[BUGFIX] GNG Example

examples/gng_iris.py

@@ -4,7 +4,7 @@ import argparse
 
 import prototorch as pt
 import pytorch_lightning as pl
-from prototorch.components.initializers import SelectionInitializer
+from prototorch.components.initializers import Zeros
 from prototorch.datasets import Iris
 from prototorch.models.unsupervised import GrowingNeuralGas
 from torch.utils.data import DataLoader
@@ -23,12 +23,16 @@ if __name__ == "__main__":
     train_loader = DataLoader(train_ds, batch_size=8)
 
     # Hyperparameters
-    hparams = dict(num_prototypes=5,
-                   lr=0.1,
-                   prototype_initializer=SelectionInitializer(train_ds.data))
+    hparams = dict(
+        num_prototypes=5,
+        lr=0.1,
+    )
 
     # Initialize the model
-    model = GrowingNeuralGas(hparams)
+    model = GrowingNeuralGas(
+        hparams,
+        prototype_initializer=Zeros(2),
+    )
 
     # Model summary
     print(model)

prototorch/models/glvq.py

@@ -64,7 +64,7 @@ class GLVQ(AbstractPrototypeModel):
     def forward(self, x):
         distances = self._forward(x)
         y_pred = self.predict_from_distances(distances)
-        y_pred = torch.eye(self.num_classes, device=self.device)[y_pred.int()]
+        y_pred = torch.eye(self.num_classes, device=self.device)[y_pred.long()]
         return y_pred
 
     def predict_from_distances(self, distances):