Let’s assume I have a tensor.
x  = torch.randn(64, 10, 2, 30)
# (batch, some length, some observation, some feature dimension)

And I want to apply dropout at the observation dimension i.e either all 30 features of 0 or either all 30 values of 1.
I tried looking for it but I couldn’t find anything that could work or maybe I misunderstood some implementation.
Anyone has any idea how I can do it?