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WIP: Refactoring #59
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WIP: Refactoring #59
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for metadata
and preprocessing - no direct tensor support in dataset - preprocessing: replace directory by images - transforms.ToTensor
sort listdir to reproduce dataset filenames
+ use torchvision.transforms.v2 + add dataloaders processing, images, thumbnail_images + test jit.script
GalaxyZooDataModule
- split member function using Mixin (https://www.qtrac.eu/pyclassmulti.html) - set default number of workers to all threads
remove mixin class design
hipster verbosity print level thumbnail images
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Comprehensive refactoring of the data modules and the HiPSter in preparation for the applicability of different data structures.
Derived class DatasetWithMetadata to provide metadata
The dataset classes return the pure data tensor for training. The derived classes DatasetWithMetadata return a tuple of data and metadata, which is currently only needed for the HiPSter. This ensures that the access also works for shuffled dataloaders.
Move data structure-dependent functionality from HiPster into DataModule
Move
write_catalog
,create_images
andcreate_thumbnails
from HiPster into DataModuleRotation invariant
The best rotation search function
find_best_rotation
is moved to the base classSpherinatorModule
to avoid duplicated code for training and HiPSter. (here)Bugfix: No variational sampling in rotational invariance
The variational sampling should be disabled in searching for the best rotation (
encode
instead offorward
).Base classes
SpherinatorDataset
andSpherinatorDataModule
Abstract base classes for dataset and DataModules to ensure that all methods for HiPSter are implemented.
Miscellaneous
images
andthumbnails
andallsky
to HiPSter as a tasktorchvision.transforms.v2
Why?