seems to fix larvatagger.jl#76

src/maggotuba/models/modules.py

@@ -90,6 +90,9 @@ class MaggotModule(nn.Module):
     def parameters(self, recurse=True):
         return self.model.parameters(recurse)
 
+    def to(self, device):
+        self.model.to(device)
+
 
 """
 Initialize a model's weights and bias (if any).
@@ -305,6 +308,9 @@ class DeepLinear(nn.Module):
         torch.save(self.state_dict(), path)
         check_permissions(path)
 
+    def to(self, device):
+        self.layers.to(device)
+
 class MaggotClassifier(MaggotModule):
     def __init__(self, path, behavior_labels=[], n_latent_features=None,
             n_layers=1, cfgfile=None, ptfile="trained_classifier.pt"):
@@ -385,6 +391,10 @@ class SupervisedMaggot(nn.Module):
         self.clf.model # force parameter loading or initialization
         return super().parameters(self)
 
+    def to(self, device):
+        self.encoder.to(device)
+        self.clf.to(device)
+
 class MultiscaleSupervisedMaggot(nn.Module):
     def __init__(self, cfgfilepath, behaviors=[], n_layers=1):
         super().__init__()

src/maggotuba/models/trainers.py

@@ -231,7 +231,7 @@ class MaggotTrainer:
         self.model.save()
 
 def new_generator(seed=None):
-    generator = torch.Generator(device)
+    generator = torch.Generator('cpu')
     if seed == 'random': return generator
     if seed is None: seed = 0b11010111001001101001110
     return generator.manual_seed(seed)