Metadata-Version: 2.1
Name: torchsynth
Version: 0.0.2
Summary: A modular synthesizer in pytorch, GPU-optional and differentiable
Home-page: UNKNOWN
Author: Joseph Turian, Jordie Shier, Max Henry
Author-email: 
License: Apache-2.0
Description: # torchsynth
        
        torchsynth is based upon traditional modular synthesis written in
        pytorch. It is GPU-optional and differentiable.
        
        [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/turian/torchsynth/blob/main/examples/examples.ipynb)
        
        [![PyPI](https://img.shields.io/pypi/v/torchsynth)](https://pypi.org/project/torchsynth/)
        ![PyPI - Wheel](https://img.shields.io/pypi/wheel/torchsynth)
        ![PyPI - License](https://img.shields.io/pypi/l/torchsynth)
        [![codecov.io](https://codecov.io/gh/turian/torchsynth/branch/main/graphs/badge.svg?logoWidth=18)](https://codecov.io/github/turian/torchsynth?branch=master)
        [![Total alerts](https://img.shields.io/lgtm/alerts/g/turian/torchsynth.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/turian/torchsynth/alerts/)
        [![Travis CI build status](https://travis-ci.com/turian/torchsynth.png)](https://travis-ci.com/turian/torchsynth)
        ![Snyk Vulnerabilities for GitHub Repo](https://img.shields.io/snyk/vulnerabilities/github/turian/torchsynth)
        
        You will need to install the particular version of
        [torchcsprng][https://github.com/pytorch/csprng] for your CUDA
        device. Please follow their simple installation instructions.  But
        if you use the CPU version of torchcsprng, it probably won't affect
        performance much.
        
        ## Development Installation
        
        ```
        git clone https://github.com/turian/torchsynth
        cd torchsynth
        pip3 install -e ".[dev]"
        ```
        
        Make sure you have pre-commit hooks installed:
        ```
        pre-commit install
        ```
        This helps us avoid checking dirty jupyter notebook cells into the
        repo.
        
        Note that torchsynth requires PyTorch version 1.7 or greater.
        
        ### Examples
        
        Unfortunately, Python 3.9 (e.g. OSX Big Sur) won't work, because
        librosa repends upon numba which isn't packaged for 3.9 yet. In
        which case you'll have to create a Python 3.7 conda environment.
        (You might also need to downgrade LLVM to 10 or 9.):
        ```
        conda install -c conda-forge ipython librosa matplotlib numpy matplotlib scipy jupytext
        conda install -c anaconda ipykernel
        python -m ipykernel install --user --name=envname
        ```
        and change the kernel to `envname`.
        
        ### Tests
        Unit testing is performed using `pytest`.
        
        `pytest` and other project development dependencies can be installed as follows: 
        ```
        pip3 install -e ".[test]"
        ```
        
        To run tests, run `pytest` from the project root:
        ```
        pytest
        ```
        
        To run tests with a coverage report:
        ```
        pytest --cov=./torchsynth
        ```
        
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: dev
