Cleaning codes for speculative attention mode (#10149)

docs/advanced_features/server_arguments.md

@@ -209,6 +209,7 @@ Please consult the documentation below and [server_args.py](https://github.com/s
 | `--speculative-accept-threshold-single` | Accept a draft token if its probability in the target model is greater than this threshold. | 1.0 |
 | `--speculative-accept-threshold-acc` | The accept probability of a draft token is raised from its target probability p to min(1, p / threshold_acc). | 1.0 |
 | `--speculative-token-map` | The path of the draft model's small vocab table. | None |
+| `--speculative-attention-mode` | Attention backend for speculative decoding operations (both target verify and draft extend). Can be one of 'prefill' (default) or 'decode'. | Prefill |
 
 ## Expert parallelism
 

python/sglang/srt/layers/attention/hybrid_attn_backend.py

@@ -34,7 +34,7 @@ class HybridAttnBackend(AttentionBackend):
 
         Note:
             - decode_or_idle: Always uses decode backend
-            - target_verify or draft_extend: Uses decode backend if speculative_attention_backend is "decode", otherwise prefill backend
+            - target_verify or draft_extend: Uses decode backend if speculative_attention_mode is "decode", otherwise prefill backend
             - prefill: Always uses prefill backend
         """
         if forward_mode.is_decode_or_idle():
@@ -42,8 +42,7 @@ class HybridAttnBackend(AttentionBackend):
         elif forward_mode.is_target_verify() or forward_mode.is_draft_extend():
             return (
                 self.decode_backend
-                if self.model_runner.server_args.speculative_attention_backend
-                == "decode"
+                if self.model_runner.server_args.speculative_attention_mode == "decode"
                 else self.prefill_backend
             )
         else:
@@ -57,7 +56,7 @@ class HybridAttnBackend(AttentionBackend):
         self.decode_backend.init_cuda_graph_state(max_bs, max_num_tokens)
         if (
             self.model_runner.server_args.speculative_algorithm is not None
-            and self.model_runner.server_args.speculative_attention_backend == "prefill"
+            and self.model_runner.server_args.speculative_attention_mode == "prefill"
         ):
             # When speculative decoding is enabled, we need to initialize the backend
             # that will be used for target_verify.

python/sglang/srt/managers/schedule_batch.py

@@ -98,7 +98,7 @@ GLOBAL_SERVER_ARGS_KEYS = [
     "sampling_backend",
     "speculative_accept_threshold_single",
     "speculative_accept_threshold_acc",
-    "speculative_attention_backend",
+    "speculative_attention_mode",
     "torchao_config",
     "triton_attention_reduce_in_fp32",
     "num_reserved_decode_tokens",

python/sglang/srt/models/deepseek_v2.py

@@ -1050,7 +1050,7 @@ class DeepseekV2AttentionMLA(nn.Module):
             or forward_batch.forward_mode.is_draft_extend()
         ):
             # Use the specified backend for speculative operations (both verify and draft extend)
-            if global_server_args_dict["speculative_attention_backend"] == "decode":
+            if global_server_args_dict["speculative_attention_mode"] == "decode":
                 attention_backend = global_server_args_dict["decode_attention_backend"]
             else:  # default to prefill
                 attention_backend = global_server_args_dict["prefill_attention_backend"]

python/sglang/srt/server_args.py

@@ -262,7 +262,7 @@ class ServerArgs:
     speculative_accept_threshold_single: float = 1.0
     speculative_accept_threshold_acc: float = 1.0
     speculative_token_map: Optional[str] = None
-    speculative_attention_backend: str = "prefill"
+    speculative_attention_mode: str = "prefill"
 
     # Expert parallelism
     ep_size: int = 1
@@ -1563,11 +1563,11 @@ class ServerArgs:
             default=ServerArgs.speculative_token_map,
         )
         parser.add_argument(
-            "--speculative-attention-backend",
+            "--speculative-attention-mode",
             type=str,
             choices=["prefill", "decode"],
-            help="Attention backend to use for speculative decoding operations (both target verify and draft extend). 'prefill' (default) or 'decode'.",
-            default=ServerArgs.speculative_attention_backend,
+            help="Attention backend for speculative decoding operations (both target verify and draft extend). Can be one of 'prefill' (default) or 'decode'.",
+            default=ServerArgs.speculative_attention_mode,
         )
 
         # Expert parallelism

python/sglang/srt/speculative/eagle_worker.py

@@ -191,7 +191,7 @@ class EAGLEWorker(TpModelWorker):
         # Initialize decode attention backend
         self.draft_attn_backend = self._create_decode_backend()
 
-        # Initialize draft extend attention backend (respects speculative_attention_backend setting)
+        # Initialize draft extend attention backend (respects speculative_attention_mode setting)
         self.draft_extend_attn_backend = self._create_draft_extend_backend()
 
         self.draft_model_runner.draft_attn_backend = self.draft_attn_backend
@@ -236,7 +236,7 @@ class EAGLEWorker(TpModelWorker):
         }
         backend_name = (
             "decode_attention_backend"
-            if self.server_args.speculative_attention_backend == "decode"
+            if self.server_args.speculative_attention_mode == "decode"
             else "prefill_attention_backend"
         )
         return self._create_backend(

test/srt/test_hybrid_attn_backend.py

@@ -111,27 +111,6 @@ class TestHybridAttnBackendTorchCompile(TestHybridAttnBackendBase):
         return DEFAULT_SERVER_ARGS + ["--enable-torch-compile"]
 
 
-class TestHybridAttnBackendSpeculativeDecoding(TestHybridAttnBackendBase):
-    speculative_decode = True
-    # This eagle test uses a very small model, so the accuracy is low.
-    accuracy_threshold = 0.2
-
-    @classmethod
-    def get_server_args(cls):
-        return DEFAULT_SERVER_ARGS + [
-            "--speculative-algorithm",
-            "EAGLE",
-            "--speculative-draft-model-path",
-            DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST,
-            "--speculative-num-steps",
-            "3",
-            "--speculative-eagle-topk",
-            "2",
-            "--speculative-num-draft-tokens",
-            "4",
-        ]
-
-
 class TestHybridAttnBackendSpeculativeDecodingPrefillBackend(TestHybridAttnBackendBase):
     speculative_decode = True
     # This eagle test uses a very small model, so the accuracy is low.
@@ -150,7 +129,7 @@ class TestHybridAttnBackendSpeculativeDecodingPrefillBackend(TestHybridAttnBacke
             "2",
             "--speculative-num-draft-tokens",
             "4",
-            "--speculative-attention-backend",
+            "--speculative-attention-mode",
             "prefill",
         ]
 
@@ -173,7 +152,7 @@ class TestHybridAttnBackendSpeculativeDecodingDecodeBackend(TestHybridAttnBacken
             "2",
             "--speculative-num-draft-tokens",
             "4",
-            "--speculative-attention-backend",
+            "--speculative-attention-mode",
             "decode",
         ]