This is a code repository to efficiently train a deconvolutional neural network with rectified linear units.
It also currently relies on a change to
pylearn2.sandbox.cuda_convnet.pool.py that defines a
grad method for the
MaxPoolGrad class, which can be useful in some cases...
ICLR 2015 Paper Repo
If you came here via our paper An Analysis of Unsupervised Pre-training in Light of Recent Advances, please go here to access the experiments we ran.
Layout of the code
There are currently 3 main modules:
- datasets - generic dataset classes
- layers - layer definitions
- util - utilities for training, evaluating, and saving/loading checkpoints