Fix quality

src/transformers/models/flaubert/modeling_tf_flaubert.py

@@ -902,7 +902,7 @@ class TFFlaubertForSequenceClassification(TFFlaubertPreTrainedModel, TFSequenceC
         return_dict: Optional[bool] = None,
         labels: Optional[Union[np.ndarray, tf.Tensor]] = None,
         training: bool = False,
-    ):
+    ) -> Union[TFSequenceClassifierOutput, Tuple[tf.Tensor]]:
         r"""
         labels (`tf.Tensor` of shape `(batch_size,)`, *optional*):
             Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,
@@ -990,7 +990,7 @@ class TFFlaubertForQuestionAnsweringSimple(TFFlaubertPreTrainedModel, TFQuestion
         start_positions: Optional[Union[np.ndarray, tf.Tensor]] = None,
         end_positions: Optional[Union[np.ndarray, tf.Tensor]] = None,
         training: bool = False,
-    ):
+    ) -> Union[TFQuestionAnsweringModelOutput, Tuple[tf.Tensor]]:
         r"""
         start_positions (`tf.Tensor` of shape `(batch_size,)`, *optional*):
             Labels for position (index) of the start of the labelled span for computing the token classification loss.
@@ -1094,7 +1094,7 @@ class TFFlaubertForTokenClassification(TFFlaubertPreTrainedModel, TFTokenClassif
         return_dict: Optional[bool] = None,
         labels: Optional[Union[np.ndarray, tf.Tensor]] = None,
         training: bool = False,
-    ):
+    ) -> Union[TFTokenClassifierOutput, Tuple[tf.Tensor]]:
         r"""
         labels (`tf.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
             Labels for computing the token classification loss. Indices should be in `[0, ..., config.num_labels - 1]`.
@@ -1203,7 +1203,7 @@ class TFFlaubertForMultipleChoice(TFFlaubertPreTrainedModel, TFMultipleChoiceLos
         return_dict: Optional[bool] = None,
         labels: Optional[Union[np.ndarray, tf.Tensor]] = None,
         training: bool = False,
-    ):
+    ) -> Union[TFMultipleChoiceModelOutput, Tuple[tf.Tensor]]:
         if input_ids is not None:
             num_choices = shape_list(input_ids)[1]
             seq_length = shape_list(input_ids)[2]