bug in folds; time-efficient voting strategy; variable number of channels and prototypes - #11
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bug in folds; time-efficient voting strategy; variable number of channels and prototypes#11jgciudad wants to merge 7 commits into
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jgciudad
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August 20, 2025 17:46
…hannels and prototypes in prototype model
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Feb 11, 2026
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When no specific fold is specified (fold=-1), a fold is sampled when the training dataset is created, and again when eval_dataset is created, leading to different folds in each.
I’ve changed the default fold to fold 0 when no fold is specified. I’ve done this everywhere in the code and removed random fold selection.
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| except : | ||
| devices = "auto" | ||
| effective_batch_size = batch_size * num_nodes | ||
| num_steps = datamodule.__len__() // effective_batch_size |
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effective_batch_size was not defined. not sure if the block just before was removed by mistake, or if effective_batch_size should just be changed to batch_size
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