We explicitly need to call zero_grad() because, after loss.backward() (when gradients are computed), we need to use optimizer.step() to proceed gradient descent. More specifically, the gradients are not automatically zeroed because these two operations, loss.backward() and optimizer.step(), are separated, and optimizer.step() requires the just computed gradients.
In addition, sometimes, we need to accumulate gradient among some batches; to do that, we can simply call backward multiple times and optimize once.