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Currently, neat.Checkpointer.restore_checkpoint loads the checkpoint, along with the configuration used at the time. Would love to be able to load a checkpoint using an updated configuration file, to allow tweaking of factors such as fitness_threshold.
The text was updated successfully, but these errors were encountered:
I'd looked into this last year. The following allows a new config to be
defined when restoring a checkpoint. I've only briefly tested the change.
It did appear to 'work', however, I'm unsure which new values take effect
or if there are any adverse effects. I'd be keen to know how you go with
it.
https://github.com/luke-saunders/neat-python/tree/CheckpointNewConfig
*neat/checkpoint.py*
def restore_checkpoint(filename, update_config=None):
"""Resumes the simulation from a previous saved point"""
with gzip.open(filename) as f:
generation, config, population, species_set, rndstate =
pickle.load(f)
random.setstate(rndstate)
if update_config==None:
return Population(config, (population, species_set,
generation))
else:
return Population(update_config, (population, species_set,
generation))
On Sat, 15 Apr 2023 at 14:05, Michal A Uchmanowicz ***@***.***> wrote:
I support this. I dont know how that would work or if its possible as I am
a new user, but I think it could see some cool benefits.
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Currently,
neat.Checkpointer.restore_checkpoint
loads the checkpoint, along with the configuration used at the time. Would love to be able to load a checkpoint using an updated configuration file, to allow tweaking of factors such asfitness_threshold
.The text was updated successfully, but these errors were encountered: