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Closes #726
This includes changes to how we handle primary and secondary dependencies in the InnerEye Deep Learning library. Locking is now performed through the use of
conda export
, preventing secondary versions from switching unexpectedly. Through the use of a bash script the env is locked and anenvironment.yml
suitable for ingestion by AzureML is constructed.This is far from a perfect solution, but at the very least significantly reduces the chance of pipelines failing due to secondary dependency version changes.