annotated TFvisionEncoderDecoder input type hints (#21432)

* annotated TFvisionEncoderDecoder input type hints
Co-authored-by: JuheonChu <chuj@dickinson.edu>
Co-authored-by: AdiaWu <wua@dickinson.edu>

* fixed failing tests

* make fix-copies

* failed test fix

* style fix

* revert

---------
Co-authored-by: JuheonChu <chuj@dickinson.edu>
Co-authored-by: AdiaWu <wua@dickinson.edu>
Co-authored-by: Matt <rocketknight1@gmail.com>

src/transformers/models/vision_encoder_decoder/modeling_tf_vision_encoder_decoder.py

@@ -19,8 +19,9 @@ import gc
 import os
 import tempfile
 import warnings
-from typing import Optional
+from typing import Optional, Tuple, Union
 
+import numpy as np
 import tensorflow as tf
 
 from ...configuration_utils import PretrainedConfig
@@ -534,20 +535,20 @@ class TFVisionEncoderDecoderModel(TFPreTrainedModel, TFCausalLanguageModelingLos
     @replace_return_docstrings(output_type=TFSeq2SeqLMOutput, config_class=_CONFIG_FOR_DOC)
     def call(
         self,
-        pixel_values=None,
-        decoder_input_ids=None,
-        decoder_attention_mask=None,
-        encoder_outputs=None,
-        past_key_values=None,
-        decoder_inputs_embeds=None,
-        labels=None,
-        use_cache=None,
-        output_attentions=None,
-        output_hidden_states=None,
-        return_dict=None,
-        training=False,
+        pixel_values: Optional[Union[np.ndarray, tf.Tensor]] = None,
+        decoder_input_ids: Optional[Union[np.ndarray, tf.Tensor]] = None,
+        decoder_attention_mask: Optional[Union[np.ndarray, tf.Tensor]] = None,
+        encoder_outputs: Optional[Union[Tuple, TFBaseModelOutput]] = None,
+        past_key_values: Optional[Tuple[Tuple[Union[np.ndarray, tf.Tensor]]]] = None,
+        decoder_inputs_embeds: Optional[Union[np.ndarray, tf.Tensor]] = None,
+        labels: Optional[Union[np.ndarray, tf.Tensor]] = None,
+        use_cache: Optional[bool] = None,
+        output_attentions: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        training: bool = False,
         **kwargs,
-    ):
+    ) -> Union[TFSeq2SeqLMOutput, Tuple[tf.Tensor]]:
         r"""
         Returns: