I have a Pytorch tensor mask
of dimensions,
torch.Size([8, 24, 24])
with unique values,
> torch.unique(mask, return_counts=True)
(tensor([0, 1, 2]), tensor([2093, 1054, 1461]))
I wish to randomly replace the number of 2s to 0s, such that the unique values and counts in the tensor become,
> torch.unique(mask, return_counts=True)
(tensor([0, 1, 2]), tensor([2500, 1054, 1054]))
I have tried using torch.where
to no success. How can this be achieved?
One of the possible solutions is through flattening via view
and numpy.random.choice
:
from numpy.random import choice
idx = torch.where(mask.view(-1) == 2)[0] # get all indicies of 2 in flat tensor
num_to_change = 2500 - 2093 # as follows from example above
idx_to_change = choice(idx, size=num_to_change, replace=False)
mask.view(-1)[idx_to_change] = 0