Use raise .. from .. to explicitly chain exceptions (Lightning-AI#3750

) * Fix exception chaining * names * Change exception names for consistency Co-authored-by: Nicki Skafte <[email protected]> * Change exception names for consistency Co-authored-by: Nicki Skafte <[email protected]> Co-authored-by: Jirka Borovec <[email protected]> Co-authored-by: Nicki Skafte <[email protected]>
nrupatunga · Oct 1, 2020 · ebc1b23 · ebc1b23
1 parent e17712e
commit ebc1b23
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Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/pytorch_lightning/accelerators/ddp2_backend.py b/pytorch_lightning/accelerators/ddp2_backend.py
@@ -47,9 +47,9 @@ def _resolve_task_idx(self):
             # torchelastic or general non_slurm ddp2
             try:
                 self.task_idx = int(os.environ['LOCAL_RANK'])
-            except Exception as e:
+            except Exception as exp:
                 m = 'ddp2 only works in SLURM or via torchelastic with the WORLD_SIZE, LOCAL_RANK, GROUP_RANK flags'
-                raise MisconfigurationException(m)
+                raise MisconfigurationException(m) from exp
 
     def train(self):
         model = self.trainer.model

diff --git a/pytorch_lightning/trainer/logging.py b/pytorch_lightning/trainer/logging.py
@@ -141,13 +141,13 @@ def process_dict_result(self, output, train=False):
         if train:
             try:
                 loss = output['loss']
-            except Exception:
+            except Exception as exp:
                 if isinstance(output, torch.Tensor):
                     loss = output
                 else:
                     raise RuntimeError(
                         'No `loss` value in the dictionary returned from `model.training_step()`.'
-                    )
+                    ) from exp
 
             # when using dp need to reduce the loss
             if self.use_dp or self.use_ddp2:

diff --git a/pytorch_lightning/utilities/parsing.py b/pytorch_lightning/utilities/parsing.py
@@ -158,8 +158,8 @@ class AttributeDict(Dict):
     def __getattr__(self, key):
         try:
             return self[key]
-        except KeyError:
-            raise AttributeError(f'Missing attribute "{key}"')
+        except KeyError as exp:
+            raise AttributeError(f'Missing attribute "{key}"') from exp
 
     def __setattr__(self, key, val):
         self[key] = val

diff --git a/tests/base/models.py b/tests/base/models.py
@@ -10,9 +10,9 @@
 
 try:
     from test_tube import HyperOptArgumentParser
-except ImportError:
+except ImportError as exp:
     # TODO: this should be discussed and moved out of this package
-    raise ImportError('Missing test-tube package.')
+    raise ImportError('Missing test-tube package.') from exp
 
 from pytorch_lightning.core.lightning import LightningModule