Simplify re-raising exceptions.

Most module use the simpler `raise` version. Normalize those that don't.

src/transformers/modeling_tf_pytorch_utils.py

@@ -76,12 +76,12 @@ def load_pytorch_checkpoint_in_tf2_model(tf_model, pytorch_checkpoint_path, tf_i
     try:
         import tensorflow as tf  # noqa: F401
         import torch  # noqa: F401
-    except ImportError as e:
+    except ImportError:
         logger.error(
             "Loading a PyTorch model in TensorFlow, requires both PyTorch and TensorFlow to be installed. Please see "
             "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions."
         )
-        raise e
+        raise
 
     pt_path = os.path.abspath(pytorch_checkpoint_path)
     logger.info("Loading PyTorch weights from {}".format(pt_path))
@@ -111,12 +111,12 @@ def load_pytorch_weights_in_tf2_model(tf_model, pt_state_dict, tf_inputs=None, a
         import torch  # noqa: F401
         import tensorflow as tf  # noqa: F401
         from tensorflow.python.keras import backend as K
-    except ImportError as e:
+    except ImportError:
         logger.error(
             "Loading a PyTorch model in TensorFlow, requires both PyTorch and TensorFlow to be installed. Please see "
             "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions."
         )
-        raise e
+        raise
 
     if tf_inputs is None:
         tf_inputs = tf_model.dummy_inputs
@@ -209,12 +209,12 @@ def load_tf2_checkpoint_in_pytorch_model(pt_model, tf_checkpoint_path, tf_inputs
     try:
         import tensorflow as tf  # noqa: F401
         import torch  # noqa: F401
-    except ImportError as e:
+    except ImportError:
         logger.error(
             "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see "
             "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions."
         )
-        raise e
+        raise
 
     import transformers
 
@@ -251,12 +251,12 @@ def load_tf2_weights_in_pytorch_model(pt_model, tf_weights, allow_missing_keys=F
     try:
         import tensorflow as tf  # noqa: F401
         import torch  # noqa: F401
-    except ImportError as e:
+    except ImportError:
         logger.error(
             "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see "
             "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions."
         )
-        raise e
+        raise
 
     new_pt_params_dict = {}
     current_pt_params_dict = dict(pt_model.named_parameters())

src/transformers/modeling_utils.py

@@ -454,12 +454,12 @@ class PreTrainedModel(nn.Module):
                     from transformers import load_tf2_checkpoint_in_pytorch_model
 
                     model = load_tf2_checkpoint_in_pytorch_model(model, resolved_archive_file, allow_missing_keys=True)
-                except ImportError as e:
+                except ImportError:
                     logger.error(
                         "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see "
                         "https://pytorch.org/ and https://www.tensorflow.org/install/ for installation instructions."
                     )
-                    raise e
+                    raise
         else:
             # Convert old format to new format if needed from a PyTorch state_dict
             old_keys = []

src/transformers/tokenization_xlm.py

@@ -646,7 +646,7 @@ class XLMTokenizer(PreTrainedTokenizer):
                 self.ja_word_tokenizer = Mykytea.Mykytea(
                     "-model %s/local/share/kytea/model.bin" % os.path.expanduser("~")
                 )
-            except (AttributeError, ImportError) as e:
+            except (AttributeError, ImportError):
                 logger.error(
                     "Make sure you install KyTea (https://github.com/neubig/kytea) and it's python wrapper (https://github.com/chezou/Mykytea-python) with the following steps"
                 )
@@ -655,7 +655,7 @@ class XLMTokenizer(PreTrainedTokenizer):
                 logger.error("3. ./configure --prefix=$HOME/local")
                 logger.error("4. make && make install")
                 logger.error("5. pip install kytea")
-                raise e
+                raise
         return list(self.ja_word_tokenizer.getWS(text))
 
     @property
@@ -760,12 +760,12 @@ class XLMTokenizer(PreTrainedTokenizer):
                     from pythainlp.tokenize import word_tokenize as th_word_tokenize
                 else:
                     th_word_tokenize = sys.modules["pythainlp"].word_tokenize
-            except (AttributeError, ImportError) as e:
+            except (AttributeError, ImportError):
                 logger.error(
                     "Make sure you install PyThaiNLP (https://github.com/PyThaiNLP/pythainlp) with the following steps"
                 )
                 logger.error("1. pip install pythainlp")
-                raise e
+                raise
             text = th_word_tokenize(text)
         elif lang == "zh":
             try:
@@ -773,10 +773,10 @@ class XLMTokenizer(PreTrainedTokenizer):
                     import jieba
                 else:
                     jieba = sys.modules["jieba"]
-            except (AttributeError, ImportError) as e:
+            except (AttributeError, ImportError):
                 logger.error("Make sure you install Jieba (https://github.com/fxsjy/jieba) with the following steps")
                 logger.error("1. pip install jieba")
-                raise e
+                raise
             text = " ".join(jieba.cut(text))
             text = self.moses_pipeline(text, lang=lang)
             text = text.split()