BART - Fix attention mask device issue on copied models (#18540)

* attempt to fix attn mask device

* fix bart `_prepare_decoder_attention_mask`

- add correct device
- run `make fix-copies` to propagate the fix

src/transformers/models/bart/modeling_bart.py

@@ -915,7 +915,9 @@ class BartDecoder(BartPretrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/bigbird_pegasus/modeling_bigbird_pegasus.py

@@ -2116,7 +2116,9 @@ class BigBirdPegasusDecoder(BigBirdPegasusPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/blenderbot/modeling_blenderbot.py

@@ -854,7 +854,9 @@ class BlenderbotDecoder(BlenderbotPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/blenderbot_small/modeling_blenderbot_small.py

@@ -850,7 +850,9 @@ class BlenderbotSmallDecoder(BlenderbotSmallPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/marian/modeling_marian.py

@@ -860,7 +860,9 @@ class MarianDecoder(MarianPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/mbart/modeling_mbart.py

@@ -913,7 +913,9 @@ class MBartDecoder(MBartPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/opt/modeling_opt.py

@@ -534,7 +534,9 @@ class OPTDecoder(OPTPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/pegasus/modeling_pegasus.py

@@ -880,7 +880,9 @@ class PegasusDecoder(PegasusPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )

src/transformers/models/plbart/modeling_plbart.py

@@ -887,7 +887,9 @@ class PLBartDecoder(PLBartPreTrainedModel):
 
         if attention_mask is not None:
             # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len]
-            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1])
+            expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to(
+                inputs_embeds.device
+            )
             combined_attention_mask = (
                 expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
             )