Clean load keys (#24505)

* Preliminary work on some models

* Fix test load missing and make sure nonpersistent buffers are tested

* Always ignore nonpersistent buffers if in state_dict

* Treat models

* More models

* Treat remaining models

* Fix quality

* Fix tests

* Remove draft

* This test is not needed anymore

* Fix copies

* Fix last test

* Newly added models

* Fix last tests

* Address review comments

tests/models/roberta/test_modeling_roberta.py

@@ -15,7 +15,6 @@
 
 
 import unittest
-from copy import deepcopy
 
 from transformers import RobertaConfig, is_torch_available
 from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
@@ -579,23 +578,3 @@ class RobertaModelIntegrationTest(TestCasePlus):
         # expected_tensor = roberta.predict("mnli", input_ids, return_logits=True).detach()
 
         self.assertTrue(torch.allclose(output, expected_tensor, atol=1e-4))
-
-    # XXX: this might be a candidate for common tests if we have many of those
-    def test_lm_head_ignore_keys(self):
-        keys_to_ignore_on_save_tied = [r"lm_head.decoder.weight", r"lm_head.decoder.bias"]
-        keys_to_ignore_on_save_untied = [r"lm_head.decoder.bias"]
-        config = RobertaConfig.from_pretrained(ROBERTA_TINY)
-        config_tied = deepcopy(config)
-        config_tied.tie_word_embeddings = True
-        config_untied = deepcopy(config)
-        config_untied.tie_word_embeddings = False
-        for cls in [RobertaForMaskedLM, RobertaForCausalLM]:
-            model = cls(config_tied)
-            self.assertEqual(model._keys_to_ignore_on_save, keys_to_ignore_on_save_tied, cls)
-
-            # the keys should be different when embeddings aren't tied
-            model = cls(config_untied)
-            self.assertEqual(model._keys_to_ignore_on_save, keys_to_ignore_on_save_untied, cls)
-
-            # test that saving works with updated ignore keys - just testing that it doesn't fail
-            model.save_pretrained(self.get_auto_remove_tmp_dir())