Cast learning_rate to float lambda for pickle safety when doing model.load #1901
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…ssed a function with non-float types
araffin
reviewed
Apr 19, 2024
stable_baselines3/common/utils.py
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| @@ -92,7 +92,7 @@ def get_schedule_fn(value_schedule: Union[Schedule, float]) -> Schedule: | |||
| value_schedule = constant_fn(float(value_schedule)) | |||
| else: | |||
| assert callable(value_schedule) | |||
| return value_schedule | |||
| return lambda _: float(value_schedule(_)) | |||
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maybe a better solution is to do a call to value_schedule(1.0) and check that the return type is a float (and output a useful error message if not).
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or, what you do is fine but I would explicitly name the parameter progress_remaining and add a comment of why
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Hm... I see the value in both. Let me noodle a bit and I'll see if I can sort it out during my lunch. Thanks araffin!
|
Awesome! Thanks again araffin! The docs on SB3 you and the crew wrote and your guidance made this a breeze :) |
friedeggs
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Jul 22, 2024
….load (DLR-RM#1901) * create failing test for unpickle error * Fix learning_rate argument causing failure in weights_only=True if passed a function with non-float types * Updated with feedback from araffin on PR#1901 * Update test and version * Update changelog and SBX doc --------- Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
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Description
closes #1900
Motivation and Context
closes [Bug]: if learning_rate function uses special types, they can cause torch.load to fail when weights_only=True #1900
Types of changes
Checklist
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