You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Using GPU : 0 from 1 devices
Use Adam
Start training epoch: (0/100)
/export/home/hanxiaobing/anaconda3/envs/crosspoint/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:134: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_scheduler.step(). Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
Traceback (most recent call last):
File "train_crosspoint.py", line 261, in
train(args, io)
File "train_crosspoint.py", line 103, in train
_, point_feats, _ = point_model(data)
File "/export/home/hanxiaobing/anaconda3/envs/crosspoint/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/export/home/hanxiaobing/Documents/PlaneNet_PlaneRCNN/DGCNN_PointNet2/SensatUrban/MAE/CrossPoint/models/dgcnn.py", line 95, in forward
x = get_graph_feature(x, k=self.k)
File "/export/home/hanxiaobing/Documents/PlaneNet_PlaneRCNN/DGCNN_PointNet2/SensatUrban/MAE/CrossPoint/models/dgcnn.py", line 29, in get_graph_feature
idx_base = torch.arange(0, batch_size, device=device).view(-1, 1, 1)*num_points
RuntimeError: CUDA error: invalid device ordinal
The text was updated successfully, but these errors were encountered:
Hi @MohamedAfham
Have you ever met this bug before? Thanks a lot.
Using GPU : 0 from 1 devices
Use Adam
Start training epoch: (0/100)
/export/home/hanxiaobing/anaconda3/envs/crosspoint/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:134: UserWarning: Detected call of
lr_scheduler.step()
beforeoptimizer.step()
. In PyTorch 1.1.0 and later, you should call them in the opposite order:optimizer.step()
beforelr_scheduler.step()
. Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
Traceback (most recent call last):
File "train_crosspoint.py", line 261, in
train(args, io)
File "train_crosspoint.py", line 103, in train
_, point_feats, _ = point_model(data)
File "/export/home/hanxiaobing/anaconda3/envs/crosspoint/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/export/home/hanxiaobing/Documents/PlaneNet_PlaneRCNN/DGCNN_PointNet2/SensatUrban/MAE/CrossPoint/models/dgcnn.py", line 95, in forward
x = get_graph_feature(x, k=self.k)
File "/export/home/hanxiaobing/Documents/PlaneNet_PlaneRCNN/DGCNN_PointNet2/SensatUrban/MAE/CrossPoint/models/dgcnn.py", line 29, in get_graph_feature
idx_base = torch.arange(0, batch_size, device=device).view(-1, 1, 1)*num_points
RuntimeError: CUDA error: invalid device ordinal
The text was updated successfully, but these errors were encountered: