[tests] remove TF tests (uses of require_tf) (#38944)

* remove uses of require_tf

* remove redundant import guards

* this class has no tests

* nits

* del tf rng comment

tests/utils/test_modeling_utils.py

@@ -61,7 +61,6 @@ from transformers.testing_utils import (
     require_non_hpu,
     require_read_token,
     require_safetensors,
-    require_tf,
     require_torch,
     require_torch_accelerator,
     require_torch_multi_accelerator,
@@ -79,7 +78,6 @@ from transformers.utils.import_utils import (
     is_flash_attn_2_available,
     is_flash_attn_3_available,
     is_flax_available,
-    is_tf_available,
     is_torch_npu_available,
     is_torch_sdpa_available,
 )
@@ -322,9 +320,6 @@ class TestModelGammaBeta(PreTrainedModel):
 if is_flax_available():
     from transformers import FlaxBertModel
 
-if is_tf_available():
-    from transformers import TFBertModel
-
 
 TINY_T5 = "patrickvonplaten/t5-tiny-random"
 TINY_BERT_FOR_TOKEN_CLASSIFICATION = "hf-internal-testing/tiny-bert-for-token-classification"
@@ -1535,27 +1530,6 @@ class ModelUtilsTest(TestCasePlus):
         for p1, p2 in zip(hub_model.parameters(), new_model.parameters()):
             self.assertTrue(torch.equal(p1, p2))
 
-    @require_tf
-    @require_safetensors
-    def test_safetensors_torch_from_tf(self):
-        hub_model = BertModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only")
-        model = TFBertModel.from_pretrained("hf-internal-testing/tiny-bert-tf-only")
-
-        with tempfile.TemporaryDirectory() as tmp_dir:
-            model.save_pretrained(tmp_dir, safe_serialization=True)
-            new_model = BertModel.from_pretrained(tmp_dir)
-
-        for p1, p2 in zip(hub_model.parameters(), new_model.parameters()):
-            self.assertTrue(torch.equal(p1, p2))
-
-    @require_tf
-    def test_torch_from_tf(self):
-        model = TFBertModel.from_pretrained("hf-internal-testing/tiny-bert-tf-only")
-
-        with tempfile.TemporaryDirectory() as tmp_dir:
-            model.save_pretrained(tmp_dir)
-            _ = BertModel.from_pretrained(tmp_dir, from_tf=True)
-
     @require_safetensors
     def test_safetensors_torch_from_torch_sharded(self):
         model = BertModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only")