The tensors should be broadcastable, so this would work:
a = torch.randn(32, 4, 13)
b = torch.randn(32, 4, 13)

c = torch.empty((32, 1, 1), dtype=torch.uint8).random_(2)

d = torch.where(c, a, b)

In your case, just get a new view on c:
c = c.view(-1, 1, 1)