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==[Train] Iter: 0 | Loss: 0.9923 | Accuracy: 0.596924 == ==[Train] Iter: 1 | Loss: 0.9856 | Accuracy: 0.795410 == Traceback (most recent call last): File "main.py", line 101, in train(args) File "/home/ailab/workspace/CMQ/attMPTI/runs/mpti_train.py", line 59, in train loss, accuracy = MPTI.train(data) File "/home/ailab/workspace/CMQ/attMPTI/models/mpti_learner.py", line 67, in train query_logits, loss= self.model(support_x, support_y, query_x, query_y) File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call result = self.forward(*input, **kwargs) File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 87, in forward fg_prototypes, fg_labels = self.getForegroundPrototypes(support_feat, fg_mask, k=self.n_subprototypes) File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 187, in getForegroundPrototypes class_prototypes = self.getMutiplePrototypes(feat, k) File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 148, in getMutiplePrototypes fps_index = fps(feat, None, ratio=ratio, random_start=False).unique() File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/tensor.py", line 384, in unique return torch.unique(self, sorted=sorted, return_inverse=return_inverse, return_counts=return_counts, dim=dim) File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/functional.py", line 471, in unique return_counts=return_counts, RuntimeError: transform: failed to synchronize: cudaErrorIllegalAddress: an illegal memory access was encountered
Is this problem caused by my insufficient memory?I hope someone can answer my doubts
The text was updated successfully, but these errors were encountered:
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==[Train] Iter: 0 | Loss: 0.9923 | Accuracy: 0.596924 ==
==[Train] Iter: 1 | Loss: 0.9856 | Accuracy: 0.795410 ==
Traceback (most recent call last):
File "main.py", line 101, in
train(args)
File "/home/ailab/workspace/CMQ/attMPTI/runs/mpti_train.py", line 59, in train
loss, accuracy = MPTI.train(data)
File "/home/ailab/workspace/CMQ/attMPTI/models/mpti_learner.py", line 67, in train
query_logits, loss= self.model(support_x, support_y, query_x, query_y)
File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 87, in forward
fg_prototypes, fg_labels = self.getForegroundPrototypes(support_feat, fg_mask, k=self.n_subprototypes)
File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 187, in getForegroundPrototypes
class_prototypes = self.getMutiplePrototypes(feat, k)
File "/home/ailab/workspace/CMQ/attMPTI/models/mpti.py", line 148, in getMutiplePrototypes
fps_index = fps(feat, None, ratio=ratio, random_start=False).unique()
File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/tensor.py", line 384, in unique
return torch.unique(self, sorted=sorted, return_inverse=return_inverse, return_counts=return_counts, dim=dim)
File "/root/anaconda3/envs/attmpti/lib/python3.6/site-packages/torch/functional.py", line 471, in unique
return_counts=return_counts,
RuntimeError: transform: failed to synchronize: cudaErrorIllegalAddress: an illegal memory access was encountered
Is this problem caused by my insufficient memory?I hope someone can answer my doubts
The text was updated successfully, but these errors were encountered: