Project-MONAI / Project-MONAI/tutorials

warning msgs `auto3dseg/notebooks/hpo_optuna.ipynb`

Offen
#1,118 3 Kommentare 0 Reaktionen 0 zugewiesene Personen Auf GitHub ansehen

Dieses Issue hat noch niemand übernommen.

Vorherrschende Sprache
Jupyter Notebook
Sterne
2.5k
Forks
803
Ø Merge
6 T. 22 Std.
Gemergte PRs (30 T.)
3

Beschreibung

[2022-12-19T17:36:30.048Z] Running ./auto3dseg/notebooks/hpo_optuna.ipynb
[2022-12-19T17:36:30.048Z] Checking PEP8 compliance...
[2022-12-19T17:36:30.609Z] Running notebook...
[2022-12-19T17:36:30.609Z] Before:
[2022-12-19T17:36:30.609Z]     "max_epochs = 2\n",
[2022-12-19T17:36:30.609Z] After:
[2022-12-19T17:36:30.609Z]     "max_epochs = 1\n",
[2022-12-19T17:36:34.777Z] MONAI version: 1.1.0rc1+49.gb159ce78
[2022-12-19T17:36:34.777Z] Numpy version: 1.22.2
[2022-12-19T17:36:34.777Z] Pytorch version: 1.10.2+cu102
[2022-12-19T17:36:34.777Z] MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
[2022-12-19T17:36:34.777Z] MONAI rev id: b159ce78d0ee14041e6f1f19f478394d91ab1d85
[2022-12-19T17:36:34.777Z] MONAI __file__: /home/jenkins/agent/workspace/Monai-notebooks/MONAI/monai/__init__.py
[2022-12-19T17:36:34.777Z] 
[2022-12-19T17:36:34.777Z] Optional dependencies:
[2022-12-19T17:36:34.777Z] Pytorch Ignite version: 0.4.10
[2022-12-19T17:36:34.777Z] Nibabel version: 4.0.2
[2022-12-19T17:36:34.777Z] scikit-image version: 0.19.3
[2022-12-19T17:36:34.777Z] Pillow version: 7.0.0
[2022-12-19T17:36:34.777Z] Tensorboard version: 2.11.0
[2022-12-19T17:36:34.777Z] gdown version: 4.6.0
[2022-12-19T17:36:34.777Z] TorchVision version: 0.11.3+cu102
[2022-12-19T17:36:34.777Z] tqdm version: 4.64.1
[2022-12-19T17:36:34.777Z] lmdb version: 1.3.0
[2022-12-19T17:36:34.777Z] psutil version: 5.9.2
[2022-12-19T17:36:34.777Z] pandas version: 1.1.5
[2022-12-19T17:36:34.777Z] einops version: 0.6.0
[2022-12-19T17:36:34.777Z] transformers version: 4.21.3
[2022-12-19T17:36:34.777Z] mlflow version: 2.0.1
[2022-12-19T17:36:34.777Z] pynrrd version: 1.0.0
[2022-12-19T17:36:34.777Z] 
[2022-12-19T17:36:34.777Z] For details about installing the optional dependencies, please visit:
[2022-12-19T17:36:34.777Z]     https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies
[2022-12-19T17:36:34.777Z] 
[2022-12-19T17:36:35.706Z] /opt/conda/lib/python3.8/site-packages/papermill/iorw.py:153: UserWarning: the file is not specified with any extension : -
[2022-12-19T17:36:35.706Z]   warnings.warn(
[2022-12-19T17:36:58.023Z] 
Executing:   0%|          | 0/23 [00:00<?, ?cell/s]
Executing:   4%|▍         | 1/23 [00:01<00:34,  1.56s/cell]
Executing:  13%|█▎        | 3/23 [00:06<00:43,  2.16s/cell]
Executing:  22%|██▏       | 5/23 [00:09<00:35,  1.97s/cell]
Executing:  30%|███       | 7/23 [00:10<00:21,  1.35s/cell]
Executing:  57%|█████▋    | 13/23 [00:14<00:08,  1.21cell/s]
Executing:  91%|█████████▏| 21/23 [00:14<00:00,  2.64cell/s]2022-12-19 17:36:57.804411: 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
[2022-12-19T17:36:58.023Z] To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
[2022-12-19T17:36:58.023Z] 2022-12-19 17:36:57.947004: I tensorflow/core/util/port.cc:104] 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`.
[2022-12-19T17:36:58.951Z] 2022-12-19 17:36:58.670627: W tensorflow/compiler/xla/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: /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
[2022-12-19T17:36:58.951Z] 2022-12-19 17:36:58.670708: W tensorflow/compiler/xla/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: /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
[2022-12-19T17:36:58.951Z] 2022-12-19 17:36:58.670715: 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.
[2022-12-19T17:37:01.470Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:01.470Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:01.470Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:01.470Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:01.470Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:02.837Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:04.728Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] 
Executing:  96%|█████████▌| 22/23 [00:30<00:00,  2.64cell/s]Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:06.579Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:08.471Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:10.358Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:10.358Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:10.358Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:10.358Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:10.358Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:12.244Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:12.244Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:12.244Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:12.244Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:12.244Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:14.130Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:14.130Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:14.130Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
[2022-12-19T17:37:14.130Z] Default upsampling behavior when mode=trilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.

Beitragsleitfaden

Beitragsleitfaden öffnen

Erste Schritte

  1. Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
  3. Forke das Repository und arbeite in einem Branch.
  4. Öffne einen Pull Request, der die Issue-Nummer nennt.

Rechercherichtung

Beginne mit auto3dseg/notebooks/hpo_optuna.ipynb und reproduziere dessen Notebook-Prüfung, wobei du dich auf die im Bericht gezeigten papermill- und TensorFlow-Warnungen konzentrierst. Verfolge, welche Warnungen vom Notebook-Lauf und nicht von der Umgebung stammen, und verifiziere anschließend, dass die Notebook-Prüfung ohne die gemeldeten Warnmeldungen abgeschlossen wird.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
jupyter-notebook, python, pytorch, tensorflow
Bereich
machine-learning, testing-qa
Issue-Typ
Bug
Schwierigkeit
3/5
Geschätzter Aufwand
1-2 Tage
Aktivitätsstatus
Veraltet
Klarheit
Muss geklärt werden
Anfängerfreundlichkeit
30/100

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.