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We should consider having consistent behavior across all endpoints (always raise on a "failed" status) or decide if it makes sense to not throw exceptions specifically for training operations.
We don't raise on a "failed" status for training and instead return the model with errors. There are two errors lists on a model: top-level model errors and per-training document errors. If we do throw an exception here we need to figure out what should be raised.
Architect guidance
Throw exception if training method returns model with "invalid" status
Exception message should include model_id, along with message from service that explains why it failed
Include in documentation that a model is still created even if the training operation fails
The text was updated successfully, but these errors were encountered:
This is done. Training now throw an error on invalid status, with error messages including information about the details of what documents have errors.
See: Azure/azure-sdk-for-net#11473 and Azure/azure-sdk-for-python#11323
We should consider having consistent behavior across all endpoints (always raise on a "failed" status) or decide if it makes sense to not throw exceptions specifically for training operations.
We don't raise on a "failed" status for training and instead return the model with errors. There are two errors lists on a model: top-level model errors and per-training document errors. If we do throw an exception here we need to figure out what should be raised.
Architect guidance
Throw exception if training method returns model with "invalid" status
Exception message should include model_id, along with message from service that explains why it failed
Include in documentation that a model is still created even if the training operation fails
The text was updated successfully, but these errors were encountered: