Quick Fix: fix Qwen3-VL launch failure caused by MRotaryEmbedding arg (#10985)

python/sglang/srt/layers/rotary_embedding.py

@@ -1065,6 +1065,7 @@ class MRotaryEmbedding(RotaryEmbedding):
         positions: torch.Tensor,
         query: torch.Tensor,
         key: torch.Tensor,
+        fused_set_kv_buffer_arg: Optional[FusedSetKVBufferArg] = None,
     ) -> Tuple[torch.Tensor, torch.Tensor]:
         """PyTorch-native implementation equivalent to forward().
 
@@ -1075,6 +1076,9 @@ class MRotaryEmbedding(RotaryEmbedding):
             query: [num_tokens, num_heads * head_size]
             key: [num_tokens, num_kv_heads * head_size]
         """
+        assert (
+            fused_set_kv_buffer_arg is None
+        ), "save kv cache is not supported for MRotaryEmbedding."
         assert positions.ndim == 1 or positions.ndim == 2
 
         num_tokens = positions.shape[-1]

python/sglang/srt/models/qwen3_moe.py

@@ -51,7 +51,7 @@ from sglang.srt.layers.moe.fused_moe_triton.layer import FusedMoE
 from sglang.srt.layers.moe.topk import TopK
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
-from sglang.srt.layers.rotary_embedding import get_rope
+from sglang.srt.layers.rotary_embedding import MRotaryEmbedding, get_rope
 from sglang.srt.layers.utils import get_layer_id
 from sglang.srt.layers.vocab_parallel_embedding import ParallelLMHead
 from sglang.srt.managers.schedule_batch import global_server_args_dict
@@ -358,6 +358,10 @@ class Qwen3MoeAttention(nn.Module):
             rope_scaling=rope_scaling,
             dual_chunk_attention_config=dual_chunk_attention_config,
         )
+        self.compatible_with_fused_kv_buffer = (
+            False if isinstance(self.rotary_emb, MRotaryEmbedding) else True
+        )
+
         self.attn = RadixAttention(
             self.num_heads,
             self.head_dim,
@@ -427,6 +431,7 @@ class Qwen3MoeAttention(nn.Module):
                     forward_batch=forward_batch,
                 )
                 if enable_fused_set_kv_buffer(forward_batch)
+                and self.compatible_with_fused_kv_buffer
                 else None
             ),
         )
@@ -439,7 +444,10 @@ class Qwen3MoeAttention(nn.Module):
             return hidden_states
         attn_output = self.attn(
             *inner_state,
-            save_kv_cache=not enable_fused_set_kv_buffer(forward_batch),
+            save_kv_cache=not (
+                enable_fused_set_kv_buffer(forward_batch)
+                and self.compatible_with_fused_kv_buffer
+            ),
         )
         output, _ = self.o_proj(attn_output)
         return output