fast-neural-style
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Computation issue
Hi, Thanks for sharing code! I have a question regarding computation. It seems that the computation of perceptual loss is much heavier than MSE loss. In my experiment, using perceptual loss will make training much slower and batch size much smaller. Is it normal?
Hi there,
Yes, perceptual loss involves more computation as it takes intermediate activations from different layers, calculates the gram matrices, and back-propagation on the MSE of the differences between two images. It also uses more memory.
But I am not sure how much slower and how much smaller are normal. You can try to reduce the number of layers used in LossNetwork and see if there is a visible difference.