Stop calling expand_1d on newer TF versions (#20786)

src/transformers/modeling_tf_utils.py

@@ -1473,7 +1473,8 @@ def train_step(self, data):
         label_kwargs = find_labels(self.__class__)
         label_to_output = self.get_label_to_output_name_mapping()
         output_to_label = {val: key for key, val in label_to_output.items()}
-        if not self._using_dummy_loss:
+        if not self._using_dummy_loss and parse(tf.__version__) < parse("2.11.0"):
+            # Newer TF train steps leave this out
             data = data_adapter.expand_1d(data)
         x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data)
         # If the inputs are mutable dictionaries, make a shallow copy of them because we will modify
@@ -1580,7 +1581,8 @@ def test_step(self, data):
         label_kwargs = find_labels(self.__class__)
         label_to_output = self.get_label_to_output_name_mapping()
         output_to_label = {val: key for key, val in label_to_output.items()}
-        if not self._using_dummy_loss:
+        if not self._using_dummy_loss and parse(tf.__version__) < parse("2.11.0"):
+            # Newer versions leave this out
             data = data_adapter.expand_1d(data)
         x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data)
         # If the inputs are mutable dictionaries, make a shallow copy of them because we will modify