GLVQ with configurable distance.

prototorch/models/glvq.py

@@ -12,13 +12,19 @@ class GLVQ(pl.LightningModule):
     """Generalized Learning Vector Quantization."""
     def __init__(self, hparams, **kwargs):
         super().__init__()
+
         self.save_hyperparameters(hparams)
+
+        # Default Values
+        self.hparams.setdefault("distance", euclidean_distance)
+
         self.proto_layer = Prototypes1D(
             input_dim=self.hparams.input_dim,
             nclasses=self.hparams.nclasses,
             prototypes_per_class=self.hparams.prototypes_per_class,
             prototype_initializer=self.hparams.prototype_initializer,
             **kwargs)
+
         self.train_acc = torchmetrics.Accuracy()
 
     @property
@@ -35,7 +41,7 @@ class GLVQ(pl.LightningModule):
 
     def forward(self, x):
         protos = self.proto_layer.prototypes
-        dis = euclidean_distance(x, protos)
+        dis = self.hparams.distance(x, protos)
         return dis
 
     def training_step(self, train_batch, batch_idx):