New directory is not created while using flag --no-train · microsoft/InnerEye-DeepLearning#844

2023-05-22T07:56:12.000Z

### Is there an existing issue for this? - [X] I have searched the existing issues ### Bug summary While using flag --no-train there is an error that path does not exist. I tried also using local_weights_path, but still the same error. ### Code for reproduction ```Python CUDA_VISIBLE_DEVICES=5 python InnerEye/ML/runner.py --model=DynamicUnetBones --no-train --local_weights_path=outputs/2023-05-19T071816Z_DynamicUnetBones/checkpoints/last.ckpt ``` ### Actual outcome Traceback (most recent call last): File "InnerEye/ML/runner.py", line 467, in main() File "InnerEye/ML/runner.py", line 461, in main run(project_root=fixed_paths.repository_root_directory(), File "InnerEye/ML/runner.py", line 457, in run return runner.run() File "InnerEye/ML/runner.py", line 220, in run self.run_in_situ(azure_run_info) File "InnerEye/ML/runner.py", line 412, in run_in_situ self.ml_runner.run() File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/ML/run_ml.py", line 378, in run self.run_inference_for_lightning_models(checkpoint_paths_for_testing) File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/ML/run_ml.py", line 469, in run_inference_for_lightning_models with change_working_directory(self.container.outputs_folder): File "/home/.conda/envs/InnerEye3/lib/python3.8/contextlib.py", line 113, in __enter__ return next(self.gen) File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/Common/common_util.py", line 436, in change_working_directory os.chdir(new_path) FileNotFoundError: [Errno 2] No such file or directory: '/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/outputs/2023-05-22T073814Z_DynamicUnetBones' ### Error messages ```python-traceback FileNotFoundError: [Errno 2] No such file or directory: '/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/outputs/2023-05-22T073814Z_DynamicUnetBones' ``` ### Expected outcome It should run predictions on test data and save the result either on the local_weights_path directory or the new path (doesn't matter for me) ### System info OS: NAME="Ubuntu" VERSION="18.04.5 LTS (Bionic Beaver)" ID=ubuntu ID_LIKE=debian PRETTY_NAME="Ubuntu 18.04.5 LTS" VERSION_ID="18.04" HOME_URL="https://www.ubuntu.com/" SUPPORT_URL="https://help.ubuntu.com/" BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/" PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy" VERSION_CODENAME=bionic UBUNTU_CODENAME=bionic INNEREYE COMMIT HASH: commit 2877002d50d3a34d80f647c18cb561025d9066cc (HEAD -> main, origin/main, origin/HEAD) CONDA ENV: name: InnerEye3 channels: - pytorch - defaults dependencies: - _libgcc_mutex=0.1=main - _openmp_mutex=5.1=1_gnu - blas=1.0=mkl - blosc=1.21.0=h4ff587b_1 - bzip2=1.0.8=h7b6447c_0 - ca-certificates=2022.07.19=h06a4308_0 - certifi=2022.9.24=py38h06a4308_0 - cudatoolkit=11.3.1=h2bc3f7f_2 - ffmpeg=4.2.2=h20bf706_0 - freetype=2.11.0=h70c0345_0 - giflib=5.2.1=h7b6447c_0 - gmp=6.2.1=h295c915_3 - gnutls=3.6.15=he1e5248_0 - intel-openmp=2021.4.0=h06a4308_3561 - jpeg=9e=h7f8727e_0 - lame=3.100=h7b6447c_0 - lcms2=2.12=h3be6417_0 - ld_impl_linux-64=2.38=h1181459_1 - lerc=3.0=h295c915_0 - libdeflate=1.8=h7f8727e_5 - libffi=3.3=he6710b0_2 - libgcc-ng=11.2.0=h1234567_1 - libgomp=11.2.0=h1234567_1 - libidn2=2.3.2=h7f8727e_0 - libopus=1.3.1=h7b6447c_0 - libpng=1.6.37=hbc83047_0 - libstdcxx-ng=11.2.0=h1234567_1 - libtasn1=4.16.0=h27cfd23_0 - libtiff=4.4.0=hecacb30_0 - libunistring=0.9.10=h27cfd23_0 - libuv=1.40.0=h7b6447c_0 - libvpx=1.7.0=h439df22_0 - libwebp=1.2.4=h11a3e52_0 - libwebp-base=1.2.4=h5eee18b_0 - lz4-c=1.9.3=h295c915_1 - mkl=2021.4.0=h06a4308_640 - mkl-service=2.4.0=py38h7f8727e_0 - mkl_fft=1.3.1=py38hd3c417c_0 - mkl_random=1.2.2=py38h51133e4_0 - ncurses=6.3=h5eee18b_3 - nettle=3.7.3=hbbd107a_1 - openh264=2.1.1=h4ff587b_0 - openssl=1.1.1q=h7f8727e_0 - pip=20.1.1=py38_1 - python=3.8.3=hcff3b4d_2 - python-blosc=1.7.0=py38h7b6447c_0 - pytorch=1.10.0=py3.8_cuda11.3_cudnn8.2.0_0 - pytorch-mutex=1.0=cuda - readline=8.1.2=h7f8727e_1 - setuptools=63.4.1=py38h06a4308_0 - sqlite=3.39.3=h5082296_0 - tk=8.6.12=h1ccaba5_0 - torchvision=0.11.1=py38_cu113 - typing_extensions=4.3.0=py38h06a4308_0 - wheel=0.37.1=pyhd3eb1b0_0 - x264=1!157.20191217=h7b6447c_0 - xz=5.2.6=h5eee18b_0 - zlib=1.2.12=h5eee18b_3 - zstd=1.5.2=ha4553b6_0 - pip: - absl-py==1.2.0 - adal==1.2.7 - aiofiles==23.1.0 - aiohttp==3.8.3 - aiosignal==1.2.0 - alabaster==0.7.12 - alembic==1.8.1 - ansiwrap==0.8.4 - applicationinsights==0.11.10 - argon2-cffi==21.3.0 - argon2-cffi-bindings==21.2.0 - argparse==1.4.0 - async-timeout==4.0.2 - attrs==22.1.0 - azure-common==1.1.28 - azure-core==1.26.0 - azure-graphrbac==0.61.1 - azure-identity==1.7.0 - azure-mgmt-authorization==0.61.0 - azure-mgmt-containerregistry==10.0.0 - azure-mgmt-core==1.3.2 - azure-mgmt-datafactory==1.1.0 - azure-mgmt-keyvault==9.3.0 - azure-mgmt-resource==12.1.0 - azure-mgmt-storage==11.2.0 - azure-storage-blob==12.6.0 - azureml-automl-core==1.36.1 - azureml-core==1.36.0.post2 - azureml-dataprep==2.24.4 - azureml-dataprep-native==38.0.0 - azureml-dataprep-rslex==2.0.3 - azureml-dataset-runtime==1.36.0 - azureml-mlflow==1.36.0 - azureml-pipeline==1.36.0 - azureml-pipeline-core==1.36.0 - azureml-pipeline-steps==1.36.0 - azureml-sdk==1.36.0 - azureml-telemetry==1.36.0 - azureml-tensorboard==1.36.0 - azureml-train-automl-client==1.36.0 - azureml-train-core==1.36.0 - azureml-train-restclients-hyperdrive==1.36.0 - babel==2.10.3 - backcall==0.2.0 - backports-tempfile==1.0 - backports-weakref==1.0.post1 - batchgenerators==0.25 - beautifulsoup4==4.11.1 - black==22.10.0 - bleach==5.0.1 - cachetools==4.2.4 - cffi==1.15.1 - charset-normalizer==2.1.1 - click==8.1.3 - cloudpickle==1.6.0 - colorama==0.4.5 - commonmark==0.9.1 - conda-merge==0.1.5 - contextlib2==21.6.0 - coverage==6.5.0 - cryptography==3.3.2 - cycler==0.11.0 - databricks-cli==0.17.3 - dataclasses-json==0.5.2 - debugpy==1.6.3 - decorator==5.1.1 - defusedxml==0.7.1 - deprecated==1.2.13 - dicom2nifti==2.4.8 - dill==0.3.6 - distro==1.8.0 - docker==4.3.1 - docutils==0.18.1 - dotnetcore2==2.1.23 - entrypoints==0.4 - execnet==1.9.0 - fastjsonschema==2.16.2 - fastmri==0.2.0 - flake8==3.8.3 - flask==2.2.2 - frozenlist==1.3.1 - fsspec==2022.8.2 - furo==2022.6.21 - fusepy==3.0.1 - future==0.18.3 - gitdb==4.0.9 - gitpython==3.1.7 - google-auth==1.35.0 - google-auth-oauthlib==0.4.6 - gputil==1.4.0 - greenlet==1.1.3.post0 - grpcio==1.49.1 - gunicorn==20.1.0 - h5py==2.10.0 - hi-ml==0.2.5 - hi-ml-azure==0.2.5 - humanize==4.4.0 - idna==3.4 - imageio==2.15.0 - imagesize==1.4.1 - importlib-metadata==5.0.0 - importlib-resources==5.10.0 - iniconfig==1.1.1 - innereye-dicom-rt==1.1.0 - ipykernel==6.16.0 - ipython==7.31.1 - ipython-genutils==0.2.0 - ipywidgets==8.0.2 - isodate==0.6.1 - itsdangerous==2.1.2 - jedi==0.18.2 - jeepney==0.8.0 - jinja2==3.0.2 - jmespath==0.10.0 - joblib==0.16.0 - jsonpickle==2.2.0 - jsonschema==4.16.0 - jupyter==1.0.0 - jupyter-client==6.1.5 - jupyter-console==6.4.4 - jupyter-core==4.11.1 - jupyterlab-pygments==0.2.2 - jupyterlab-widgets==3.0.3 - kiwisolver==1.4.4 - lightning-bolts==0.4.0 - linecache2==1.0.0 - llvmlite==0.34.0 - mako==1.2.3 - markdown==3.4.1 - markdown-it-py==2.1.0 - markupsafe==2.1.1 - marshmallow==3.18.0 - marshmallow-enum==1.5.1 - matplotlib==3.3.0 - matplotlib-inline==0.1.6 - mccabe==0.6.1 - mdit-py-plugins==0.3.1 - mdurl==0.1.2 - medpy==0.4.0 - mistune==2.0.4 - mlflow==1.23.1 - mlflow-skinny==1.29.0 - monai==0.6.0 - more-itertools==8.14.0 - msal==1.20.0 - msal-extensions==0.3.1 - msrest==0.7.1 - msrestazure==0.6.4 - multidict==6.0.2 - mypy==0.910 - mypy-extensions==0.4.3 - myst-parser==0.18.0 - nbclient==0.7.0 - nbconvert==7.2.1 - nbformat==5.7.0 - ndg-httpsclient==0.5.1 - nest-asyncio==1.5.6 - networkx==2.8.7 - nibabel==4.0.2 - nnunet==1.7.0 - notebook==6.4.12 - numba==0.51.2 - numpy==1.19.1 - oauthlib==3.2.1 - opencv-python-headless==4.5.1.48 - packaging==21.3 - pandas==1.1.0 - pandocfilters==1.5.0 - papermill==2.2.2 - param==1.9.3 - parso==0.8.3 - pathspec==0.10.1 - pathtools==0.1.2 - pexpect==4.8.0 - pickleshare==0.7.5 - pillow==9.1.1 - pkgutil-resolve-name==1.3.10 - platformdirs==2.5.2 - pluggy==0.13.1 - portalocker==2.5.1 - prometheus-client==0.14.1 - prometheus-flask-exporter==0.20.3 - prompt-toolkit==3.0.38 - protobuf==3.20.1 - psutil==5.7.2 - ptyprocess==0.7.0 - py==1.11.0 - pyarrow==3.0.0 - pyasn1==0.4.8 - pyasn1-modules==0.2.8 - pycodestyle==2.6.0 - pycparser==2.21 - pydeprecate==0.3.2 - pydicom==2.0.0 - pyflakes==2.2.0 - pygments==2.15.1 - pyjwt==2.4.0 - pynndescent==0.5.7 - pyopenssl==20.0.1 - pyparsing==3.0.9 - pyrsistent==0.18.1 - pysocks==1.7.1 - pytest==6.0.1 - pytest-cov==2.10.1 - pytest-forked==1.3.0 - pytest-xdist==1.34.0 - python-dateutil==2.8.2 - python-gdcm==3.0.22 - pytorch-lightning==1.6.5 - pytz==2022.4 - pywavelets==1.4.1 - pyyaml==6.0 - pyzmq==24.0.1 - qtconsole==5.3.2 - qtpy==2.2.1 - querystring-parser==1.2.4 - radio==0.1.0 - requests==2.28.1 - requests-oauthlib==1.3.1 - rich==10.13.0 - rpdb==0.1.6 - rsa==4.9 - ruamel-yaml==0.16.12 - ruamel-yaml-clib==0.2.6 - runstats==1.8.0 - scikit-image==0.17.2 - scikit-learn==0.23.2 - scipy==1.5.2 - seaborn==0.10.1 - secretstorage==3.3.3 - send2trash==1.8.0 - simpleitk==1.2.4 - six==1.15.0 - sklearn==0.0.post5 - smmap==5.0.0 - snowballstemmer==2.2.0 - soupsieve==2.3.2.post1 - sphinx==5.0.2 - sphinx-argparse==0.3.1 - sphinx-basic-ng==1.0.0b1 - sphinx-rtd-theme==1.0.0 - sphinxcontrib-applehelp==1.0.2 - sphinxcontrib-devhelp==1.0.2 - sphinxcontrib-htmlhelp==2.0.0 - sphinxcontrib-jsmath==1.0.1 - sphinxcontrib-qthelp==1.0.3 - sphinxcontrib-serializinghtml==1.1.5 - sqlalchemy==1.4.41 - sqlparse==0.4.3 - stopit==1.1.2 - stringcase==1.2.0 - tabulate==0.8.7 - tenacity==8.1.0 - tensorboard==2.3.0 - tensorboard-plugin-wit==1.8.1 - tensorboardx==2.1 - terminado==0.16.0 - textwrap3==0.9.2 - threadpoolctl==3.1.0 - tifffile==2022.10.10 - tinycss2==1.1.1 - toml==0.10.2 - tomli==2.0.1 - torchio==0.18.74 - torchmetrics==0.6.0 - tornado==6.2 - tqdm==4.64.1 - traceback2==1.4.0 - traitlets==5.9.0 - typing-inspect==0.8.0 - umap-learn==0.5.2 - unittest2==1.1.0 - urllib3==1.26.7 - wcwidth==0.2.6 - webencodings==0.5.1 - websocket-client==1.4.1 - werkzeug==2.2.2 - widgetsnbextension==4.0.3 - wrapt==1.14.1 - yacs==0.1.8 - yarl==1.8.1 - zipp==3.9.0 prefix: /home/.conda/envs/InnerEye3

(4 comments) (0 reactions) (0 assignees)Python (519 stars) (138 forks)batch import

buggood first issue

Description

Is there an existing issue for this?

I have searched the existing issues

Bug summary

While using flag --no-train there is an error that path does not exist. I tried also using local_weights_path, but still the same error.

Code for reproduction

CUDA_VISIBLE_DEVICES=5 python InnerEye/ML/runner.py --model=DynamicUnetBones --no-train --local_weights_path=outputs/2023-05-19T071816Z_DynamicUnetBones/checkpoints/last.ckpt

Actual outcome

Traceback (most recent call last): File "InnerEye/ML/runner.py", line 467, in main() File "InnerEye/ML/runner.py", line 461, in main run(project_root=fixed_paths.repository_root_directory(), File "InnerEye/ML/runner.py", line 457, in run return runner.run() File "InnerEye/ML/runner.py", line 220, in run self.run_in_situ(azure_run_info) File "InnerEye/ML/runner.py", line 412, in run_in_situ self.ml_runner.run() File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/ML/run_ml.py", line 378, in run self.run_inference_for_lightning_models(checkpoint_paths_for_testing) File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/ML/run_ml.py", line 469, in run_inference_for_lightning_models with change_working_directory(self.container.outputs_folder): File "/home/.conda/envs/InnerEye3/lib/python3.8/contextlib.py", line 113, in enter return next(self.gen) File "/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/InnerEye/Common/common_util.py", line 436, in change_working_directory os.chdir(new_path) FileNotFoundError: [Errno 2] No such file or directory: '/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/outputs/2023-05-22T073814Z_DynamicUnetBones'

Error messages

FileNotFoundError: [Errno 2] No such file or directory: '/home/medical-models-nnUnet/newer/medical-models/InnerEye-DeepLearning/outputs/2023-05-22T073814Z_DynamicUnetBones'

Expected outcome

It should run predictions on test data and save the result either on the local_weights_path directory or the new path (doesn't matter for me)

System info

OS: NAME="Ubuntu" VERSION="18.04.5 LTS (Bionic Beaver)" ID=ubuntu ID_LIKE=debian PRETTY_NAME="Ubuntu 18.04.5 LTS" VERSION_ID="18.04" HOME_URL="https://www.ubuntu.com/" SUPPORT_URL="https://help.ubuntu.com/" BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/" PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy" VERSION_CODENAME=bionic UBUNTU_CODENAME=bionic

INNEREYE COMMIT HASH: commit 2877002d50d3a34d80f647c18cb561025d9066cc (HEAD -> main, origin/main, origin/HEAD)

CONDA ENV: name: InnerEye3 channels:

pytorch
defaults dependencies:
_libgcc_mutex=0.1=main
_openmp_mutex=5.1=1_gnu
blas=1.0=mkl
blosc=1.21.0=h4ff587b_1
bzip2=1.0.8=h7b6447c_0
ca-certificates=2022.07.19=h06a4308_0
certifi=2022.9.24=py38h06a4308_0
cudatoolkit=11.3.1=h2bc3f7f_2
ffmpeg=4.2.2=h20bf706_0
freetype=2.11.0=h70c0345_0
giflib=5.2.1=h7b6447c_0
gmp=6.2.1=h295c915_3
gnutls=3.6.15=he1e5248_0
intel-openmp=2021.4.0=h06a4308_3561
jpeg=9e=h7f8727e_0
lame=3.100=h7b6447c_0
lcms2=2.12=h3be6417_0
ld_impl_linux-64=2.38=h1181459_1
lerc=3.0=h295c915_0
libdeflate=1.8=h7f8727e_5
libffi=3.3=he6710b0_2
libgcc-ng=11.2.0=h1234567_1
libgomp=11.2.0=h1234567_1
libidn2=2.3.2=h7f8727e_0
libopus=1.3.1=h7b6447c_0
libpng=1.6.37=hbc83047_0
libstdcxx-ng=11.2.0=h1234567_1
libtasn1=4.16.0=h27cfd23_0
libtiff=4.4.0=hecacb30_0
libunistring=0.9.10=h27cfd23_0
libuv=1.40.0=h7b6447c_0
libvpx=1.7.0=h439df22_0
libwebp=1.2.4=h11a3e52_0
libwebp-base=1.2.4=h5eee18b_0
lz4-c=1.9.3=h295c915_1
mkl=2021.4.0=h06a4308_640
mkl-service=2.4.0=py38h7f8727e_0
mkl_fft=1.3.1=py38hd3c417c_0
mkl_random=1.2.2=py38h51133e4_0
ncurses=6.3=h5eee18b_3
nettle=3.7.3=hbbd107a_1
openh264=2.1.1=h4ff587b_0
openssl=1.1.1q=h7f8727e_0
pip=20.1.1=py38_1
python=3.8.3=hcff3b4d_2
python-blosc=1.7.0=py38h7b6447c_0
pytorch=1.10.0=py3.8_cuda11.3_cudnn8.2.0_0
pytorch-mutex=1.0=cuda
readline=8.1.2=h7f8727e_1
setuptools=63.4.1=py38h06a4308_0
sqlite=3.39.3=h5082296_0
tk=8.6.12=h1ccaba5_0
torchvision=0.11.1=py38_cu113
typing_extensions=4.3.0=py38h06a4308_0
wheel=0.37.1=pyhd3eb1b0_0
x264=1!157.20191217=h7b6447c_0
xz=5.2.6=h5eee18b_0
zlib=1.2.12=h5eee18b_3
zstd=1.5.2=ha4553b6_0
pip:
- absl-py==1.2.0
- adal==1.2.7
- aiofiles==23.1.0
- aiohttp==3.8.3
- aiosignal==1.2.0
- alabaster==0.7.12
- alembic==1.8.1
- ansiwrap==0.8.4
- applicationinsights==0.11.10
- argon2-cffi==21.3.0
- argon2-cffi-bindings==21.2.0
- argparse==1.4.0
- async-timeout==4.0.2
- attrs==22.1.0
- azure-common==1.1.28
- azure-core==1.26.0
- azure-graphrbac==0.61.1
- azure-identity==1.7.0
- azure-mgmt-authorization==0.61.0
- azure-mgmt-containerregistry==10.0.0
- azure-mgmt-core==1.3.2
- azure-mgmt-datafactory==1.1.0
- azure-mgmt-keyvault==9.3.0
- azure-mgmt-resource==12.1.0
- azure-mgmt-storage==11.2.0
- azure-storage-blob==12.6.0
- azureml-automl-core==1.36.1
- azureml-core==1.36.0.post2
- azureml-dataprep==2.24.4
- azureml-dataprep-native==38.0.0
- azureml-dataprep-rslex==2.0.3
- azureml-dataset-runtime==1.36.0
- azureml-mlflow==1.36.0
- azureml-pipeline==1.36.0
- azureml-pipeline-core==1.36.0
- azureml-pipeline-steps==1.36.0
- azureml-sdk==1.36.0
- azureml-telemetry==1.36.0
- azureml-tensorboard==1.36.0
- azureml-train-automl-client==1.36.0
- azureml-train-core==1.36.0
- azureml-train-restclients-hyperdrive==1.36.0
- babel==2.10.3
- backcall==0.2.0
- backports-tempfile==1.0
- backports-weakref==1.0.post1
- batchgenerators==0.25
- beautifulsoup4==4.11.1
- black==22.10.0
- bleach==5.0.1
- cachetools==4.2.4
- cffi==1.15.1
- charset-normalizer==2.1.1
- click==8.1.3
- cloudpickle==1.6.0
- colorama==0.4.5
- commonmark==0.9.1
- conda-merge==0.1.5
- contextlib2==21.6.0
- coverage==6.5.0
- cryptography==3.3.2
- cycler==0.11.0
- databricks-cli==0.17.3
- dataclasses-json==0.5.2
- debugpy==1.6.3
- decorator==5.1.1
- defusedxml==0.7.1
- deprecated==1.2.13
- dicom2nifti==2.4.8
- dill==0.3.6
- distro==1.8.0
- docker==4.3.1
- docutils==0.18.1
- dotnetcore2==2.1.23
- entrypoints==0.4
- execnet==1.9.0
- fastjsonschema==2.16.2
- fastmri==0.2.0
- flake8==3.8.3
- flask==2.2.2
- frozenlist==1.3.1
- fsspec==2022.8.2
- furo==2022.6.21
- fusepy==3.0.1
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- innereye-dicom-rt==1.1.0
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- python-dateutil==2.8.2
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- threadpoolctl==3.1.0
- tifffile==2022.10.10
- tinycss2==1.1.1
- toml==0.10.2
- tomli==2.0.1
- torchio==0.18.74
- torchmetrics==0.6.0
- tornado==6.2
- tqdm==4.64.1
- traceback2==1.4.0
- traitlets==5.9.0
- typing-inspect==0.8.0
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- urllib3==1.26.7
- wcwidth==0.2.6
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- wrapt==1.14.1
- yacs==0.1.8
- yarl==1.8.1
- zipp==3.9.0 prefix: /home/.conda/envs/InnerEye3

Contributor guide

Tech stack: pythonpytorch
Domain: machine learningai
Issue type: bug
Difficulty: 3
Estimated time: 1-3 hours
Activity status: fresh
Clarity: clear
Prerequisites: PythonPyTorchmedical imaging basics
Newbie friendliness: 70
Research direction: The error occurs in `InnerEye/ML/run ml.py` at line 469 when `change working directory` is called with `self.container.outputs folder`. The fix should ensure the output directory is created if it does not exist before attempting to change into it. Look at how the `outputs folder` is set in the `container` class and add a `os.makedirs` call with `exist ok=True` in the appropriate location, such as in `run ml.py` or `common util.py`. Check existing code for similar directory creation patterns.