In pytorch documentation T_cur is ‘current epoch’, and T_max is the maximum number of iterations. I found these definitions a bit confusing, because typically ‘iterations’ means (dataset_size/batch_size). So for example, if I have batch_size=1, dataset_size=100, does it mean that T_max=100 should I choose to keep the learning rate decaying until the termination of the algorithm?