Cache: revert DynamicCache init for BC (#33861)

* tmp commit

* tmp commit

* make fixup

* missing removal

* fix condition

* fix end-to-end compilation

* if -> elif

* BC

* BC

* use @deprecate_kwarg("num_hidden_layers", version="4.47.0")

* wups the import

* 🥴

---------

Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>

tests/models/mllama/test_modeling_mllama.py

@@ -383,45 +383,73 @@ class MllamaForConditionalGenerationModelTest(ModelTesterMixin, GenerationTester
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_beam_sample_generate_dict_output():
+    def test_beam_sample_generate_dict_output(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_beam_search_generate_dict_output():
+    def test_beam_search_generate_dict_output(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_constrained_beam_search_generate_dict_output():
+    def test_constrained_beam_search_generate_dict_output(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_dola_decoding_sample():
+    def test_dola_decoding_sample(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_generate_methods_with_num_logits_to_keep():
+    def test_generate_methods_with_num_logits_to_keep(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_greedy_generate_dict_outputs():
+    def test_greedy_generate_dict_outputs(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_group_beam_search_generate_dict_output():
+    def test_group_beam_search_generate_dict_output(self):
         pass
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_model_parallel_beam_search():
+    def test_model_parallel_beam_search(self):
         pass
 
-    @unittest.skip(reason="Failing test, need to fix")
-    def test_new_cache_format_2():
-        pass
+    @is_flaky()  # TODO (joao, raushan) - investigate why this test is flaky (probably depends on the model initialization)
+    def test_new_cache_format_0(self):
+        super().test_new_cache_format_0()
+
+    @is_flaky()  # TODO (joao, raushan) - investigate why this test is flaky (probably depends on the model initialization)
+    def test_new_cache_format_1(self):
+        super().test_new_cache_format_1()
+
+    @is_flaky()  # TODO (joao, raushan) - investigate why this test is flaky (probably depends on the model initialization)
+    def test_new_cache_format_2(self):
+        super().test_new_cache_format_2()
 
     @unittest.skip(reason="Failing test, need to fix")
-    def test_sample_generate_dict_output():
+    def test_sample_generate_dict_output(self):
         pass
 
+    def test_generate_text_only_with_cache(self):
+        """
+        Tests that our cached generation with text-only inputs works. When mllama was introduced, this feature
+        required cache modifications (because layers are skipped in practice). This test should prevent regressions.
+        """
+        config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_model_classes:
+            model = model_class(config)
+            model.to(torch_device)
+            model.eval()
+
+            inputs = self._prepare_for_class(inputs_dict, model_class)
+
+            input_ids = inputs["input_ids"]
+            del inputs["input_ids"]
+            del inputs["pixel_values"]
+
+            model.generate(input_ids, use_cache=True)
+
 
 @require_torch
 class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):