6 ms·
It's nice to have the Keras front-end for TF - less boilerplate etc. I don't think there would be a reason why Keras couldn't sit on PyTorch but I can't see an
by mamp 9y ago
It's nice to have the Keras front-end for TF - less boilerplate etc.
I don't think there would be a reason why Keras couldn't sit on PyTorch but I can't see any work on this.
Keras is very productive unless you are doing NN research. Also you can also run it using CNTK if you want speed up RNNs which are slower on TF compared with CNTK.
- Q6T46nT668w6i3m 9y agoI use Keras for machine learning research and find that it works extremely well. The one advantage of PyTorch is more flexible broadcasting, but that introduces other problems. A major advantage of Keras is that if you’re using a standard training scheme (e.g. training a convolutional neural network for image classification), your research will be entirely focused on either the underlying architecture (that’s easily summarized and serialized), your custom layers (my favorite abstraction for convolutional neural networks), and losses. Keras’ abstractions eliminate stuff like IO that I find extremely distracting.