Update train.py

Author: adityac8

Deraining/train.py

@@ -117,8 +117,8 @@
         restored = model_restoration(input_)
 
         # Compute loss at each stage
-        loss_char = np.sum([criterion_char(restored[j],target) for j in range(len(restored))])
-        loss_edge = np.sum([criterion_edge(restored[j],target) for j in range(len(restored))])
+        loss_char = torch.sum([criterion_char(restored[j],target) for j in range(len(restored))])
+        loss_edge = torch.sum([criterion_edge(restored[j],target) for j in range(len(restored))])
         loss = (loss_char) + (0.05*loss_edge)
 
         loss.backward()