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rhayes777
approved these changes
Mar 25, 2024
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| from autogalaxy.analysis.adapt_images.adapt_images import AdaptImages | ||
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| class AdaptImageMaker: |
Collaborator
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There's a not a huge amount of point in this class given that you could simply call:
result.adapt_images_from(
use_model_images=self.use_model_images
)
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| if isinstance(paths, af.DatabasePaths): | ||
| return |
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Why the exception here? Might be cleaner to put this outside the function
| settings typically control the overall run-time. | ||
| """ | ||
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| if paths is None: |
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| @property | ||
| def preloads_cls(self): | ||
| return Preloads | ||
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| @property | ||
| def fit_maker_cls(self): | ||
| return FitMaker |
Collaborator
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You can also do this by setting class level attributes.
class AnalysisDataset(Analysis):
Preloads = Preloads
FitMaker = FitMaker
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Author
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Going to do this in a moment when I do it for the Result casting.
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| os.makedirs(paths.profile_path, exist_ok=True) | ||
| self.preloads.output_info_to_summary(file_path=paths.profile_path) |
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Handle directory creation right before the data is output (e.g. in the output_info_to_summary method)
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Recent updates changed it so that the
AdaptImageswere computed and passed to anAnalysisobject during search chaining pipelines.However, this meant resuming already completed pipelines is slow, because the adapt images would be computed for each fit even though for fits that are already completed the adapt images are not used.
This PR instead uses an
AdaptImageMakerobject, which computes theAdaptImageswhen they are used and then caches them. This means pipelines can be resumed much faster again.