Project-MONAI / Project-MONAI/tutorials
new warning messages from notebooks
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Description
Describe the bug
02:28:58 Running ./3d_segmentation/unet_segmentation_3d_ignite.ipynb
02:28:58 Checking PEP8 compliance...
02:28:59 Running notebook...
02:28:59 Before:
02:28:59 "max_epochs = 10\n",
02:28:59 After:
02:28:59 "max_epochs = 1\n",
02:29:03 MONAI version: 1.0.0rc1+9.ge98226dd
02:29:03 Numpy version: 1.22.4
02:29:03 Pytorch version: 1.10.2+cu102
02:29:03 MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
02:29:03 MONAI rev id: e98226dd6d0fb56ff344bc9122c68f9c8a3af96e
02:29:03 MONAI __file__: /home/jenkins/agent/workspace/Monai-notebooks/MONAI/monai/__init__.py
02:29:03
02:29:03 Optional dependencies:
02:29:03 Pytorch Ignite version: 0.4.10
02:29:03 Nibabel version: 4.0.2
02:29:03 scikit-image version: 0.19.3
02:29:03 Pillow version: 7.0.0
02:29:03 Tensorboard version: 2.10.0
02:29:03 gdown version: 4.5.1
02:29:03 TorchVision version: 0.11.3+cu102
02:29:03 tqdm version: 4.64.0
02:29:03 lmdb version: 1.3.0
02:29:03 psutil version: 5.9.1
02:29:03 pandas version: 1.1.5
02:29:03 einops version: 0.4.1
02:29:03 transformers version: 4.21.3
02:29:03 mlflow version: 1.28.0
02:29:03 pynrrd version: 0.4.3
02:29:03
02:29:03 For details about installing the optional dependencies, please visit:
02:29:03 https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies
02:29:03
02:29:04 /opt/conda/lib/python3.8/site-packages/papermill/iorw.py:153: UserWarning: the file is not specified with any extension : -
02:29:04 warnings.warn(
02:29:25
Executing: 0%| | 0/29 [00:00<?, ?cell/s]
Executing: 3%|▎ | 1/29 [00:01<00:36, 1.32s/cell]
Executing: 10%|█ | 3/29 [00:05<00:52, 2.01s/cell]
Executing: 17%|█▋ | 5/29 [00:09<00:44, 1.84s/cell]
Executing: 38%|███▊ | 11/29 [00:16<00:26, 1.45s/cell]
Executing: 45%|████▍ | 13/29 [00:21<00:25, 1.62s/cell]
Executing: 52%|█████▏ | 15/29 [00:21<00:17, 1.22s/cell]2022-09-09 01:29:25.282097: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
02:29:25 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
02:29:25 2022-09-09 01:29:25.450820: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
02:29:25 2022-09-09 01:29:25.490201: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
02:29:26 2022-09-09 01:29:26.138841: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib/x86_64-linux-gnu:/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
02:29:26 2022-09-09 01:29:26.138936: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib/x86_64-linux-gnu:/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
02:29:26 2022-09-09 01:29:26.138944: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with 3d_segmentation/unet_segmentation_3d_ignite.ipynb and reproduce its papermill execution using the dependency versions shown in the report. Inspect which messages come from notebook execution versus the TensorFlow and CUDA environment; the issue does not define which warnings should be removed or what the completed behavior should be.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python, pytorch
- Domain
- machine-learning, testing-qa
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100