No. torch.optim.lr_scheduler is used to adjust only the hyperparameter of learning rate in a model.
Early stopping refers to another hyperparameter, the number of train epochs. It is the stopping of training when loss reaches a plateau. Typically, models are over-parameterized meaning that if you keep training for “too many” epochs, they will begin to overfit on junk info (noise) from the dataset. To prevent overfitting, use early stopping; this means, when the loss stops decreasing on the validation set, stop training.
Jason has a great post on early stopping here 95.