Examples use GPUs if available.

examples/cbc_iris.py

@@ -37,6 +37,7 @@ if __name__ == "__main__":
 
     # Setup trainer
     trainer = pl.Trainer(
+        gpus=-1,
         max_epochs=200,
         callbacks=[
             dvis,

examples/glvq_iris.py

@@ -30,10 +30,11 @@ if __name__ == "__main__":
                            prototype_initializer=pt.components.SMI(train_ds))
 
     # Callbacks
-    vis = pt.models.VisGLVQ2D(data=(x_train, y_train))
+    vis = pt.models.VisGLVQ2D(data=(x_train, y_train), block=False)
 
     # Setup trainer
     trainer = pl.Trainer(
+        gpus=-1,
         max_epochs=50,
         callbacks=[vis],
     )

examples/glvq_spiral.py

@@ -3,17 +3,7 @@
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
-
-
-class StopOnNaN(pl.Callback):
-    def __init__(self, param):
-        super().__init__()
-        self.param = param
-
-    def on_epoch_end(self, trainer, pl_module, logs={}):
-        if torch.isnan(self.param).any():
-            raise ValueError("NaN encountered. Stopping.")
-
+from prototorch.models.callbacks import StopOnNaN
 
 if __name__ == "__main__":
     # Dataset
@@ -40,11 +30,12 @@ if __name__ == "__main__":
                                                                    noise=1e-1))
 
     # Callbacks
-    vis = pt.models.VisGLVQ2D(train_ds, show_last_only=True, block=True)
+    vis = pt.models.VisGLVQ2D(train_ds, show_last_only=False, block=True)
     snan = StopOnNaN(model.proto_layer.components)
 
     # Setup trainer
     trainer = pl.Trainer(
+        gpus=-1,
         max_epochs=200,
         callbacks=[vis, snan],
     )

examples/gmlvq_iris.py

@@ -29,7 +29,7 @@ if __name__ == "__main__":
                             prototype_initializer=pt.components.SMI(train_ds))
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=100)
+    trainer = pl.Trainer(max_epochs=100, gpus=-1)
 
     # Training loop
     trainer.fit(model, train_loader)

examples/gmlvq_mnist.py

@@ -53,13 +53,15 @@ if __name__ == "__main__":
     # Callbacks
     vis = pt.models.VisImgComp(data=train_ds,
                                nrow=5,
-                               show=False,
-                               tensorboard=True)
+                               show=True,
+                               tensorboard=True,
+                               pause_time=0.5)
 
     # Setup trainer
     trainer = pl.Trainer(
         max_epochs=50,
         callbacks=[vis],
+        gpus=-1,
         # overfit_batches=1,
         # fast_dev_run=3,
     )

examples/knn_iris.py

@@ -26,7 +26,7 @@ if __name__ == "__main__":
     vis = pt.models.VisGLVQ2D(data=(x_train, y_train))
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=1, callbacks=[vis])
+    trainer = pl.Trainer(max_epochs=1, callbacks=[vis], gpus=-1)
 
     # Training loop
     # This is only for visualization. k-NN has no training phase.

examples/liramlvq_tecator.py

@@ -34,7 +34,7 @@ if __name__ == "__main__":
     vis = pt.models.VisSiameseGLVQ2D(train_ds, border=0.1)
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=200, callbacks=[vis])
+    trainer = pl.Trainer(max_epochs=200, callbacks=[vis], gpus=-1)
 
     # Training loop
     trainer.fit(model, train_loader)

examples/ng_iris.py

@@ -34,7 +34,7 @@ if __name__ == "__main__":
     vis = pt.models.VisNG2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=200, callbacks=[vis])
+    trainer = pl.Trainer(gpus=-1, max_epochs=200, callbacks=[vis])
 
     # Training loop
     trainer.fit(model, train_loader)

examples/siamese_glvq_iris.py

@@ -55,7 +55,7 @@ if __name__ == "__main__":
     vis = pt.models.VisSiameseGLVQ2D(data=train_ds, border=0.1)
 
     # Setup trainer
-    trainer = pl.Trainer(max_epochs=100, callbacks=[vis])
+    trainer = pl.Trainer(max_epochs=100, callbacks=[vis], gpus=-1)
 
     # Training loop
     trainer.fit(model, train_loader)