[test] the the CNNTrainer using LightCNN9

bob/learn/pytorch/test/test.py

@@ -124,7 +124,7 @@ class DummyDataSet(Dataset):
   def __len__(self):
     return 100
   def __getitem__(self, idx):
-    data =  numpy.random.rand(3, 128, 128).astype("float32")
+    data =  numpy.random.rand(1, 128, 128).astype("float32")
     label = numpy.random.randint(20)
     sample = {'image': torch.from_numpy(data), 'label': label}
     return sample
@@ -132,8 +132,8 @@ class DummyDataSet(Dataset):
 
 def test_CNNtrainer():
 
-  from ..architectures import CNN8
-  net = CNN8(20)
+  from ..architectures import LightCNN9
+  net = LightCNN9(20)
 
   dataloader = torch.utils.data.DataLoader(DummyDataSet(), batch_size=32, shuffle=True)