Implement RNN/LSTMs for Leaf

[MichaelHirn]

This issue makes part of #20 more concrete.

Recurrent Neural Networks, became an effective Neural Network architecture, that we would like to implement in Leaf as well. The operations could probably be composed of BLAS operations with collenchyma-blas. Differentiation for backpropagation is another topic, that might better be solved with Auto Differentiation.

[johnnyman727]

@MichaelHirn if this isn't super timer critical, I can own this task. I will need some hand-holding to get started. Where would be the best place to start?

[MichaelHirn]

Awesome!

I think it should be verily straight forward. Two resources about RNN and performance, that look interesting and might be helpful for technical implementation.

• Introduction to RNNs by Karpathy
• Optimizing RNN performance

The rest is just adding a new common layer to Leaf, using the BLAS operations from collenchyma-nn. You can reach @hobofan anytime on the gitter chat for any guidance.

If you succeed we the implementation, we are super thrilled to publish the Benchmarks of your RNN/LSTM implementation on Deep Learning Benchmarks and compare them with RNN implementations of other Frameworks.

[MichaelHirn]

As an update:

cuDNN v5, which will be released for early developers in a few weeks, will come with primitives for LSTM/RNNs.

[carlthome]

Adding most of the optimizations described in cuDNN 5 here would easily make leaf the fastest basic LSTM implementation out there.

[robsmith11]

Was any progress made on this? I might try to add LSTM support in the future.