[TF] Fix creating a PR while pushing in TF framework

src/transformers/modeling_tf_utils.py

@@ -2905,9 +2905,10 @@ def push_to_hub(
         use_temp_dir: Optional[bool] = None,
         commit_message: Optional[str] = None,
         private: Optional[bool] = None,
-        use_auth_token: Optional[Union[bool, str]] = None,
         max_shard_size: Optional[Union[int, str]] = "10GB",
-        **model_card_kwargs,
+        use_auth_token: Optional[Union[bool, str]] = None,
+        create_pr: bool = False,
+        **base_model_card_args,
     ) -> str:
         """
         Upload the model files to the 🤗 Model Hub while synchronizing a local clone of the repo in `repo_path_or_name`.
@@ -2931,8 +2932,8 @@ def push_to_hub(
                 Only applicable for models. The maximum size for a checkpoint before being sharded. Checkpoints shard
                 will then be each of size lower than this size. If expressed as a string, needs to be digits followed
                 by a unit (like `"5MB"`).
-            model_card_kwargs:
-                Additional keyword arguments passed along to the [`~TFPreTrainedModel.create_model_card`] method.
+            create_pr (`bool`, *optional*, defaults to `False`):
+                Whether or not to create a PR with the uploaded files or directly commit.
 
         Examples:
 
@@ -2948,15 +2949,15 @@ def push_to_hub(
         model.push_to_hub("huggingface/my-finetuned-bert")
         ```
         """
-        if "repo_path_or_name" in model_card_kwargs:
+        if "repo_path_or_name" in base_model_card_args:
             warnings.warn(
                 "The `repo_path_or_name` argument is deprecated and will be removed in v5 of Transformers. Use "
                 "`repo_id` instead."
             )
-            repo_id = model_card_kwargs.pop("repo_path_or_name")
+            repo_id = base_model_card_args.pop("repo_path_or_name")
         # Deprecation warning will be sent after for repo_url and organization
-        repo_url = model_card_kwargs.pop("repo_url", None)
-        organization = model_card_kwargs.pop("organization", None)
+        repo_url = base_model_card_args.pop("repo_url", None)
+        organization = base_model_card_args.pop("organization", None)
 
         if os.path.isdir(repo_id):
             working_dir = repo_id
@@ -2982,11 +2983,16 @@ def push_to_hub(
                     "output_dir": work_dir,
                     "model_name": Path(repo_id).name,
                 }
-                base_model_card_args.update(model_card_kwargs)
+                base_model_card_args.update(base_model_card_args)
                 self.create_model_card(**base_model_card_args)
 
             self._upload_modified_files(
-                work_dir, repo_id, files_timestamps, commit_message=commit_message, token=use_auth_token
+                work_dir,
+                repo_id,
+                files_timestamps,
+                commit_message=commit_message,
+                token=use_auth_token,
+                create_pr=create_pr,
             )
 
     @classmethod

tests/test_modeling_tf_common.py

@@ -85,13 +85,15 @@
         TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
         TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
         BertConfig,
+        PreTrainedModel,
         PushToHubCallback,
         RagRetriever,
         TFAutoModel,
         TFAutoModelForSequenceClassification,
         TFBertForMaskedLM,
         TFBertForSequenceClassification,
         TFBertModel,
+        TFPreTrainedModel,
         TFRagModel,
         TFSharedEmbeddings,
     )
@@ -2466,6 +2468,7 @@ def test_push_to_hub(self):
                 break
         self.assertTrue(models_equal)
 
+    @is_pt_tf_cross_test
     def test_push_to_hub_callback(self):
         config = BertConfig(
             vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37
@@ -2489,6 +2492,12 @@ def test_push_to_hub_callback(self):
                 break
         self.assertTrue(models_equal)
 
+        tf_push_to_hub_params = dict(inspect.signature(TFPreTrainedModel.push_to_hub).parameters)
+        tf_push_to_hub_params.pop("base_model_card_args")
+        pt_push_to_hub_params = dict(inspect.signature(PreTrainedModel.push_to_hub).parameters)
+        pt_push_to_hub_params.pop("deprecated_kwargs")
+        self.assertDictEaual(tf_push_to_hub_params, pt_push_to_hub_params)
+
     def test_push_to_hub_in_organization(self):
         config = BertConfig(
             vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37