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

src/transformers/generation/utils.py

@@ -666,6 +666,9 @@ class GenerationMixin:
                 expand_size, dim=0
             )
             model_kwargs["encoder_outputs"] = encoder_outputs
+            decoder_attention_mask = model_kwargs.get("decoder_attention_mask")
+            if decoder_attention_mask is not None:
+                model_kwargs["decoder_attention_mask"] = decoder_attention_mask.repeat_interleave(expand_size, dim=0)
 
         return input_ids, model_kwargs
 
@@ -701,13 +704,21 @@ class GenerationMixin:
             token_type_ids = model_kwargs["token_type_ids"]
             model_kwargs["token_type_ids"] = torch.cat([token_type_ids, token_type_ids[:, -1].unsqueeze(-1)], dim=-1)
 
-        # update attention mask
         if not is_encoder_decoder:
+            # update attention mask
             if "attention_mask" in model_kwargs:
                 attention_mask = model_kwargs["attention_mask"]
                 model_kwargs["attention_mask"] = torch.cat(
                     [attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1
                 )
+        else:
+            # update decoder attention mask
+            if "decoder_attention_mask" in model_kwargs:
+                decoder_attention_mask = model_kwargs["decoder_attention_mask"]
+                model_kwargs["decoder_attention_mask"] = torch.cat(
+                    [decoder_attention_mask, decoder_attention_mask.new_ones((decoder_attention_mask.shape[0], 1))],
+                    dim=-1,
+                )
 
         return model_kwargs
 

src/transformers/models/bart/modeling_bart.py

@@ -1420,6 +1420,7 @@ class BartForConditionalGeneration(BartPretrainedModel):
         decoder_input_ids,
         past=None,
         attention_mask=None,
+        decoder_attention_mask=None,
         head_mask=None,
         decoder_head_mask=None,
         cross_attn_head_mask=None,
@@ -1437,6 +1438,7 @@ class BartForConditionalGeneration(BartPretrainedModel):
             "past_key_values": past,
             "decoder_input_ids": decoder_input_ids,
             "attention_mask": attention_mask,
+            "decoder_attention_mask": decoder_attention_mask,
             "head_mask": head_mask,
             "decoder_head_mask": decoder_head_mask,
             "cross_attn_head_mask": cross_attn_head_mask,

src/transformers/models/bigbird_pegasus/modeling_bigbird_pegasus.py

@@ -2619,6 +2619,7 @@ class BigBirdPegasusForConditionalGeneration(BigBirdPegasusPreTrainedModel):
         decoder_input_ids,
         past=None,
         attention_mask=None,
+        decoder_attention_mask=None,
         head_mask=None,
         decoder_head_mask=None,
         cross_attn_head_mask=None,
@@ -2636,6 +2637,7 @@ class BigBirdPegasusForConditionalGeneration(BigBirdPegasusPreTrainedModel):
             "past_key_values": past,
             "decoder_input_ids": decoder_input_ids,
             "attention_mask": attention_mask,
+            "decoder_attention_mask": decoder_attention_mask,
             "head_mask": head_mask,
             "decoder_head_mask": decoder_head_mask,
             "cross_attn_head_mask": cross_attn_head_mask,

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__(