This module contains two implementations of CTC [Graves2006] for Chainer.
1. Is build using custom CUDA kernels / Cython code
2. Is a wrapper around Baidu's warp-ctc
The first one is faster than the original Chainer implementation but slower than warp-ctc. However, it allows for easier modification of the CTC algorithm. If you want to tinker with it, use the first method. If you just want speed, use warp-ctc.
1. Chainer
2. Python 3.x
3. GPU + CUDA for high performance
First, clone this repository.
git clone https://github.com/jheymann85/chainer_ctc.git
Next, we need to install warp-ctc. This can be done with the install script
chmod +x install_warp-ctc.sh
./install_warp-ctc.sh
Now you can install the module
pip install --user -e .
Finally, run the tests to see if the installation was successful
nosetests tests/
Baidu for their incredible fast warp-ctc implementation.
[Graves2006]: Alex Graves, Santiago Fernandez, Faustino Gomez, Jurgen Schmidhuber Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf