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https://github.com/tensorflow/magenta

Magenta: Music and Art Generation with Machine Intelligence
https://github.com/tensorflow/magenta

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Magenta: Music and Art Generation with Machine Intelligence

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README 

        
# Status



This repository is currently inactive 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://g.co/magenta) and [Magenta GitHub Organization](https://github.com/magenta).



# Magenta






[![Build Status](https://github.com/magenta/magenta/workflows/build/badge.svg)](https://github.com/magenta/magenta/actions?query=workflow%3Abuild)

 [![PyPI version](https://badge.fury.io/py/magenta.svg)](https://badge.fury.io/py/magenta)



**Magenta** is a research project exploring the role of machine learning

in the process of creating art and music.  Primarily this

involves developing new deep learning and reinforcement learning

algorithms for generating songs, images, drawings, and other materials. But it's also

an exploration in building smart tools and interfaces that allow

artists and musicians to extend (not replace!) their processes using

these models.  Magenta was started by some researchers and engineers

from the [Google Brain team](https://research.google.com/teams/brain/),

but many others have contributed significantly to the project. We use

[TensorFlow](https://www.tensorflow.org) and release our models and

tools in open source on this GitHub.  If you’d like to learn more

about Magenta, check out our [blog](https://magenta.tensorflow.org),

where we post technical details.  You can also join our [discussion

group](https://groups.google.com/a/tensorflow.org/forum/#!forum/magenta-discuss).



This is the home for our Python TensorFlow library. To use our models in the browser with [TensorFlow.js](https://js.tensorflow.org/), head to the [Magenta.js](https://github.com/tensorflow/magenta-js) repository.



## Getting Started



Take a look at our [colab notebooks](https://magenta.tensorflow.org/demos/colab/) for various models, including one on [getting started](https://colab.research.google.com/notebooks/magenta/hello_magenta/hello_magenta.ipynb).

[Magenta.js](https://github.com/tensorflow/magenta-js) is also a good resource for models and [demos](https://magenta.tensorflow.org/demos/web/) that run in the browser.

This and more, including [blog posts](https://magenta.tensorflow.org/blog) and [Ableton Live plugins](https://magenta.tensorflow.org/demos/native/), can be found at [https://magenta.tensorflow.org](https://magenta.tensorflow.org).



## Magenta Repo



* [Installation](#installation)

* [Using Magenta](#using-magenta)

* [Development Environment (Advanced)](#development-environment)



## Installation



Magenta maintains a [pip package](https://pypi.python.org/pypi/magenta) for easy

installation. We recommend using Anaconda to install it, but it can work in any

standard Python environment. We support Python 3 (>= 3.5). These instructions

will assume you are using Anaconda.



### Automated Install (w/ Anaconda)



If you are running Mac OS X or Ubuntu, you can try using our automated

installation script. Just paste the following command into your terminal.



```bash

curl https://raw.githubusercontent.com/tensorflow/magenta/main/magenta/tools/magenta-install.sh > /tmp/magenta-install.sh

bash /tmp/magenta-install.sh

```



After the script completes, open a new terminal window so the environment

variable changes take effect.



The Magenta libraries are now available for use within Python programs and

Jupyter notebooks, and the Magenta scripts are installed in your path!



Note that you will need to run `source activate magenta` to use Magenta every

time you open a new terminal window.



### Manual Install (w/o Anaconda)



If the automated script fails for any reason, or you'd prefer to install by

hand, do the following steps.



Install the Magenta pip package:



```bash

pip install magenta

```



**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:



```bash

sudo apt-get install build-essential libasound2-dev libjack-dev portaudio19-dev

```

On Fedora Linux, use

```bash

sudo dnf group install "C Development Tools and Libraries"

sudo dnf install SAASound-devel jack-audio-connection-kit-devel portaudio-devel

```



The Magenta libraries are now available for use within Python programs and

Jupyter notebooks, and the Magenta scripts are installed in your path!



## Using Magenta



You can now train our various models and use them to generate music, audio, and images. You can

find instructions for each of the models by exploring the [models directory](magenta/models).



## Development Environment

If you want to develop on Magenta, you'll need to set up the full Development Environment.



First, clone this repository:



```bash

git clone https://github.com/tensorflow/magenta.git

```



Next, install the dependencies by changing to the base directory and executing the setup command:



```bash

pip install -e .

```



You 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:



```bash

python magenta/models/melody_rnn/melody_rnn_generate --config=...

```



You can also install the (potentially modified) package with:



```bash

pip install .

```



Before creating a pull request, please also test your changes with:



```bash

pip install pytest-pylint

pytest

```



## PIP Release



To build a new version for pip, bump the version and then run:



```bash

python setup.py test

python setup.py bdist_wheel --universal

twine upload dist/magenta-N.N.N-py2.py3-none-any.whl

```