About Olympic PyTorch

My first foray into deep learning code was Tensorflow. Myself (and many others) found Tensorflow to be powerful but unwieldy. Next I moved onto Keras, which is a brilliant library that makes deep learning very accessible as it strips away most of the boilerplate code.

As I started to want more control and to implement research architectures I turned to PyTorch as its dynamic graph and clean interface made it not only relatively easy to use but also fun. However I missed some of the abstractions and utilities of Keras.

There are other libraries similar to this one (notably ignite and torchsample) but they weren’t quite what I wanted so I decided to make what I wanted myself. And by make I mean copy and paste from Keras (MIT license) because don’t fix what ain’t broken.

Future development

I only intend to update this library sufficient to keep it compatible with the latest PyTorch and maintain feature parity with Keras Callbacks. I will not be adding any more features beyond what already exists.