u002Fdemos\u002Fcolab\u002F) for various models, including one on [getting started](https:\u002F\u002Fcolab.research.google.com\u002Fnotebooks\u002Fmagenta\u002Fhello_magenta\u002Fhello_magenta.ipynb).\n[Magenta.js](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Fmagenta-js) is also a good resource for models and [demos](https:\u002F\u002Fmagenta.tensorflow.org\u002Fdemos\u002Fweb\u002F) that run in the browser.\nThis and more, including [blog posts](https:\u002F\u002Fmagenta.tensorflow.org\u002Fblog) and [Ableton Live plugins](https:\u002F\u002Fmagenta.tensorflow.org\u002Fdemos\u002Fnative\u002F), can be found at [https:\u002F\u002Fmagenta.tensorflow.org](https:\u002F\u002Fmagenta.tensorflow.org).\n\n## Magenta Repo\n\n* [Installation](#installation)\n* [Using Magenta](#using-magenta)\n* [Development Environment (Advanced)](#development-environment)\n\n## Installation\n\nMagenta maintains a [pip package](https:\u002F\u002Fpypi.python.org\u002Fpypi\u002Fmagenta) for easy\ninstallation. We recommend using Anaconda to install it, but it can work in any\nstandard Python environment. We support Python 3 (>= 3.5). These instructions\nwill assume you are using Anaconda.\n\n### Automated Install (w\u002F Anaconda)\n\nIf you are running Mac OS X or Ubuntu, you can try using our automated\ninstallation script. Just paste the following command into your terminal.\n\n```bash\ncurl https:\u002F\u002Fraw.githubusercontent.com\u002Ftensorflow\u002Fmagenta\u002Fmain\u002Fmagenta\u002Ftools\u002Fmagenta-install.sh > \u002Ftmp\u002Fmagenta-install.sh\nbash \u002Ftmp\u002Fmagenta-install.sh\n```\n\nAfter the script completes, open a new terminal window so the environment\nvariable changes take effect.\n\nThe Magenta libraries are now available for use within Python programs and\nJupyter notebooks, and the Magenta scripts are installed in your path!\n\nNote that you will need to run `source activate magenta` to use Magenta every\ntime you open a new terminal window.\n\n### Manual Install (w\u002Fo Anaconda)\n\nIf the automated script fails for any reason, or you'd prefer to install by\nhand, do the following steps.\n\nInstall the Magenta pip package:\n\n```bash\npip install magenta\n```\n\n**NOTE**: In order to install the `rtmidi` package that we depend on, you may need to install headers for some sound libraries. On Ubuntu Linux, this command should install the necessary packages:\n\n```bash\nsudo apt-get install build-essential libasound2-dev libjack-dev portaudio19-dev\n```\nOn Fedora Linux, use\n```bash\nsudo dnf group install \"C Development Tools and Libraries\"\nsudo dnf install SAASound-devel jack-audio-connection-kit-devel portaudio-devel\n```\n\n\nThe Magenta libraries are now available for use within Python programs and\nJupyter notebooks, and the Magenta scripts are installed in your path!\n\n## Using Magenta\n\nYou can now train our various models and use them to generate music, audio, and images. You can\nfind instructions for each of the models by exploring the [models directory](magenta\u002Fmodels).\n\n## Development Environment\nIf you want to develop on Magenta, you'll need to set up the full Development Environment.\n\nFirst, clone this repository:\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Fmagenta.git\n```\n\nNext, install the dependencies by changing to the base directory and executing the setup command:\n\n```bash\npip install -e .\n```\n\nYou can now edit the files and run scripts by calling Python as usual. For example, this is how you would run the `melody_rnn_generate` script from the base directory:\n\n```bash\npython magenta\u002Fmodels\u002Fmelody_rnn\u002Fmelody_rnn_generate --config=...\n```\n\nYou can also install the (potentially modified) package with:\n\n```bash\npip install .\n```\n\nBefore creating a pull request, please also test your changes with:\n\n```bash\npip install pytest-pylint\npytest\n```\n\n## PIP Release\n\nTo build a new version for pip, bump the version and then run:\n\n```bash\npython setup.py test\npython setup.py bdist_wheel --universal\ntwine upload dist\u002Fmagenta-N.N.N-py2.py3-none-any.whl\n```\n","Magenta是一个探索机器学习在艺术和音乐创作中作用的研究项目。它主要通过开发新的深度学习和强化学习算法来生成音乐、图像等艺术作品，并致力于构建智能工具与界面，以帮助艺术家扩展其创作过程。Magenta基于TensorFlow框架，采用Python语言实现，提供开源模型和工具。该项目适合希望结合人工智能技术进行艺术创作的个人或团队使用，尤其适用于音乐家、视觉艺术家以及对AI生成内容感兴趣的开发者。尽管官方仓库已归档，但Magenta官网及GitHub组织仍在持续更新相关研究进展。",2,"2026-06-11 02:50:04","top_language"]