Update Examples to new initializer architecture.

Visualization still borken for some examples.

prototorch/models/glvq.py

@@ -1,4 +1,3 @@
-import pytorch_lightning as pl
 import torch
 import torchmetrics
 from prototorch.components import LabeledComponents
@@ -7,7 +6,6 @@ from prototorch.functions.competitions import wtac
 from prototorch.functions.distances import (euclidean_distance,
                                             squared_euclidean_distance)
 from prototorch.functions.losses import glvq_loss
-from prototorch.modules.prototypes import Prototypes1D
 
 from .abstract import AbstractPrototypeModel
 
@@ -55,7 +53,6 @@ class GLVQ(AbstractPrototypeModel):
         with torch.no_grad():
             preds = wtac(dis, plabels)
         # `.int()` because FloatTensors are assumed to be class probabilities
-        self.train_acc(preds.int(), y.int())
 
         # Logging
         self.log("train_loss", loss)