Exercise

Training CNNs

Similarly to what you did in Chapter 2, you are going to train a neural network. This time however, you will train the CNN you built in the previous lesson, instead of a fully connected network. The packages you need have been imported for you and the network (called net) instantiated. The cross-entropy loss function (called criterion) and the Adam optimizer (called optimizer) are also available. We have subsampled the training set so that the training goes faster, and you are going to use a single epoch.

Instructions

100 XP

Compute the predictions from the net.
Using the predictions and the labels, compute the loss function.
Compute the gradients for each weight.
Update the weights using the optimizer.