https://github.com/mila-iqia/blocks

A Theano framework for building and training neural networks
https://github.com/mila-iqia/blocks

Last synced: 4 months ago
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A Theano framework for building and training neural networks

• Host: GitHub
• URL: https://github.com/mila-iqia/blocks
• Owner: mila-iqia
• License: other
• Created: 2014-10-06T00:08:32.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2019-02-19T12:41:38.000Z (over 5 years ago)
• Last Synced: 2024-03-10T20:30:15.033Z (4 months ago)
• Language: Python
• Homepage:
• Size: 4.55 MB
• Stars: 1,160
• Watchers: 87
• Forks: 351
• Open Issues: 192
• Metadata Files:
  • Readme: README.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

Lists

• awesome-rnn - Blocks
• awesome-stars - mila-iqia/blocks - A Theano framework for building and training neural networks (Python)
• my-awesome-stars - mila-iqia/blocks - A Theano framework for building and training neural networks (Python)

README

        
.. image:: https://img.shields.io/coveralls/mila-udem/blocks.svg

   :target: https://coveralls.io/r/mila-udem/blocks

.. image:: https://travis-ci.org/mila-udem/blocks.svg?branch=master

   :target: https://travis-ci.org/mila-udem/blocks

.. image:: https://readthedocs.org/projects/blocks/badge/?version=latest

   :target: https://blocks.readthedocs.org/

.. image:: https://img.shields.io/scrutinizer/g/mila-udem/blocks.svg

   :target: https://scrutinizer-ci.com/g/mila-udem/blocks/

.. image:: https://requires.io/github/mila-udem/blocks/requirements.svg?branch=master

   :target: https://requires.io/github/mila-udem/blocks/requirements/?branch=master

.. image:: https://img.shields.io/badge/license-MIT-blue.svg

   :target: https://github.com/mila-udem/blocks/blob/master/LICENSE

Blocks

======

Blocks is a framework that helps you build neural network models on top of

Theano. Currently it supports and provides:

* Constructing parametrized Theano operations, called "bricks"

* Pattern matching to select variables and bricks in large models

* Algorithms to optimize your model

* Saving and resuming of training

* Monitoring and analyzing values during training progress (on the training set

  as well as on test sets)

* Application of graph transformations, such as dropout

In the future we also hope to support:

* Dimension, type and axes-checking

See Also:

   * `Fuel`_, the data processing engine developed primarily for Blocks.

   * `Blocks-examples`_ for maintained examples of scripts using Blocks.

   * `Blocks-extras`_ for semi-maintained additional Blocks components.

Citing Blocks

   If you use Blocks or Fuel in your work, we'd really appreciate it if you could cite the following paper:

   

   Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, and Yoshua Bengio, "`Blocks and Fuel: Frameworks for deep learning`_," *arXiv preprint arXiv:1506.00619 [cs.LG]*, 2015.

    

Documentation

   Please see the documentation_ for more information.

   

Contributing

   If you want to contribute, please make sure to read the `developer guidelines`_.

.. _documentation: http://blocks.readthedocs.org

.. _developer guidelines: http://blocks.readthedocs.org/en/latest/development/index.html

.. _Blocks and Fuel\: Frameworks for deep learning: http://arxiv.org/abs/1506.00619

.. _Blocks-examples: https://github.com/mila-udem/blocks-examples 

.. _Blocks-extras: https://github.com/mila-udem/blocks-extras

.. _Fuel: https://github.com/mila-udem/fuel