Bump numpy >= 1.20 to avoid MKL error in conda env, and add --upgrade for pip install app sdk #211
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…all monai-deploy-app-sdk Signed-off-by: mmelqin <mingmelvinq@nvidia.com>
gigony
approved these changes
Nov 26, 2021
Merged
MMelQin
deleted the
mqin/update_numpy_version_to_avoid_conda_MKL_issue
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It was found out that when running Jupyter-lab within a environment set up using conda, pytorch encountered error related to MKL, see pytorch issue.
A previous PR modified the Jupyter notebook adding env var ['MKL_THREADING_LAYER'] = 'GNU' to work around the MKL issue, which is one of the suggested fixes.
A cleaner fix, as also stated in the said issue, is to upgrade to numpy 1.20 to avoid the MKL issue without needing the env var workaround.
The example segmentation examples had already been tested with numpy >= 1.20, so it is the safe and correct fix to bump the numpy version >= 1.20, in the apps, as well as in the Jupyter notebooks that copied the app code.
Also added
--upgradeoption for pip install monai-deploy-app-sdk, in case the env had an earlier version of the sdk installed.