cuda no grad

model/pytorch/dcrnn_supervisor.py

@@ -37,6 +37,7 @@ class DCRNNSupervisor:
         # setup model
         dcrnn_model = DCRNNModel(adj_mx, self._logger, **self._model_kwargs)
         self.dcrnn_model = dcrnn_model.cuda() if torch.cuda.is_available() else dcrnn_model
+        self._logger.info("Model created")
 
     @staticmethod
     def _get_log_dir(kwargs):
@@ -93,6 +94,7 @@ class DCRNNSupervisor:
         Computes mean L1Loss
         :return: mean L1Loss
         """
+        with torch.no_grad():
             self.dcrnn_model = self.dcrnn_model.eval()
 
             val_iterator = self._data['{}_loader'.format(dataset)].get_iterator()