paper preperations and notebooks, optuna callbacks

models/cnn_baseline.py

@@ -3,8 +3,6 @@ from argparse import Namespace
 
 from torch import nn
 
-from ml_lib.metrics.binary_class_classifictaion import BinaryScores
-from ml_lib.metrics.multi_class_classification import MultiClassScores
 from ml_lib.modules.blocks import LinearModule
 from ml_lib.modules.model_parts import CNNEncoder
 from ml_lib.modules.util import (LightningBaseModule)
@@ -52,9 +50,3 @@ class CNNBaseline(CombinedModelMixins,
 
         tensor = self.classifier(tensor)
         return Namespace(main_out=tensor)
-
-    def additional_scores(self, outputs):
-        if self.params.n_classes > 2:
-            return MultiClassScores(self)(outputs)
-        else:
-            return BinaryScores(self)(outputs)