distance_transform_edt not always working with cuCIM backend

[aaronkujawa]

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.

[KumoLiu]

Hi @aaronkujawa, thanks for the reporting. I have created a PR to fix it.
Main reason is that indices_ may not always be a shallow copy for F-order input as it constantly converts to C-order.

MONAI/monai/transforms/utils.py

Line 2209 in ffd4454

indices_ = convert_to_cupy(indices)

MONAI/monai/utils/type_conversion.py

Line 262 in ffd4454

data = cp.ascontiguousarray(data)

[aaronkujawa]

Hi @KumoLiu , thanks for the quick fix!