Add draft extend CUDA graph for Triton backend (#6705)

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

@@ -128,6 +128,7 @@ class TritonAttnBackend(AttentionBackend):
             )
 
         self.num_draft_tokens = model_runner.server_args.speculative_num_draft_tokens
+        self.speculative_num_steps = model_runner.server_args.speculative_num_steps
 
         self.num_head = (
             model_runner.model_config.num_attention_heads // get_attention_tp_size()
@@ -424,6 +425,34 @@ class TritonAttnBackend(AttentionBackend):
             num_kv_splits = None
             attn_logits = None
             attn_lse = None
+        elif forward_mode.is_draft_extend():
+            num_tokens_per_bs = self.speculative_num_steps + 1
+            qo_indptr = self.qo_indptr[: bs + 1]
+            qo_indptr[: bs + 1] = torch.arange(
+                0,
+                bs * num_tokens_per_bs + 1,
+                step=num_tokens_per_bs,
+                dtype=torch.int32,
+                device=self.device,
+            )
+            kv_indptr = self.kv_indptr[: bs + 1]
+            kv_indptr[1 : bs + 1] = torch.cumsum(seq_lens, dim=0)
+            kv_indices = self.cuda_graph_kv_indices
+            create_flashinfer_kv_indices_triton[(bs,)](
+                self.req_to_token,
+                req_pool_indices,
+                seq_lens,
+                kv_indptr,
+                None,
+                kv_indices,
+                self.req_to_token.stride(0),
+            )
+            custom_mask = None
+            mask_indptr = None
+            max_extend_len = num_tokens_per_bs
+            num_kv_splits = None
+            attn_logits = None
+            attn_lse = None
         else:
             raise ValueError(
                 f"Invalid forward mode: {forward_mode=} for CUDA Graph capture."
@@ -504,6 +533,23 @@ class TritonAttnBackend(AttentionBackend):
             seq_mask_len = self.num_draft_tokens * (seq_lens + self.num_draft_tokens)
             mask_indptr = self.mask_indptr[: bs + 1]
             mask_indptr[1 : bs + 1] = torch.cumsum(seq_mask_len, dim=0)
+        elif forward_mode.is_draft_extend():
+            seq_lens = seq_lens[:bs]
+            accept_lens = spec_info.accept_length[:bs]
+            qo_indptr = self.qo_indptr[: bs + 1]
+            qo_indptr[1 : bs + 1] = torch.cumsum(accept_lens, dim=0)
+            kv_indptr = self.kv_indptr[: bs + 1]
+            kv_indptr[1 : bs + 1] = torch.cumsum(seq_lens, dim=0)
+            kv_indices = self.cuda_graph_kv_indices
+            create_flashinfer_kv_indices_triton[(bs,)](
+                self.req_to_token,
+                req_pool_indices,
+                seq_lens,
+                kv_indptr,
+                None,
+                kv_indices,
+                self.req_to_token.stride(0),
+            )
         else:
             raise ValueError(
                 f"Invalid forward mode: {forward_mode=} for CUDA Graph replay."

python/sglang/srt/speculative/eagle_worker.py

@@ -179,6 +179,7 @@ class EAGLEWorker(TpModelWorker):
             self.has_prefill_wrapper_verify = True
         elif self.server_args.attention_backend == "triton":
             from sglang.srt.layers.attention.triton_backend import (
+                TritonAttnBackend,
                 TritonMultiStepDraftBackend,
             )
 
@@ -187,7 +188,10 @@ class EAGLEWorker(TpModelWorker):
                 self.topk,
                 self.speculative_num_steps,
             )
-            self.draft_extend_attn_backend = None
+            self.draft_extend_attn_backend = TritonAttnBackend(
+                self.draft_model_runner,
+                skip_prefill=False,
+            )
             self.padded_static_len = self.speculative_num_steps + 1
             self.has_prefill_wrapper_verify = False
         elif self.server_args.attention_backend == "fa3":