fix pylint issue

Author: ftian1

lpot/adaptor/torch_utils/util.py

@@ -24,9 +24,11 @@ def collate_torch_preds(results):
         results = zip(*results)
         collate_results = []
         for output in results:
-           output = [batch.numpy() if isinstance(batch, torch.Tensor) else batch for batch in output]
+           output = [batch.numpy() if isinstance(batch, torch.Tensor) \
+                         else batch for batch in output]
            collate_results.append(np.concatenate(output))
     elif isinstance(batch, torch.Tensor):
-        results = [batch.numpy() if isinstance(batch, torch.Tensor) else batch for batch in results]
+        results = [batch.numpy() if isinstance(batch, torch.Tensor) \
+                       else batch for batch in results]
         collate_results = np.concatenate(results)
     return collate_results

lpot/experimental/quantization.py

@@ -192,8 +192,9 @@ def calib_dataloader(self, dataloader):
                                       a 'real' calib_dataloader will be created, 
                                       the reason is we have to know the framework info
                                       and only after the Quantization object created then
-                                      framework infomation can be known. Future we will support
-                                      creating iterable dataloader from lpot.experimental.common.DataLoader
+                                      framework infomation can be known.
+                                      Future we will support creating iterable dataloader
+                                      from lpot.experimental.common.DataLoader
         """
         from .common import _generate_common_dataloader
         self._calib_dataloader = _generate_common_dataloader(