Training of your neural network still strangely slow? Better check out your embeddings!
Believe or not, but implementations of embedding layers built-in the most popular deep learning frameworks (including Torch, PyTorch and TensorFlow) are terribly inefficient. All because their strict commitment to the perfect determinism. While it’s a good thing in general, it often make things not very CUDA-friendly. That’s what’s slowing you down!
If you’re ready to accept some nondeterminism in your training process (and admit it, you don’t really care), make sure to check the new lib from our colleague, Darek: pytorch-fast-embedding – the drop-in replacement for PyTorch embeddings that instantly gives you up to 35x speed up.
That’s 5 hours instead of 7 days. How cool is that?!
