No, DataParallel in its basic form is just applied on the model, such that the input batch will be split in dim0 and each specified GPU will get a chunk. The forward and backward passes are executed in parallel and all necessary gradients etc. are finally gathered on the default device.
Your training routine should not change if you are using DataParallel.
However, in the mentioned code base, the Trainer class is handling the models, optimizers etc.
Using DataParallel by just wrapping your model in it and leaving all other code snippets as they were, is thus most likely not possible, and would need some code refactoring.