Introduce Named Data Classes for mlos_core #811
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bpkroth
reviewed
Jul 31, 2024
bpkroth
reviewed
Jul 31, 2024
| elif left is not None and right is not None: | ||
| if not left.equals(right): | ||
| return False | ||
| return True |
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I think this can be simplified a bit:
if left is not None and right is not None and left.equals(right):
return True
return False
bpkroth
reviewed
Jul 31, 2024
bpkroth
reviewed
Sep 18, 2024
| def __repr__(self) -> str: | ||
| return ( | ||
| f"Observation(config={self.config}, score={self.score}," | ||
| + " context={self.context}, metadata={self.metadata})" |
bpkroth
reviewed
Sep 18, 2024
| scores: pd.DataFrame, | ||
| context: Optional[pd.DataFrame] = None, | ||
| metadata: Optional[pd.DataFrame] = None, | ||
| observation: Observation, |
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Suggested change
| observation: Observation, | |
| observations: Observations, |
bpkroth
reviewed
Sep 18, 2024
| @@ -150,7 +134,7 @@ def suggest( | |||
| *, | |||
| context: Optional[pd.DataFrame] = None, | |||
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Suggested change
| context: Optional[pd.DataFrame] = None, | |
| context: Optional[pd.Series] = None, |
Did this one get replacd by a Series elsewhere?
bpkroth
reviewed
Sep 18, 2024
| """ | ||
| pass # pylint: disable=unnecessary-pass # pragma: no cover | ||
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| def get_observations(self) -> Tuple[pd.DataFrame, pd.DataFrame, Optional[pd.DataFrame]]: | ||
| def get_observations(self) -> Observation: |
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Suggested change
| def get_observations(self) -> Observation: | |
| def get_observations(self) -> Observations: |
docstring needs updating too
bpkroth
reviewed
Sep 18, 2024
| ).reset_index(drop=True) | ||
| return (configs, scores, contexts if len(contexts.columns) > 0 else None) | ||
| return Observation( |
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Suggested change
| return Observation( | |
| return Observations( |
bpkroth
reviewed
Sep 18, 2024
| return Observation( | ||
| config=configs, | ||
| score=scores, | ||
| context=contexts if len(contexts.columns) > 0 else None, |
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Suggested change
| context=contexts if len(contexts.columns) > 0 else None, | |
| context=contexts if len(contexts) > 0 else None, |
?
bpkroth
reviewed
Sep 18, 2024
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| def get_best_observations( | ||
| self, | ||
| *, | ||
| n_max: int = 1, | ||
| ) -> Tuple[pd.DataFrame, pd.DataFrame, Optional[pd.DataFrame]]: | ||
| ) -> Observation: |
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Suggested change
| ) -> Observation: | |
| ) -> Observations: |
bpkroth
reviewed
Sep 18, 2024
| return (configs.loc[idx], scores.loc[idx], None if contexts is None else contexts.loc[idx]) | ||
| observations = self.get_observations() | ||
| idx = observations.score.nsmallest( | ||
| n_max, columns=self._optimization_targets, keep="first" |
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Suggested change
| n_max, columns=self._optimization_targets, keep="first" | |
| n_max, columns=self._optimization_targets, keep="first", |
trailing comma, format fixups
bpkroth
reviewed
Sep 20, 2024
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| def compare_optional_dataframe( | ||
| left: Optional[pd.DataFrame], right: Optional[pd.DataFrame] |
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Suggested change
| left: Optional[pd.DataFrame], right: Optional[pd.DataFrame] | |
| left: Optional[pd.DataFrame], right: Optional[pd.DataFrame], |
nit: trailing comma and black reformat
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Got confused and started commenting here again. I think #852 supercedes this one, so let's close this one. |
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Introduces
@dataclasstypes for return values from mlos_core.Optimizers to improve code readability.See also: #751