That’s where I’m stuck, using those two classes (datasetA and datasetB) to use dataloaders.
I was iterating earlier like,
for batch,(imgs,pids,camids) in enumerate(trainloader):

Now I want to be able to feed half of the batch to augmented 1(datasetA) and the other half to augmented 2(datasetB). Your approach (self.data) expects a Tensor , instead i want to use your approach with the form I have i.e
dataset_ = dataset_manager.init_img_dataset(
    root='data',name=dataset_name # Can be datasetA or datasetB
)

So as per your approach ( i want to implement in class datasetA and class datasetB).
So that it may become of the form self.data = dataset_) So how can I possibly do that ?