Make cbc example reproducible

examples/cbc_iris.py

@@ -11,6 +11,9 @@ if __name__ == "__main__":
     x_train = x_train[:, [0, 2]]
     train_ds = pt.datasets.NumpyDataset(x_train, y_train)
 
+    # Reproducibility
+    pl.utilities.seed.seed_everything(seed=2)
+
     # Dataloaders
     train_loader = torch.utils.data.DataLoader(train_ds,
                                                num_workers=0,
@@ -20,8 +23,8 @@ if __name__ == "__main__":
     hparams = dict(
         input_dim=x_train.shape[1],
         nclasses=3,
-        num_components=9,
-        component_initializer=pt.components.SMI(train_ds),
+        num_components=5,
+        component_initializer=pt.components.SSI(train_ds, noise=0.01),
         lr=0.01,
     )
 
@@ -34,7 +37,7 @@ if __name__ == "__main__":
 
     # Setup trainer
     trainer = pl.Trainer(
-        max_epochs=50,
+        max_epochs=200,
         callbacks=[
             dvis,
         ],