distance_transform_edt not always working with cuCIM backend #7660
Description
Describe the bug
The distance_transform_edt returns all zero in special cases when cuCIM is installed and used as a backend.
This happens when convert_to_cupy() decides that the data array needs to be copied here:
To Reproduce
!pip install torch
!pip install cucim
!pip install monai
!pip install numpy
from monai.transforms import distance_transform_edt
import torch
import numpy as np
# create a c-contiguous array
mask = np.zeros((1, 4, 4))
# make it f-contiguous to force convert_to_cupy to copy the data array later on
mask2 = np.asfortranarray(mask)
# convert to torch tensor to make distance_transform_edt use cuCIM backend
mask = torch.tensor(mask, device='cuda')
mask2 = torch.tensor(mask2, device='cuda')
# set half of the mask to foreground
mask[0, 0:2, :,] = 1
mask2[0, 0:2, :,] = 1
# confirm masks are the same
print(mask)
print(mask2)
# calculate distance transform
edt = distance_transform_edt(mask)
edt2 = distance_transform_edt(mask2)
# check if the results are the same
print(edt)
print(edt2)
tensor([[[1., 1., 1., 1.],
[1., 1., 1., 1.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]]], device='cuda:0', dtype=torch.float64)
tensor([[[1., 1., 1., 1.],
[1., 1., 1., 1.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]]], device='cuda:0', dtype=torch.float64)
tensor([[[2., 2., 2., 2.],
[1., 1., 1., 1.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]]], device='cuda:0')
tensor([[[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]]], device='cuda:0')
Expected behavior
Results should be the same, but the second output is all zero.