Hi,
after several epochs, I encounter the “RuntimeError: CUDA error: device-side assert triggered” in the interpolation function. I already checked if the there is an error in the indexing but seems everything alright. I appreciate any useful hint.
system:
Versions of relevant libraries:
[pip3] numpy==1.21.5
[pip3] pytorch-lightning==1.5.2
[pip3] torch==1.10.1
[pip3] torch-cluster==1.5.9
[pip3] torch-geometric==2.0.3
[pip3] torch-points-kernels==0.7.0
[pip3] torch-scatter==2.0.9
[pip3] torch-sparse==0.6.12
[pip3] torch-spline-conv==1.2.1
[pip3] torchaudio==0.10.1
[pip3] torchmetrics==0.6.0
[pip3] torchvision==0.11.2
def interpolation(xyz, new_xyz, feat, offset, new_offset, k=3):
“”"
input: xyz: (m, 3), new_xyz: (n, 3), feat: (m, c), offset: (b), new_offset: (b)
output: (n, c)
“”"
assert xyz.is_contiguous() and new_xyz.is_contiguous() and feat.is_contiguous()
idx, dist = knnquery(k, xyz, new_xyz, offset, new_offset) # (n, 3), (n, 3)
dist_recip = 1.0 / (dist + 1e-8) # (n, 3)
norm = torch.sum(dist_recip, dim=1, keepdim=True)
weight = dist_recip / norm # (n, 3)
new_feat = torch.cuda.FloatTensor(new_xyz.shape[0], feat.shape[1]).zero_()
for i in range(k):

    new_feat += feat[idx[:, i].long(), :] * weight[:, i].unsqueeze(-1)
    #print(feat.size(),idx[:, i])
return new_feat