Merge branch 'v0.15.1-dev-qwen2audio' into 'v0.15.1-dev'

invoke flash_attn in the Qwen2AudioEncoder (transformers)

See merge request dcutoolkit/deeplearing/vllm!508

vllm/model_executor/models/qwen2_audio.py

@@ -337,6 +337,7 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal, Supports
         self.quant_config = quant_config
 
         with self._mark_tower_model(vllm_config, "audio"):
+            config.audio_config._attn_implementation = "flash_attention_2"
             self.audio_tower = Qwen2AudioEncoder(config.audio_config)
             self.multi_modal_projector = Qwen2AudioMultiModalProjector(
                 config.audio_config.d_model, config.text_config.hidden_size
@@ -422,6 +423,9 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal, Supports
         )
         audio_attention_mask[audio_attention_mask_] = float("-inf")
 
+        attn_impl = getattr(self.audio_tower.config, "_attn_implementation", "eager")
+        if attn_impl in ("flash_attention_2", "flash_attention_3"):
+            audio_attention_mask = (~padding_mask).to(dtype=torch.int32)
         audio_outputs = self.audio_tower(
             input_features, attention_mask=audio_attention_mask
         )
@@ -473,4 +477,4 @@ class Qwen2AudioForConditionalGeneration(nn.Module, SupportsMultiModal, Supports
 
     def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
         loader = AutoWeightsLoader(self)
-        return loader.load_weights(weights)
+        return loader.load_weights(weights)
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