new warning messages from notebooks

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.

Iniziare da 3d_segmentation/unet_segmentation_3d_ignite.ipynb e riprodurne l’esecuzione con papermill utilizzando le versioni delle dipendenze indicate nel report. Verificare quali messaggi provengono dall’esecuzione del notebook e quali dall’ambiente TensorFlow e CUDA; l’issue non definisce quali avvisi debbano essere rimossi né quale dovrebbe essere il comportamento al completamento.