fix using cuda with model.predict

braindecode/models/base.py

@@ -285,8 +285,12 @@ class BaseModel(object):
             Predicted labels per trial. 
         """
         all_preds = []
-        for b_X, _ in self.iterator.get_batches(SignalAndTarget(X, X), False):
-            all_preds.append(var_to_np(self.network(np_to_var(b_X))))
+        with th.no_grad():
+            for b_X, _ in self.iterator.get_batches(SignalAndTarget(X, X), False):
+                b_X_var = np_to_var(b_X)
+                if self.cuda:
+                    b_X_var = b_X_var.cuda()
+                all_preds.append(var_to_np(self.network(b_X_var)))
         if self.cropped:
             pred_labels = compute_trial_labels_from_crop_preds(
                 all_preds, self.iterator.input_time_length, X)

braindecode/version.py

@@ -1 +1 @@
-__version__ = "0.4.5"
+__version__ = "0.4.6"