New Dataset superclass #89
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matsen
approved these changes
Nov 22, 2024
matsen
requested changes
Nov 24, 2024
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I appreciate what you're doing here, but there's something that doesn't quite make sense.
The ModelBase covers all sorts of models, e.g. SHM models, so it doesn't make sense for it to have a method selection_factors_of_sequences. We could call it something generic like evaluate_sequences, as long as all the components will make sense for SHM models and DXSM models.
netam/models.py
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| def selection_factors_of_sequences(self, sequences, encoder=None): | ||
| if encoder is None: | ||
| raise ValueError("An encoder must be provided.") | ||
| device = next(self.parameters()).device |
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Let's make this a @property .
|
I've changed |
matsen
approved these changes
Nov 26, 2024
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Addressing #55, I consolidating some branch lengths-related code into a new superclass
BranchLengthDataset. I can't seem to find any other duplicated code.The only opportunity for more code reuse would be to abstract methods like
tothat map over all attributes of the class and apply some function. This could be done inBranchLengthDatasetusing thevarsbuiltin, but I think it might be more trouble than it's worth.Will close #55