Hi TenseOstrich47
You can check the new clearml-serving , and the new python interfaces added to the "Model" class.
https://github.com/allegroai/clearml/blob/22d795f68f0175ba9511cabd444ea4dba464f3cd/clearml/model.py#L444
In particular, I am trying to find a neat way to query all models available, and use tags to know the context. As it stands, I log the model accuracies/RMEs as part of the metadata, alongside the training data filepath. Issue is that this is not the neatest way of querying models across tasks without a lot of laborious manual lifting. Suggestions welcome
While we're here, how can I return the model accuracy (or any performance metric for that matter) given a model(s) belonging to a particular task? Is this information stored anywhere or do I need to explicitly log this data somehow?
Is this information stored anywhere or do I need to explicitly log this data somehow?
On the creating Task along side all the other reports.
Basically each model stores its creating Task (Task ID), using the Task ID you can query all the metrics reported by the task