Enable decoder_attention_mask in generate function (#20726)

* Enable `decoder_attention_mask` in `generate` function

* Make style corrections

* Run `make repo-consistency`

* Add integration test

tests/models/bart/test_modeling_bart.py

@@ -1226,6 +1226,36 @@ class BartModelIntegrationTests(unittest.TestCase):
             ],
         )
 
+    @slow
+    def test_decoder_attention_mask(self):
+        model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", forced_bos_token_id=0).to(
+            torch_device
+        )
+        tokenizer = self.default_tokenizer
+        sentence = "UN Chief Says There Is No <mask> in Syria"
+        input_ids = tokenizer(sentence, return_tensors="pt").input_ids.to(torch_device)
+        padding_size = 3
+        decoder_input_ids = torch.tensor(
+            [
+                [model.config.decoder_start_token_id]
+                + padding_size * [model.config.pad_token_id]
+                + [model.config.bos_token_id]
+            ],
+            dtype=torch.long,
+            device=torch_device,
+        )
+        decoder_attention_mask = torch.where(decoder_input_ids == model.config.pad_token_id, 0, 1).to(torch_device)
+        generated_ids = model.generate(
+            input_ids=input_ids,
+            use_cache=False,
+            max_new_tokens=20,
+            decoder_input_ids=decoder_input_ids,
+            decoder_attention_mask=decoder_attention_mask,
+        )
+        generated_sentence = tokenizer.batch_decode(generated_ids)[0]
+        expected_sentence = "</s><pad><pad><pad><s>UN Chief Says There Is No Plan B for Peace in Syria</s>"
+        self.assertEqual(generated_sentence, expected_sentence)
+
 
 class BartStandaloneDecoderModelTester:
     def __init__(