Add validation and test logic

examples/liramlvq_tecator.py

@@ -7,14 +7,14 @@ import torch
 if __name__ == "__main__":
     # Dataset
     train_ds = pt.datasets.Tecator(root="~/datasets/", train=True)
+    test_ds = pt.datasets.Tecator(root="~/datasets/", train=False)
 
     # Reproducibility
     pl.utilities.seed.seed_everything(seed=42)
 
     # Dataloaders
-    train_loader = torch.utils.data.DataLoader(train_ds,
-                                               num_workers=0,
-                                               batch_size=32)
+    train_loader = torch.utils.data.DataLoader(train_ds, batch_size=32)
+    test_loader = torch.utils.data.DataLoader(test_ds, batch_size=32)
 
     # Hyperparameters
     nclasses = 2
@@ -23,8 +23,8 @@ if __name__ == "__main__":
         distribution=(nclasses, prototypes_per_class),
         input_dim=100,
         latent_dim=2,
-        proto_lr=0.001,
-        bb_lr=0.001,
+        proto_lr=0.005,
+        bb_lr=0.005,
     )
 
     # Initialize the model
@@ -35,10 +35,15 @@ if __name__ == "__main__":
     vis = pt.models.VisSiameseGLVQ2D(train_ds, border=0.1)
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=200, callbacks=[vis], gpus=0)
+    trainer = pl.Trainer(
+        gpus=0,
+        max_epochs=20,
+        callbacks=[vis],
+        weights_summary=None,
+    )
 
     # Training loop
-    trainer.fit(model, train_loader)
+    trainer.fit(model, train_loader, test_loader)
 
     # Save the model
     torch.save(model, "liramlvq_tecator.pt")
@@ -48,3 +53,7 @@ if __name__ == "__main__":
 
     # Display the Lambda matrix
     saved_model.show_lambda()
+
+    # Testing
+    # TODO
+    # trainer.test(model, test_dataloaders=test_loader)

examples/siamese_glvq_iris.py

@@ -48,7 +48,7 @@ if __name__ == "__main__":
         hparams,
         prototype_initializer=pt.components.SMI(train_ds),
         backbone=backbone,
-        both_path_gradients=True,
+        both_path_gradients=False,
     )
 
     # Model summary