Hi,
I’d have a quick question: In the ResNet paper, in section 4.2, an architecture is described for the CIFAR10 dataset. When they describe using a very deep ResNet, they write:

So we use 0.01 to warm up the training until the training error is below
80% (about 400 iterations), and then go back to 0.1 and continue training.

Therefore, I would like to have the following learning rate schedule:

LR = 10^{-2} for the first two epochs,
LR = 10^{-1} for the rest of the training.

However, I haven’t found a way to achieve exactly this (cyclical learning rates would only gradually increase the learning rate, not at once). Any help would be appreciated. (-: