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
Hi, I work out of the Michelson Center at USC and I'm trying to run the cbvaegan2D_target.sh script in the /examples/training_scripts folder.
My objective ultimately is to use the model on labeled soft xray tomography data to predict the insulin vesicle label field given membrane, nucleus, and mitochondria labels.
I am running into the following error after the model is initialized. Any help would be great. Thank you!
Traceback (most recent call last):
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/bin/ic_train_model", line 33, in
sys.exit(load_entry_point('pytorch-integrated-cell', 'console_scripts', 'ic_train_model')())
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/bin/train_model.py", line 484, in main
model.train()
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/models/base_model.py", line 89, in train
errors, zLatent = self.iteration()
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/models/cbvaegan_target2.py", line 185, in iteration
minimaxDecDLoss.mul(self.lambda_decD_loss).backward()
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/lib/python3.7/site-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/lib/python3.7/site-packages/torch/autograd/init.py", line 132, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [512, 15360]] is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).
The text was updated successfully, but these errors were encountered:
Hi, I work out of the Michelson Center at USC and I'm trying to run the cbvaegan2D_target.sh script in the /examples/training_scripts folder.
My objective ultimately is to use the model on labeled soft xray tomography data to predict the insulin vesicle label field given membrane, nucleus, and mitochondria labels.
I am running into the following error after the model is initialized. Any help would be great. Thank you!
Traceback (most recent call last):
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/bin/ic_train_model", line 33, in
sys.exit(load_entry_point('pytorch-integrated-cell', 'console_scripts', 'ic_train_model')())
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/bin/train_model.py", line 484, in main
model.train()
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/models/base_model.py", line 89, in train
errors, zLatent = self.iteration()
File "/data/jpfrancis/Development/related_work_code/pytorch_integrated_cell/integrated_cell/models/cbvaegan_target2.py", line 185, in iteration
minimaxDecDLoss.mul(self.lambda_decD_loss).backward()
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/lib/python3.7/site-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/jpfrancis/anaconda3/envs/pytorch_integrated_cell/lib/python3.7/site-packages/torch/autograd/init.py", line 132, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [512, 15360]] is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).
The text was updated successfully, but these errors were encountered: