Metadata-Version: 2.1
Name: chop-pytorch
Version: 0.0.2
Summary: Continuous and constrained optimization with PyTorch
Home-page: http://pypi.python.org/pypi/chop-pytorch
Author: Geoffrey Negiar
Author-email: geoffrey_negiar@berkeley.edu
License: UNKNOWN
Description: # pytorCH OPtimize: a library for continuous optimization built on PyTorch
        
        ...with applications to adversarially attacking and training neural networks.
        
        [![Build Status](https://travis-ci.org/openopt/chop.svg?branch=master)](https://travis-ci.org/openopt/chop)
        [![Coverage Status](https://coveralls.io/repos/github/openopt/chop/badge.svg?branch=master)](https://coveralls.io/github/openopt/chop?branch=master)
        [![DOI](https://zenodo.org/badge/310693245.svg)](https://zenodo.org/badge/latestdoi/310693245)
        
        :warning: This library is in early development, API might change without notice. The examples will be kept up to date. :warning:
        
        ## Stochastic Algorithms
        
        We define stochastic optimizers in the `chop.stochastic` module. These follow PyTorch Optimizer conventions, similar to the `torch.optim` module.
        
        ## Full Gradient Algorithms
        
        We also define full-gradient algorithms which operate on a batch of optimization problems in the `chop.optim` module. These are used for adversarial attacks, using the `chop.Adversary` wrapper.
        
        ## Examples:
          
          See `examples` directory and our [webpage](http://openo.pt/chop/auto_examples/index.html).
        
        ## Tests
        
        Run the tests with `pytests tests`.
        
        ## Citing
        
        If this software is useful to your research, please consider citing it as
        
        ```
        @article{chop,
          author       = {Geoffrey Negiar, Fabian Pedregosa},
          title        = {CHOP: continuous optimization built on Pytorch},
          year         = 2020,
          url          = {http://github.com/openopt/chop}
        }
        ```
        
        ## Affiliations
        
        Geoffrey Négiar is in the Mahoney lab and the El Ghaoui lab at UC Berkeley.
        
        Fabian Pedregosa is at Google Research.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Description-Content-Type: text/markdown
