Add has_attentions to TFModelTesterMixin as done on PyTorch side (#16259)

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/test_modeling_tf_common.py

@@ -114,6 +114,7 @@ class TFModelTesterMixin:
     test_resize_embeddings = True
     test_head_masking = True
     is_encoder_decoder = False
+    has_attentions = True
 
     def _prepare_for_class(self, inputs_dict, model_class, return_labels=False) -> dict:
         inputs_dict = copy.deepcopy(inputs_dict)
@@ -539,9 +540,7 @@ class TFModelTesterMixin:
 
             # Output all for aggressive testing
             config.output_hidden_states = True
-            # Pure convolutional models have no attention
-            # TODO: use a better and general criteria
-            if "TFConvNext" not in model_class.__name__:
+            if self.has_attentions:
                 config.output_attentions = True
 
             for k in ["attention_mask", "encoder_attention_mask", "decoder_attention_mask"]:
@@ -567,8 +566,6 @@ class TFModelTesterMixin:
             pt_model_class_name = model_class.__name__[2:]  # Skip the "TF" at the beginning
             pt_model_class = getattr(transformers, pt_model_class_name)
 
-            config.output_hidden_states = True
-
             tf_model = model_class(config)
             pt_model = pt_model_class(config)