diff --git a/src/mednet/libs/classification/models/alexnet.py b/src/mednet/libs/classification/models/alexnet.py
index 4d88888189ed431ce497d3e3014e86ccdf980f8a..653e1cae117fc3f1909f9883f234ce7cfad29e67 100644
--- a/src/mednet/libs/classification/models/alexnet.py
+++ b/src/mednet/libs/classification/models/alexnet.py
@@ -115,7 +115,13 @@ class Alexnet(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, _):
         images = batch[0]
diff --git a/src/mednet/libs/classification/models/densenet.py b/src/mednet/libs/classification/models/densenet.py
index 82f8d99f901485a416733cc6675f616b4ac3a52a..e89ab7ba1118aca6cbccdc2c50dd3cb976293827 100644
--- a/src/mednet/libs/classification/models/densenet.py
+++ b/src/mednet/libs/classification/models/densenet.py
@@ -118,7 +118,13 @@ class Densenet(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, _):
         images = batch[0]
diff --git a/src/mednet/libs/segmentation/models/driu.py b/src/mednet/libs/segmentation/models/driu.py
index 76608301c9b2dd717cda3c6dd6996947887caf45..2f0a5cd75fc48e93652a313e967599becc974a6d 100644
--- a/src/mednet/libs/segmentation/models/driu.py
+++ b/src/mednet/libs/segmentation/models/driu.py
@@ -158,7 +158,13 @@ class DRIU(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/driu_bn.py b/src/mednet/libs/segmentation/models/driu_bn.py
index f14f911bed17f3bd889b4e21ea148c2787dbd425..c80f88a09b69290cf320b67908956afbfa2b2859 100644
--- a/src/mednet/libs/segmentation/models/driu_bn.py
+++ b/src/mednet/libs/segmentation/models/driu_bn.py
@@ -161,7 +161,13 @@ class DRIUBN(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/driu_od.py b/src/mednet/libs/segmentation/models/driu_od.py
index d810c471fdc6d567e3a63d3b0c8534c86cea1681..ad76cb0af8457830de64f2c75479bf2bb1b94833 100644
--- a/src/mednet/libs/segmentation/models/driu_od.py
+++ b/src/mednet/libs/segmentation/models/driu_od.py
@@ -143,7 +143,13 @@ class DRIUOD(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/driu_pix.py b/src/mednet/libs/segmentation/models/driu_pix.py
index a85ac3ab1753172b012b974933cd4f6abb5cac33..e65cba0d3829f3d7cf49b19080b9fc82205ce042 100644
--- a/src/mednet/libs/segmentation/models/driu_pix.py
+++ b/src/mednet/libs/segmentation/models/driu_pix.py
@@ -147,7 +147,13 @@ class DRIUPix(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/hed.py b/src/mednet/libs/segmentation/models/hed.py
index 80e4665eea454ae6c8ef269ebde913bade71081b..630695d88a1a67fa3e240dd14c3ba7190e350cbf 100644
--- a/src/mednet/libs/segmentation/models/hed.py
+++ b/src/mednet/libs/segmentation/models/hed.py
@@ -162,7 +162,13 @@ class HED(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/m2unet.py b/src/mednet/libs/segmentation/models/m2unet.py
index ccc94c2991be732d3de83bb7c923b25231329cdf..10560a8ce47478c9bf90ba81d79984a413035f09 100644
--- a/src/mednet/libs/segmentation/models/m2unet.py
+++ b/src/mednet/libs/segmentation/models/m2unet.py
@@ -210,7 +210,13 @@ class M2UNET(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]
diff --git a/src/mednet/libs/segmentation/models/unet.py b/src/mednet/libs/segmentation/models/unet.py
index 36136bcb8dfddb85d62285c3cf555776b8271cff..f1b6f2ff7e88df138ea0f3d8ba8e99f5bda48461 100644
--- a/src/mednet/libs/segmentation/models/unet.py
+++ b/src/mednet/libs/segmentation/models/unet.py
@@ -151,7 +151,13 @@ class Unet(Model):
             )
             self.normalizer = make_imagenet_normalizer()
         else:
-            super().set_normalizer(dataloader)
+            from .normalizer import make_z_normalizer
+
+            logger.info(
+                f"Uninitialised {self.name} model - "
+                f"computing z-norm factors from train dataloader.",
+            )
+            self.normalizer = make_z_normalizer(dataloader)
 
     def training_step(self, batch, batch_idx):
         images = batch[0]["image"]