[housekeeping] super()

src/transformers/modeling_bert.py

@@ -1347,7 +1347,7 @@ class BertForTokenClassification(BertPreTrainedModel):
 )
 class BertForQuestionAnswering(BertPreTrainedModel):
     def __init__(self, config):
-        super(BertForQuestionAnswering, self).__init__(config)
+        super().__init__(config)
         self.num_labels = config.num_labels
 
         self.bert = BertModel(config)

src/transformers/modeling_flaubert.py

@@ -112,7 +112,7 @@ class FlaubertModel(XLMModel):
     pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config):  # , dico, is_encoder, with_output):
-        super(FlaubertModel, self).__init__(config)
+        super().__init__(config)
         self.layerdrop = getattr(config, "layerdrop", 0.0)
         self.pre_norm = getattr(config, "pre_norm", False)
 
@@ -307,7 +307,7 @@ class FlaubertWithLMHeadModel(XLMWithLMHeadModel):
     pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config):
-        super(FlaubertWithLMHeadModel, self).__init__(config)
+        super().__init__(config)
         self.transformer = FlaubertModel(config)
         self.init_weights()
 
@@ -327,7 +327,7 @@ class FlaubertForSequenceClassification(XLMForSequenceClassification):
     pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config):
-        super(FlaubertForSequenceClassification, self).__init__(config)
+        super().__init__(config)
         self.transformer = FlaubertModel(config)
         self.init_weights()
 
@@ -347,7 +347,7 @@ class FlaubertForQuestionAnsweringSimple(XLMForQuestionAnsweringSimple):
     pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config):
-        super(FlaubertForQuestionAnsweringSimple, self).__init__(config)
+        super().__init__(config)
         self.transformer = FlaubertModel(config)
         self.init_weights()
 
@@ -367,6 +367,6 @@ class FlaubertForQuestionAnswering(XLMForQuestionAnswering):
     pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config):
-        super(FlaubertForQuestionAnswering, self).__init__(config)
+        super().__init__(config)
         self.transformer = FlaubertModel(config)
         self.init_weights()

src/transformers/modeling_tf_flaubert.py

@@ -107,13 +107,13 @@ class TFFlaubertModel(TFXLMModel):
     pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config, *inputs, **kwargs):
-        super(TFFlaubertModel, self).__init__(config, *inputs, **kwargs)
+        super().__init__(config, *inputs, **kwargs)
         self.transformer = TFFlaubertMainLayer(config, name="transformer")
 
 
 class TFFlaubertMainLayer(TFXLMMainLayer):
     def __init__(self, config, *inputs, **kwargs):
-        super(TFFlaubertMainLayer, self).__init__(config, *inputs, **kwargs)
+        super().__init__(config, *inputs, **kwargs)
         self.layerdrop = getattr(config, "layerdrop", 0.0)
         self.pre_norm = getattr(config, "pre_norm", False)
 
@@ -312,7 +312,7 @@ class TFFlaubertWithLMHeadModel(TFXLMWithLMHeadModel):
     pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config, *inputs, **kwargs):
-        super(TFFlaubertWithLMHeadModel, self).__init__(config, *inputs, **kwargs)
+        super().__init__(config, *inputs, **kwargs)
         self.transformer = TFFlaubertMainLayer(config, name="transformer")
 
 
@@ -326,5 +326,5 @@ class TFFlaubertForSequenceClassification(TFXLMForSequenceClassification):
     pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
     def __init__(self, config, *inputs, **kwargs):
-        super(TFFlaubertForSequenceClassification, self).__init__(config, *inputs, **kwargs)
+        super().__init__(config, *inputs, **kwargs)
         self.transformer = TFFlaubertMainLayer(config, name="transformer")