What can I do to reduce the number of MLflow API calls I make?
I'm fitting multiple models in parallel. For each one, I'm logging lots of params and metrics to MLflow. I'm hitting rate limits, causing problems in my jobs.
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The first thing to try is to log in batches. If you are logging each param and metric separately, you're making 1 API call per param and 1 per metric. Instead, you should use the batch logging APIs; e.g. use "log_params" instead of "log_param" http...
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