[Spec] Support logprobs with DFlash (#33459)

python/sglang/srt/managers/scheduler.py

@@ -2442,7 +2442,11 @@ class Scheduler(
         self._maybe_namespace_elastic_radix_cache(req)
 
         if self.spec_algorithm.is_dflash_family():
-            error_msg = validate_dflash_request(req, self.enable_overlap)
+            error_msg = (
+                "DSpark speculative decoding does not support return_logprob yet."
+                if self.spec_algorithm.is_dspark() and req.return_logprob
+                else validate_dflash_request(req, self.enable_overlap)
+            )
             if error_msg is not None:
                 req.set_finish_with_abort(error_msg)
                 self.init_req_max_new_tokens(req)

python/sglang/srt/speculative/dflash_utils.py

@@ -841,9 +841,6 @@ def build_dflash_verify_target_probs(
 
 
 def validate_dflash_request(req: Req, enable_overlap: bool) -> Optional[str]:
-    if req.return_logprob:
-        return "DFLASH speculative decoding does not support return_logprob yet."
-
     if enable_overlap and req.return_hidden_states:
         return "DFLASH speculative decoding does not support return_hidden_states yet."
 

python/sglang/srt/speculative/dflash_worker_v2.py

@@ -17,6 +17,7 @@ from sglang.srt.configs.hybrid_arch import mambaish_config
 from sglang.srt.distributed import get_tp_group
 from sglang.srt.distributed.parallel_state_wrapper import ParallelState
 from sglang.srt.environ import envs
+from sglang.srt.layers.logprob_processor import compute_spec_v2_logprobs
 from sglang.srt.managers.schedule_batch import ScheduleBatch
 from sglang.srt.managers.scheduler import GenerationBatchResult
 from sglang.srt.managers.tp_worker import TpModelWorker
@@ -1383,10 +1384,6 @@ class DFlashWorkerV2(BaseSpecWorker):
         on_publish=None,
         grammar_barrier=None,
     ) -> GenerationBatchResult:
-        if getattr(batch, "return_logprob", False):
-            raise ValueError(
-                "DFLASH speculative decoding does not support return_logprob yet."
-            )
         self._validate_phase1_sampling_support(batch)
 
         if batch.forward_mode.is_extend() or batch.is_extend_in_batch:
@@ -1835,6 +1832,18 @@ class DFlashWorkerV2(BaseSpecWorker):
             # accept_len; recompute it from the forced commit_lens.
             new_seq_lens = None
 
+        if batch.return_logprob:
+            output_indices = torch.arange(
+                bs * block_size, dtype=torch.int64, device=device
+            ).view(bs, block_size)
+            compute_spec_v2_logprobs(
+                batch,
+                logits_output,
+                out_tokens.reshape(-1),
+                output_indices,
+                block_size - 1,
+            )
+
         if self._need_mamba_verify_commit:
             assert seq_lens_pre_verify is not None
             self._update_target_mamba_state_after_verify(