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Do we have somewhere test which check that loaded fitted model make the same forecast?
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self.__dict__.update(local_state) | ||
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if is_fitted: |
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May be we can move model creation logic to _create_model
method, i.e. add optional parameter state
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I don't really think that it is a good idea. Now _create_model
doesn't know anything about serialization. Just handles creation of model using hyperparameters and processing additional_seasonalities
(I added this method mostly because of them).
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self.regressor_columns: Optional[List[str]] = None | ||
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def _create_model(self) -> "Prophet": |
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Add description to the method
tests/test_models/test_prophet.py
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def test_setstate_not_fitted(): | ||
model_1 = _ProphetAdapter() |
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May be leave here only one model for simplicity:
initial_state = model.__getstate__()
new_state = model.__setstate__(model.__getstate__()).__getstate_()
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This test and my variation of this test can work even if __setstate__
does nothing. I fixed it.
Isn't |
# Conflicts: # CHANGELOG.md
Before submitting (must do checklist)
Proposed Changes
Look #1016.
Closing issues
Closes #1016.