Fix label datatype in TF Trainer (#9616)

* Fix label datatype

* Apply style

src/transformers/trainer_tf.py

@@ -638,7 +638,15 @@ class TFTrainer:
                 reduced_features = {
                     k: ft[: self.args.train_batch_size // self.args.n_replicas] for k, ft in features.items()
                 }
+
+                if tf.is_tensor(labels):
                     reduced_labels = labels[: self.args.train_batch_size // self.args.n_replicas]
+                elif isinstance(labels, dict):
+                    reduced_labels = {
+                        k: lbl[: self.args.train_batch_size // self.args.n_replicas] for k, lbl in labels.items()
+                    }
+                else:
+                    raise ValueError("The labels must be either a tf.Tensor or a dict.")
 
                 self.training_step(reduced_features, reduced_labels, nb_instances_in_global_batch)
 
@@ -650,9 +658,20 @@ class TFTrainer:
                     for k, ft in features.items()
                 }
 
+                if tf.is_tensor(labels):
                     labels = tf.concat(
                         [labels[self.args.train_batch_size // self.args.n_replicas :], reduced_labels], axis=0
                     )
+                elif isinstance(labels, dict):
+                    labels = {
+                        k: tf.concat(
+                            [lbl[self.args.train_batch_size // self.args.n_replicas :], reduced_labels[k]],
+                            axis=0,
+                        )
+                        for k, lbl in labels.items()
+                    }
+                else:
+                    raise ValueError("The labels must be either a tf.Tensor or a dict.")
 
             gradients = self.gradient_accumulator.gradients
             gradients = [