[attention][DCP] use AttentionImpl.need_to_return_lse_for_decode (#24372)

Signed-off-by: youkaichao <youkaichao@gmail.com>

vllm/attention/backends/abstract.py

@@ -257,6 +257,32 @@ class AttentionLayer(Protocol):
 
 class AttentionImpl(ABC, Generic[T]):
 
+    # Whether the attention impl can return the softmax lse for decode.
+    # Some features like decode context parallelism require the softmax lse.
+    can_return_lse_for_decode: bool = False
+
+    # some attention backends might not always want to return lse
+    # even if they can return lse (for efficiency reasons)
+    need_to_return_lse_for_decode: bool = False
+
+    dcp_world_size: int
+    dcp_rank: int
+
+    def __new__(cls, *args, **kwargs):
+        # use __new__ so that all subclasses will call this
+        self = super().__new__(cls)
+        try:
+            from vllm.distributed.parallel_state import get_dcp_group
+            self.dcp_world_size = get_dcp_group().world_size
+            self.dcp_rank = get_dcp_group().rank_in_group
+        except AssertionError:
+            # DCP might not be initialized in testing
+            self.dcp_world_size = 1
+            self.dcp_rank = 0
+        self.need_to_return_lse_for_decode = self.dcp_world_size > 1 \
+            and self.can_return_lse_for_decode
+        return self
+
     @abstractmethod
     def __init__(
         self,

vllm/v1/attention/backends/mla/common.py

@@ -1592,10 +1592,6 @@ class MLACommonImpl(MLAAttentionImpl[M], Generic[M]):
 
             # recorect dcp attn_out with lse.
             if self.dcp_world_size > 1:
-                assert lse is not None, (
-                    "For a mla backend want to enable"
-                    "DCP, it is mandatory that the corresponding decode attn"
-                    "kernel return the softmax lse.")
                 attn_out = cp_lse_ag_out_rs(attn_out, lse, get_dcp_group())
 
             # v_up projection

vllm/v1/attention/backends/mla/flashmla.py

@@ -133,6 +133,8 @@ class FlashMLAMetadataBuilder(MLACommonMetadataBuilder[FlashMLAMetadata]):
 
 class FlashMLAImpl(MLACommonImpl[FlashMLAMetadata]):
 
+    can_return_lse_for_decode: bool = True
+
     def __init__(
             self,
             num_heads: int,

vllm/v1/worker/gpu_model_runner.py

@@ -56,7 +56,6 @@ from vllm.utils import (STR_DTYPE_TO_TORCH_DTYPE, DeviceMemoryProfiler,
                         GiB_bytes, LazyLoader, cdiv, check_use_alibi,
                         get_dtype_size, is_pin_memory_available, round_up,
                         supports_dynamo)
-from vllm.v1.attention.backends.mla.flashmla import FlashMLABackend
 from vllm.v1.attention.backends.utils import (
     AttentionCGSupport, AttentionMetadataBuilder, CommonAttentionMetadata,
     create_fast_prefill_custom_backend,
@@ -3405,10 +3404,16 @@ class GPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
                     copy_kv_blocks)
 
         if self.dcp_world_size > 1:
-            assert self.attn_groups[0][0].backend is FlashMLABackend, (
-                "DCP only support flashmla now."
-                "For a mla backend want to enable DCP, it is mandatory that the"
-                "corresponding decode attn kernel return the softmax lse.")
+            layer_names = self.attn_groups[0][0].layer_names
+            layers = get_layers_from_vllm_config(self.vllm_config,
+                                                 AttentionLayerBase,
+                                                 layer_names)
+            for layer in layers.values():
+                assert layer.impl.need_to_return_lse_for_decode, (
+                    "DCP requires attention impls to return"
+                    " the softmax lse for decode, but the impl "
+                    f"{layer.impl.__class__.__name__} "
+                    "does not return the softmax lse for decode.")
 
     def may_add_encoder_only_layers_to_kv_cache_config(self) -> None:
         """