You could try to use itertools.product:
from itertools import product

from torch.utils.data import TensorDataset, DataLoader

loaderA = DataLoader(
    TensorDataset(torch.arange(6)), batch_size=2)
loaderB = DataLoader(
    TensorDataset(torch.arange(1, 7) * 10), batch_size=2)

for a, b in product(loaderA, loaderB):
    print(a, b)

> [tensor([0, 1])] [tensor([10, 20])]
  [tensor([0, 1])] [tensor([30, 40])]
  [tensor([0, 1])] [tensor([50, 60])]
  [tensor([2, 3])] [tensor([10, 20])]
  [tensor([2, 3])] [tensor([30, 40])]
  [tensor([2, 3])] [tensor([50, 60])]
  [tensor([4, 5])] [tensor([10, 20])]
  [tensor([4, 5])] [tensor([30, 40])]
  [tensor([4, 5])] [tensor([50, 60])]