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Hi @Mgithus, I have tried this tutorial with MONAI v1.2 image and I can't reproduce the error. Could you please try it with the latest stable version? |
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Thnx @KumoLiu, I have tried but did not able to resolve it. |
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Hope this can help, https://discuss.pytorch.org/t/summarize-the-reasons-for-the-common-error-illegal-memory-access/130406. |
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Data information:
The dataset info given on colab notebook of this code on monai website (https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/swin_unetr_brats21_segmentation_3d.ipynb) is as follows:
Modality: MRI Size: 1470 3D volumes (1251 Training + 219 Validation)
In 1251 training samples each has 4 3D modalities and 1 3D segmentation mask in it.(1251*5 = 6255 total images)
image shape: (240, 240, 155)
label shape: (240, 240, 155)
Code information:
Trying to run following code from monai website without any modifications:
[https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/swin_unetr_brats21_segmentation_3d.ipynb]
Error:
Epoch 0/4 569/1001 loss: nan time 0.83s
Epoch 0/4 570/1001 loss: nan time 4.15s
Traceback (most recent call last):
File "notebook_of_swin_unetr.py", line 429, in
) = trainer(
File "notebook_of_swin_unetr.py", line 346, in trainer
train_loss = train_epoch(
File "notebook_of_swin_unetr.py", line 261, in train_epoch
loss.backward()
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/tensor.py", line 214, in backward
return handle_torch_function(
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/overrides.py", line 1060, in handle_torch_function
result = overloaded_arg.torch_function(public_api, types, args, kwargs)
File "/home/dlrs/.local/lib/python3.8/site-packages/monai/data/meta_tensor.py", line 249, in torch_function
ret = super().torch_function(func, types, args, kwargs)
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/tensor.py", line 995, in torch_function
ret = func(*args, **kwargs)
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/autograd/init.py", line 130, in backward
Variable._execution_engine.run_backward(
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/autograd/function.py", line 89, in apply
return self._forward_cls.backward(self, *args) # type: ignore
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/utils/checkpoint.py", line 99, in backward
torch.autograd.backward(outputs, args)
File "/home/dlrs/.local/lib/python3.8/site-packages/torch/autograd/init.py", line 130, in backward
Variable._execution_engine.run_backward(
RuntimeError: transform: failed to synchronize: cudaErrorIllegalAddress: an illegal memory access was encountered
(aug10) dlrs@spml3:~/Desktop/jul_25$ python -c 'import monai; monai.config.print_debug_info()'
"sox" backend is being deprecated. The default backend will be changed to "sox_io" backend in 0.8.0 and "sox" backend will be removed in 0.9.0. Please migrate to "sox_io" backend. Please refer to pytorch/audio#903 for the detail.
Printing MONAI config...
MONAI version: 1.0.0
Numpy version: 1.21.6
Pytorch version: 1.7.1+cu110
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: 1700933
MONAI file: /home/dlrs/.local/lib/python3.8/site-packages/monai/init.py
Optional dependencies:
Pytorch Ignite version: 0.4.8
Nibabel version: 5.1.0
scikit-image version: 0.21.0
Pillow version: 10.0.0
Tensorboard version: 2.14.0
gdown version: 4.7.1
TorchVision version: 0.8.2+cu110
tqdm version: 4.66.1
lmdb version: 1.4.1
psutil version: 5.9.5
pandas version: 2.0.3
einops version: 0.6.1
transformers version: 4.31.0
mlflow version: 2.5.0
pynrrd version: 1.0.0
For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies
================================
Printing system config...
System: Linux
Linux version: Ubuntu 20.04.6 LTS
Platform: Linux-5.15.0-78-generic-x86_64-with-glibc2.17
Processor: x86_64
Machine: x86_64
Python version: 3.8.17
Process name: python
Command: ['python', '-c', 'import monai; monai.config.print_debug_info()']
Open files: [popenfile(path='/home/dlrs/.anaconda/navigator/Code/logs/20230814T112632/ptyhost.log', fd=39, position=0, mode='a', flags=33793), popenfile(path='/snap/code/137/usr/share/code/resources/app/node_modules.asar', fd=41, position=64064, mode='r', flags=32768), popenfile(path='/snap/code/137/usr/share/code/v8_context_snapshot.bin', fd=103, position=0, mode='r', flags=32768)]
Num physical CPUs: 4
Num logical CPUs: 4
Num usable CPUs: 4
CPU usage (%): [36.9, 40.8, 42.9, 49.4]
CPU freq. (MHz): 1994
Load avg. in last 1, 5, 15 mins (%): [59.2, 67.2, 75.0]
Disk usage (%): 45.8
Avg. sensor temp. (Celsius): UNKNOWN for given OS
Total physical memory (GB): 15.6
Available memory (GB): 9.3
Used memory (GB): 5.7
================================
Printing GPU config...
Num GPUs: 1
Has CUDA: True
CUDA version: 11.0
cuDNN enabled: True
cuDNN version: 8005
Current device: 0
Library compiled for CUDA architectures: ['sm_37', 'sm_50', 'sm_60', 'sm_70', 'sm_75', 'sm_80']
GPU 0 Name: NVIDIA GeForce GTX 1080 Ti
GPU 0 Is integrated: False
GPU 0 Is multi GPU board: False
GPU 0 Multi processor count: 28
GPU 0 Total memory (GB): 10.9
GPU 0 CUDA capability (maj.min): 6.1
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