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Blocks and Fuel: Frameworks for deep learning · Around

2015

Blocks and Fuel: Frameworks for deep learning

van Merriënboer, Bart, Bahdanau, Dzmitry, Dumoulin, Vincent et al.

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We introduce two Python frameworks to train neural networks on large datasets: Blocks and Fuel.

Blocks is based on Theano, a linear algebra compiler with CUDA-support.
It facilitates the training of complex neural network models by providing parametrized Theano operations, attaching metadata to Theano's symbolic computational graph, and providing an extensive set of utilities to assist training the networks, e.g.
training algorithms, logging, monitoring, visualization, and serialization.

Built on

Theano: a CPU and GPU math expression compiler
James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, and Yoshua Bengio · 2010
Earlier work this paper cites.
Theano: new features and speed improvements
Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio · 2012
Earlier work this paper cites.
On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio · 2013
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