Greg Whittier03/22/2023, 3:26 PM
sandy03/22/2023, 9:47 PM
Would one approach be to specify a partition name (i.e., a run name) and set of hyperparameters in the run config (edited in launchpad) or is this an abuse of config? Being able to manually iterate in dagit would be very useful.Yes - exactly. This isn't an abuse of config. In the future, we'd like to find a way to allow these to be more tightly coupled. I.e. if you later want to re-run that experiment, ideally you'd maybe be able to just launch a materialization of that partition without needing to specify that config again? Curious if you have thoughts on the ideal workflow here.
How is it anticipated the hyperparameters would be later queried (for instance if one were making a graph of accuracy versus some parameter)? Would I populate my own database within the asset op (or use something like Mlflow) or is it anticipated dagster's facilities provide something natively. I.e., can I use dagster database somehow.The interface for this isn't particularly nice right now, but all this data can be recovered from the Dagster database using the Python APIs. You'd need to do the following: • Fetch a list of all the partitions (
• For each partition, find the latest materialization (
• On each of those materializations, use the run ID to find the run config (
Would you ideally basically want to be able to see this visualized in the UI? Or do you imagine you're more likely to want to have a custom visualization in an internal tool / notebook?
Greg Whittier03/23/2023, 3:10 PM