Closed marcosfelt closed 1 year ago
Hey @marcosfelt,
I've started working on this issue. It seems like the ExperimentalEmulator
is not retraining the model during initialization. However, it might be getting retrained unnecessarily in other parts of the code where it's being used. I'm going to check the usage of ExperimentalEmulator
in the tests and experiments to ensure it's not being retrained unnecessarily.
Give me a minute!
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Hey @marcosfelt,
I've started working on this issue. The plan is to modify the train
method in the ExperimentalEmulator
class to check if the model has already been trained. If it has, we'll skip the training process. This should prevent the emulator from being retrained on reinitialization.
Give me a minute!
I'm a bot that handles simple bugs and feature requests but I might make mistakes. Please be kind!
ExperimentalEmulator should not be retrained on reinitialization (see
summit/benchmarks/experimental_emulator.py
). See:https://github.com/sustainable-processes/summit/blob/8b987dee789eeb6e7e87184e935425330e2501f5/summit/benchmarks/experimental_emulator.py#L308-L317