Metadata-Version: 1.1
Name: dyNET
Version: 2.0.1.post5
Summary: The Dynamic Neural Network Toolkit
Home-page: https://github.com/clab/dynet
Author: Graham Neubig
Author-email: dynet-users@googlegroups.com
License: Apache 2.0
Download-URL: https://github.com/clab/dynet/releases
Description-Content-Type: UNKNOWN
Description: .. raw:: html

        

           <div align="center">

        

        .. raw:: html

        

           </div>

        

        --------------

        

        |Build Status| |Build Status| |Doc build Status| |PyPI version|

        

        The Dynamic Neural Network Toolkit

        

        **News!** The master branch is now DyNet version 2.0 (as of 6/28/2017),

        which contains a number of changes including a new model format, etc. If

        you're looking for the old version, check out the `v1.1

        branch <https://github.com/clab/dynet/tree/v1.1>`__.

        

        -  `General <#general>`__

        -  `Installation <#installation>`__

        -  `C++ <#c-installation>`__

        -  `Python <#python-installation>`__

        -  `Getting Started <#getting-started>`__

        -  `Citing <#citing>`__

        -  `Releases and Contributing <#releases-and-contributing>`__

        

        General

        -------

        

        DyNet is a neural network library developed by Carnegie Mellon

        University and many others. It is written in C++ (with bindings in

        Python) and is designed to be efficient when run on either CPU or GPU,

        and to work well with networks that have dynamic structures that change

        for every training instance. For example, these kinds of networks are

        particularly important in natural language processing tasks, and DyNet

        has been used to build state-of-the-art systems for `syntactic

        parsing <https://github.com/clab/lstm-parser>`__, `machine

        translation <https://github.com/neubig/lamtram>`__, `morphological

        inflection <https://github.com/mfaruqui/morph-trans>`__, and many other

        application areas.

        

        Read the `documentation <http://dynet.readthedocs.io/en/latest/>`__ to

        get started, and feel free to contact the `dynet-users

        group <https://groups.google.com/forum/#!forum/dynet-users>`__ group

        with any questions (if you want to receive email make sure to select

        "all email" when you sign up). We greatly appreciate any bug reports and

        contributions, which can be made by filing an issue or making a pull

        request through the `github page <http://github.com/clab/dynet>`__.

        

        You can also read more technical details in our `technical

        report <https://arxiv.org/abs/1701.03980>`__.

        

        Getting started

        ---------------

        

        You can find tutorials about using DyNet `here

        (C++) <http://dynet.readthedocs.io/en/latest/tutorial.html#c-tutorial>`__

        and `here

        (python) <http://dynet.readthedocs.io/en/latest/tutorial.html#python-tutorial>`__,

        and `here (EMNLP 2016

        tutorial) <https://github.com/clab/dynet_tutorial_examples>`__.

        

        One aspect that sets DyNet apart from other tookits is the

        **auto-batching** feature. See the

        `documentation <http://dynet.readthedocs.io/en/latest/minibatch.html>`__

        about batching.

        

        The ``example`` folder contains a variety of examples in C++ and python.

        

        Installation

        ------------

        

        DyNet relies on a number of external programs/libraries including CMake,

        Eigen, and Mercurial (to install Eigen). CMake, and Mercurial can be

        installed from standard repositories.

        

        For example on **Ubuntu Linux**:

        

        ::

        

            sudo apt-get install build-essential cmake mercurial

        

        Or on **macOS**, first make sure the Apple Command Line Tools are

        installed, then get CMake, and Mercurial with either homebrew or

        macports:

        

        ::

        

            xcode-select --install

            brew install cmake hg  # Using homebrew.

            sudo port install cmake mercurial # Using macports.

        

        On **Windows**, see

        `documentation <http://dynet.readthedocs.io/en/latest/install.html#windows-support>`__.

        

        To compile DyNet you also need the `development version of the Eigen

        library <https://bitbucket.org/eigen/eigen>`__. **If you use any of the

        released versions, you may get assertion failures or compile errors.**

        If you don't have Eigen already, you can get it easily using the

        following command:

        

        ::

        

            hg clone https://bitbucket.org/eigen/eigen/ -r 699b659

        

        The ``-r NUM`` specified a revision number that is known to work.

        Adventurous users can remove it and use the very latest version, at the

        risk of the code breaking / not compiling. On macOS, you can install the

        latest development of Eigen using Homebrew:

        

        ::

        

            brew install --HEAD eigen

        

        C++ installation

        ~~~~~~~~~~~~~~~~

        

        You can install dynet for C++ with the following commands

        

        ::

        

            # Clone the github repository

            git clone https://github.com/clab/dynet.git

            cd dynet

            # Checkout the latest release

            git checkout tags/v2.0

            mkdir build

            cd build

            # Run CMake

            # -DENABLE_BOOST=ON in combination with -DENABLE_CPP_EXAMPLES=ON also

            # compiles the multiprocessing c++ examples

            cmake .. -DEIGEN3_INCLUDE_DIR=/path/to/eigen -DENABLE_CPP_EXAMPLES=ON

            # Compile using 2 processes

            make -j 2

            # Test with an example

            ./examples/train_xor

        

        For more details refer to the

        `documentation <http://dynet.readthedocs.io/en/latest/install.html#building>`__

        

        Python installation

        ~~~~~~~~~~~~~~~~~~~

        

        You can install DyNet for python by using the following command

        

        ::

        

            pip install git+https://github.com/clab/dynet#egg=dynet

        

        For more details refer to the

        `documentation <http://dynet.readthedocs.io/en/latest/python.html#installing-dynet-for-python>`__

        

        Citing

        ------

        

        If you use DyNet for research, please cite this report as follows:

        

        ::

        

            @article{dynet,

              title={DyNet: The Dynamic Neural Network Toolkit},

              author={Graham Neubig and Chris Dyer and Yoav Goldberg and Austin Matthews and Waleed Ammar and Antonios Anastasopoulos and Miguel Ballesteros and David Chiang and Daniel Clothiaux and Trevor Cohn and Kevin Duh and Manaal Faruqui and Cynthia Gan and Dan Garrette and Yangfeng Ji and Lingpeng Kong and Adhiguna Kuncoro and Gaurav Kumar and Chaitanya Malaviya and Paul Michel and Yusuke Oda and Matthew Richardson and Naomi Saphra and Swabha Swayamdipta and Pengcheng Yin},

              journal={arXiv preprint arXiv:1701.03980},

              year={2017}

            }

        

        Releases and Contributing

        -------------------------

        

        The current release of DyNet is

        `v2.0 <https://github.com/clab/dynet/releases/tag/v2.0>`__.

        

        We welcome any contribution to DyNet! You can find the contributing

        guidelines

        `here <http://dynet.readthedocs.io/en/latest/contributing.html>`__

        

        .. |Build Status| image:: https://travis-ci.org/clab/dynet.svg?branch=master

           :target: https://travis-ci.org/clab/dynet

        .. |Build Status| image:: https://ci.appveyor.com/api/projects/status/github/clab/dynet?svg=true

           :target: https://ci.appveyor.com/project/danielh/dynet-c3iuq

        .. |Doc build Status| image:: https://readthedocs.org/projects/dynet/badge/?version=latest

           :target: http://dynet.readthedocs.io/en/latest/

        .. |PyPI version| image:: https://badge.fury.io/py/dyNET.svg

           :target: https://badge.fury.io/py/dyNET

        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: MacOS X
Classifier: Environment :: Win32 (MS Windows)
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
