[minimaxir]

Speed is one thing, but the key value proposition of Keras for me that rarely comes up in these comparisons are Keras’s native utility functions, including easy and correct text tokenization/padding, easy OHE of categorical variables without using sklearn, and easy model saving/loading from an .hdf5 file. (Although I am not an expert on PyTorch and not as familiar with the ETL pipeline for that)

[rjdagost]

I agree strongly with the ease of model saving / reloading in Keras. I found this basic functionality to be exasperatingly difficult and cumbersome in TensorFlow.