solve issue #542. fix pickle.UnpickingError while blendsearch warm start #554
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…h warm start Issue I encountered: microsoft#542 run test_restore.py and got _pickle.UnpicklingError: state is not a dictionary I observed: 1. numpy version i. When numpy==1.16*, np.random.RandomState.__getstate__() returns a tuple, not a dict. _pickle.UnpicklingError occurs ii. When numpy>1.17.0rc1, it returns a dict; _pickle.UnpicklingError does not occur iii. When numpy>1.17.0rc1, flaml uses np_random_generator = np.random.Generator, _pickle.UnpicklingError does not occur 2. class _BackwardsCompatibleNumpyRng When I remove func _BackwardsCompatibleNumpyRng.__getattr__() , _pickle.UnpicklingError doesn't occur (regardless of numpy version == 1.16* or 1.17*) To sum up, I think making modifications to class _BackwardsCompatibleNumpyRng is not a good choice (_BackwardsCompatibleNumpyRng came from ray）and we still need to learn more about the operation mechanism of pickle. So I upgraded the numpy version that flaml requires： setup.py："NumPy>=1.17.0rc1"
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There is a stack overflow error on the window 2019 python3.8 test pipeline. I guess rerun the pipeline might fix the problem. |
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Requesting review from @skzhang1 @MichalChromcak for the version update in conda package. |
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I run test_restore.py. It runs well if upgrade numpy version. It seems no problem to me. |
skzhang1
approved these changes
May 22, 2022
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Issue I encountered:
#542 run test_restore.py and got _pickle.UnpicklingError: state is not a dictionary
I observed:
numpy version
i. When numpy==1.16*, np.random.RandomState.getstate() returns a tuple, not a dict.
_pickle.UnpicklingError occurs
ii. When numpy>1.17.0rc1, it returns a dict;
_pickle.UnpicklingError does not occur
iii. When numpy>1.17.0rc1, flaml uses np_random_generator = np.random.Generator,
_pickle.UnpicklingError does not occur
class _BackwardsCompatibleNumpyRng
When I remove func _BackwardsCompatibleNumpyRng.getattr() , _pickle.UnpicklingError doesn't occur (regardless of numpy version == 1.16* or 1.17*)
To sum up,
I think making modifications to class _BackwardsCompatibleNumpyRng is not a good choice (_BackwardsCompatibleNumpyRng came from ray）and we still need to learn more about the operation mechanism of pickle.
So I upgraded the numpy version that flaml requires：
setup.py："NumPy>=1.17.0rc1"