[tests] remove tests from libraries with deprecated support (flax, tensorflow_text, ...) (#39051)

* rm tf/flax tests

* more flax deletions

* revert fixture change

* reverted test that should not be deleted; rm tf/flax test

* revert

* fix a few add-model-like tests

* fix add-model-like checkpoint source

* a few more

* test_get_model_files_only_pt fix

* fix test_retrieve_info_for_model_with_xxx

* fix test_retrieve_model_classes

* relative paths are the devil

* add todo

tests/models/tapas/test_tokenization_tapas.py

@@ -33,7 +33,6 @@ from transformers.models.tapas.tokenization_tapas import (
 )
 from transformers.testing_utils import (
     require_pandas,
-    require_tensorflow_probability,
     require_tokenizers,
     require_torch,
     slow,
@@ -140,41 +139,6 @@ class TapasTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         output_text = "unwanted, running"
         return input_text, output_text
 
-    @require_tensorflow_probability
-    @slow
-    def test_tf_encode_plus_sent_to_model(self):
-        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:
-                    self.skipTest(f"{tokenizer.__class__} is not in the MODEL_TOKENIZER_MAPPING")
-
-                config_class, model_class = MODEL_TOKENIZER_MAPPING[tokenizer.__class__]
-                config = config_class()
-
-                if config.is_encoder_decoder or config.pad_token_id is None:
-                    self.skipTest(reason="Model is an encoder-decoder or does not have a pad token id set")
-
-                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:
             self.skipTest(reason="test_rust_tokenizer is set to False")