[BUGFIX]Fix Qwen-Omni models audio max_token_per_item estimation error leading...

[BUGFIX]Fix Qwen-Omni models audio max_token_per_item estimation error leading to encoder_cache_size is 0 (#35994)
Signed-off-by: Miao, Avery <avery.miao@intel.com>

vllm/model_executor/models/qwen2_5_omni_thinker.py

@@ -353,6 +353,39 @@ class Qwen2_5OmniThinkerProcessingInfo(
     def get_supported_mm_limits(self) -> Mapping[str, int | None]:
         return {"audio": None, "image": None, "video": None}
 
+    def get_mm_max_tokens_per_item(
+        self,
+        seq_len: int,
+        mm_counts: Mapping[str, int] | None = None,
+    ) -> Mapping[str, int] | None:
+        mm_counts = mm_counts or {}
+        requested_modalities = {m for m, c in mm_counts.items() if c > 0}
+        mm_max_tokens: dict[str, int] = {}
+
+        if requested_modalities & {"image", "video"}:
+            vl_tokens = Qwen2_5_VLProcessingInfo.get_mm_max_tokens_per_item(
+                self,
+                seq_len=seq_len,
+                mm_counts=mm_counts,
+            )
+            mm_max_tokens.update(
+                {
+                    m: vl_tokens[m]
+                    for m in ["image", "video"]
+                    if m in requested_modalities
+                }
+            )
+
+        if "audio" in requested_modalities:
+            audio_tokens = Qwen2AudioProcessingInfo.get_mm_max_tokens_per_item(
+                self,
+                seq_len=seq_len,
+                mm_counts=mm_counts,
+            )
+            mm_max_tokens["audio"] = audio_tokens["audio"]
+
+        return mm_max_tokens
+
 
 class Qwen2_5OmniThinkerDummyInputsBuilder(
     BaseDummyInputsBuilder[Qwen2_5OmniThinkerProcessingInfo]

vllm/model_executor/models/qwen2_audio.py

@@ -179,6 +179,26 @@ class Qwen2AudioProcessingInfo(BaseProcessingInfo):
     def get_supported_mm_limits(self) -> Mapping[str, int | None]:
         return {"audio": None}
 
+    def get_mm_max_tokens_per_item(
+        self,
+        seq_len: int,
+        mm_counts: Mapping[str, int] | None = None,
+    ) -> Mapping[str, int]:
+        mm_counts = mm_counts or {}
+        if mm_counts.get("audio", 0) <= 0:
+            return {}
+
+        feature_extractor = self.get_feature_extractor()
+        chunk_length = min(feature_extractor.chunk_length, 30)
+        audio_len = int(chunk_length * feature_extractor.sampling_rate)
+        hop_length = feature_extractor.hop_length
+        max_mel_seq_len = audio_len // hop_length
+
+        input_lengths = torch.tensor([max_mel_seq_len], dtype=torch.long)
+        _, output_lengths = _get_feat_extract_output_lengths(input_lengths)
+
+        return {"audio": int(output_lengths.item())}
+
 
 class Qwen2AudioDummyInputsBuilder(BaseDummyInputsBuilder[Qwen2AudioProcessingInfo]):
     def get_dummy_text(self, mm_counts: Mapping[str, int]) -> str:

vllm/model_executor/models/qwen3_omni_moe_thinker.py

@@ -1163,6 +1163,39 @@ class Qwen3OmniMoeThinkerProcessingInfo(
     def get_supported_mm_limits(self) -> Mapping[str, int | None]:
         return {"audio": None, "image": None, "video": None}
 
+    def get_mm_max_tokens_per_item(
+        self,
+        seq_len: int,
+        mm_counts: Mapping[str, int] | None = None,
+    ) -> Mapping[str, int] | None:
+        mm_counts = mm_counts or {}
+        requested_modalities = {m for m, c in mm_counts.items() if c > 0}
+        mm_max_tokens: dict[str, int] = {}
+
+        if requested_modalities & {"image", "video"}:
+            vl_tokens = Qwen2_5_VLProcessingInfo.get_mm_max_tokens_per_item(
+                self,
+                seq_len=seq_len,
+                mm_counts=mm_counts,
+            )
+            mm_max_tokens.update(
+                {
+                    m: vl_tokens[m]
+                    for m in ["image", "video"]
+                    if m in requested_modalities
+                }
+            )
+
+        if "audio" in requested_modalities:
+            audio_tokens = Qwen2AudioProcessingInfo.get_mm_max_tokens_per_item(
+                self,
+                seq_len=seq_len,
+                mm_counts=mm_counts,
+            )
+            mm_max_tokens["audio"] = audio_tokens["audio"]
+
+        return mm_max_tokens
+
 
 Qwen3OmniMoeThinkerDummyInputsBuilder = Qwen2_5OmniThinkerDummyInputsBuilder