[aab0]

What sort of performance can be expected compared to running in the terminal? How large NNs will this scale to in practice? I see a 50-layer resnet is mentioned; but not 1000-layers?

[dharma1]

On these demos, I'm getting several seconds on the imagenet inception v3 recognition on an i7 macbook pro (nvidia gpu), on both gpu and cpu modes.

I've built tensorflow for android, running inceptionv3 trained on imagenet and it's much faster, running just on mobile CPU pretty much realtime, around 5fps. On a desktop CPU/GPU it's obviously even faster

[transcranial]

You mean with tensorflow or theano as the backend? They have all kinds of optimizations that isn't possible to replicate here yet. There is certainly room for optimization! Also, 1000-layer resnets should theoretically be possible, but probably isn't that practical. Lots of exciting work happening in searching for more efficient architectures.

[augustt]

1000 layer networks aren't used in practice. 50 layers is enough for state-of-the art performance.

[nl]

It sounds like inference (prediction) performance is ok (probably < 1 second for images with ResNet50).

I doubt training performance would be very fun.