Update NG

examples/gng_iris.py

@@ -17,11 +17,12 @@ if __name__ == "__main__":
 
     # Prepare the data
     train_ds = pt.datasets.Iris(dims=[0, 2])
-    train_loader = torch.utils.data.DataLoader(train_ds, batch_size=8)
+    train_loader = torch.utils.data.DataLoader(train_ds, batch_size=64)
 
     # Hyperparameters
     hparams = dict(
         num_prototypes=5,
+        input_dim=2,
         lr=0.1,
     )
 
@@ -50,6 +51,3 @@ if __name__ == "__main__":
 
     # Training loop
     trainer.fit(model, train_loader)
-
-    # Model summary
-    print(model)

examples/ng_iris.py

@@ -28,7 +28,11 @@ if __name__ == "__main__":
     train_loader = torch.utils.data.DataLoader(train_ds, batch_size=150)
 
     # Hyperparameters
-    hparams = dict(num_prototypes=30, lr=0.03)
+    hparams = dict(
+        num_prototypes=30,
+        input_dim=2,
+        lr=0.03,
+    )
 
     # Initialize the model
     model = pt.models.NeuralGas(

prototorch/models/unsupervised.py

@@ -28,7 +28,6 @@ class NeuralGas(UnsupervisedPrototypeModel):
         self.save_hyperparameters(hparams)
 
         # Default hparams
-        self.hparams.setdefault("input_dim", 2)
         self.hparams.setdefault("agelimit", 10)
         self.hparams.setdefault("lm", 1)