Use `raise .. from ..` to explicitly chain exceptions (#3750)

* Fix exception chaining

* names

* Change exception names for consistency

Co-authored-by: Nicki Skafte <skaftenicki@gmail.com>

* Change exception names for consistency

Co-authored-by: Nicki Skafte <skaftenicki@gmail.com>

Co-authored-by: Jirka Borovec <jirka@pytorchlightning.ai>
Co-authored-by: Nicki Skafte <skaftenicki@gmail.com>

pytorch_lightning/accelerators/ddp2_backend.py

@@ -47,9 +47,9 @@ class DDP2Backend(DDPBase):
             # 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

pytorch_lightning/trainer/logging.py

@@ -141,13 +141,13 @@ class TrainerLoggingMixin(ABC):
         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:

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

tests/base/models.py

@@ -10,9 +10,9 @@ from tests.base.datasets import TrialMNIST, AverageDataset, MNIST
 
 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