Update modeling_diffusiondet.py

modeling_diffusiondet.py

@@ -128,12 +128,12 @@ class DiffusionDet(PreTrainedModel):
 
     def _init_weights(self, module):
         if isinstance(module, nn.Linear) or isinstance(module, nn.Conv2d):
-            init.kaiming_normal_(m.weight, mode='fan_in', nonlinearity='relu')
+            torch.nn.init.kaiming_normal_(m.weight, mode='fan_in', nonlinearity='relu')
         if module.bias is not None:
-            init.constant_(module.bias, 0)
+            torch.nn.init.constant_(module.bias, 0)
         elif isinstance(module, nn.BatchNorm2d):
-            init.constant_(module.weight, 1)
-            init.constant_(module.bias, 0)
+            torch.nn.init.constant_(module.weight, 1)
+            torch.nn.init.constant_(module.bias, 0)
 
     def predict_noise_from_start(self, x_t, t, x0):
         return (