Open zacps opened 3 years ago
@zacps I'd be interested in picking this up. Could you provide some more details maybe?
Are we looking at some logger method that a user can use (kind of like print()
)?
def my_code():
memento.logger.log("starting experiment")
# Other stuff
memento.logger.log(f"got a result: {result}")
More like a store for time-series values. For example if you wanted to record the loss of a model during training.
Really all this has to be is a thin wrapper around pandas. Primarily we should take care of:
As a convenience utility we should provide the ability for users to log numeric metrics during their experiment.
These metrics should be cached along with other results.
By narrowing what metrics we support we can automatically provide aggregation (median, mean, stderr, ...) calculations and potentially provide (live?) automatic plots (via matplotlib/seaborn?).