So you wanted to do is multi-scale training?
Then perhaps you could do:
for batch1, batch2, batch3 in zip(daloaders[0], dataloaders[1], dataloaders[2]):
    input1, label1 = batch1
    input2, label2 = batch2
    input3, label3 = batch3

    pred1 = model(input1)
    pred2 = model(input2)
    pred3 = model(input3)
    loss1 = criterion(pred1, label1)
    loss2 = criterion(pred2, label2)
    loss3 = criterion(pred3, label3)
    loss = loss1 + loss2 + loss3
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()