Closed avagraw closed 2 years ago
Testing evidence with multiple ontologies: https://dev.azure.com/azureiotdevxp/aziotcli/_build/results?buildId=5914&view=logs&s=859b8d9a-8fd6-5a5c-6f5e-f84f1990894e
More evidence - Tests process 3 ontologies: https://dev.azure.com/azureiotdevxp/aziotcli/_build/results?buildId=5922&view=logs&j=e24f7e52-36f4-54e9-a8eb-6f10b62b4c84&t=85779272-bb12-5d7f-5c2e-f38ba3ce51f9
We should add a HISTORY.rst entry, and refresh the help to describe the improvements to this command. Users should be aware they can simply clone an ontology repository and upload all models in a single command -- and behavior if there is a failure during the process.
It would be nice to improve this section in the contributing docs https://github.com/Azure/azure-iot-cli-extension/blob/dev/CONTRIBUTING.md#required-repositories to specifically to state clone commands including optionally fetching submodules to enable more tests.
Has there been thought on including an enum based --failure-policy
param that includes rollback
or none
options so the user can prevent the model deletion rollback behavior if desired?
Has there been thought on including an enum based
--failure-policy
param that includesrollback
ornone
options so the user can prevent the model deletion rollback behavior if desired?
Created a task for this: https://msazure.visualstudio.com/One/_sprints/taskboard/IoT-Platform-UPX/One/Custom/IoT/2207?workitem=14902067
The model creation command (az dt model create) currently only supports input ontologies consisting of 250 models or lesser (This limit is enforced by the underlying API). This code change allows users to pass in ontologies of size constrained only by max number of models which can be stored on the ADT instance (default is 10,000 models). The logic takes care of figuring out the dependencies and creating batches (smaller or equal to the API limit) . Each batch is then processed by a separate API call. The batching logic ensures that the dependency of each model being processed is in the same batch or has already been created on the DT instance as a part of a previous batch.
TQDM integration allows users to monitor progress.
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