No implicit learning rate scheduling

examples/glvq_iris.py

@@ -2,10 +2,10 @@
 
 import argparse
 
+import prototorch as pt
 import pytorch_lightning as pl
 import torch
-
-import prototorch as pt
+from torch.optim.lr_scheduler import ExponentialLR
 
 if __name__ == "__main__":
     # Command-line arguments
@@ -29,9 +29,16 @@ if __name__ == "__main__":
     )
 
     # Initialize the model
-    model = pt.models.GLVQ(hparams,
-                           optimizer=torch.optim.Adam,
-                           prototype_initializer=pt.components.SMI(train_ds))
+    model = pt.models.GLVQ(
+        hparams,
+        optimizer=torch.optim.Adam,
+        prototype_initializer=pt.components.SMI(train_ds),
+        lr_scheduler=ExponentialLR,
+        lr_scheduler_kwargs=dict(gamma=0.99, verbose=False),
+    )
+
+    # Compute intermediate input and output sizes
+    model.example_input_array = torch.zeros(4, 2)
 
     # Callbacks
     vis = pt.models.VisGLVQ2D(data=train_ds)
@@ -40,6 +47,8 @@ if __name__ == "__main__":
     trainer = pl.Trainer.from_argparse_args(
         args,
         callbacks=[vis],
+        weights_summary="full",
+        accelerator="ddp",
     )
 
     # Training loop