Fix `test_tf_encode_plus_sent_to_model` for `TAPAS` (#19559)

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

tests/models/tapas/test_tokenization_tapas.py

@@ -143,8 +143,39 @@ class TapasTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         return input_text, output_text
 
     @require_tensorflow_probability
+    @slow
     def test_tf_encode_plus_sent_to_model(self):
-        super().test_tf_encode_plus_sent_to_model()
+        from transformers import TF_MODEL_MAPPING, TOKENIZER_MAPPING
+
+        MODEL_TOKENIZER_MAPPING = merge_model_tokenizer_mappings(TF_MODEL_MAPPING, TOKENIZER_MAPPING)
+
+        tokenizers = self.get_tokenizers(do_lower_case=False)
+        for tokenizer in tokenizers:
+            with self.subTest(f"{tokenizer.__class__.__name__}"):
+                if tokenizer.__class__ not in MODEL_TOKENIZER_MAPPING:
+                    return
+
+                config_class, model_class = MODEL_TOKENIZER_MAPPING[tokenizer.__class__]
+                config = config_class()
+
+                if config.is_encoder_decoder or config.pad_token_id is None:
+                    return
+
+                model = model_class(config)
+
+                # Make sure the model contains at least the full vocabulary size in its embedding matrix
+                self.assertGreaterEqual(model.config.vocab_size, len(tokenizer))
+
+                # Build sequence
+                first_ten_tokens = list(tokenizer.get_vocab().keys())[:10]
+                sequence = " ".join(first_ten_tokens)
+                table = self.get_table(tokenizer, length=0)
+                encoded_sequence = tokenizer.encode_plus(table, sequence, return_tensors="tf")
+                batch_encoded_sequence = tokenizer.batch_encode_plus(table, [sequence, sequence], return_tensors="tf")
+
+                # This should not fail
+                model(encoded_sequence)
+                model(batch_encoded_sequence)
 
     def test_rust_and_python_full_tokenizers(self):
         if not self.test_rust_tokenizer: