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fix unexcepted answer in EAGLE mode #9252

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merged 2 commits into from
Aug 17, 2025
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fix unexcepted answer in EAGLE mode #9252

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30fabfc
fix unexcepted answer in EAGLE mode
zyksir Aug 16, 2025
73311e3
format files
zyksir Aug 16, 2025
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21 changes: 16 additions & 5 deletions python/sglang/srt/speculative/eagle_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,11 +177,22 @@ def generate_attn_arg_prefill(
)
return kv_indices, cum_kv_seq_len, qo_indptr, None

def filter_batch(self, new_indices: torch.Tensor):
self.topk_p = self.topk_p[: len(new_indices)]
self.topk_index = self.topk_index[: len(new_indices)]
self.hidden_states = self.hidden_states[: len(new_indices)]
self.verified_id = self.verified_id[: len(new_indices)]
def filter_batch(self, new_indices: torch.Tensor, has_been_filtered: bool = True):
if has_been_filtered:
# in eagle_utils.py:verify, we have already filtered the batch by `unfinished_index`
# therefore, we don't need to filter the batch again in scheduler
if len(new_indices) != len(self.topk_p):
logger.warning(f"length of new_indices: {len(new_indices)} != length of topk_p: {len(self.topk_p)}, this should not happen")
self.topk_p = self.topk_p[: len(new_indices)]
self.topk_index = self.topk_index[: len(new_indices)]
self.hidden_states = self.hidden_states[: len(new_indices)]
self.verified_id = self.verified_id[: len(new_indices)]
else:
# in some cases(e.g draft_extend), we have not filtered the batch by `unfinished_index`
self.topk_p = self.topk_p[new_indices]
self.topk_index = self.topk_index[new_indices]
self.hidden_states = self.hidden_states[new_indices]
self.verified_id = self.verified_id[new_indices]

def merge_batch(self, spec_info: EagleDraftInput):
if self.hidden_states is None:
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11 changes: 11 additions & 0 deletions python/sglang/srt/speculative/eagle_worker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -836,6 +836,17 @@ def forward_draft_extend(
assert isinstance(forward_batch.spec_info, EagleDraftInput)
assert forward_batch.spec_info is batch.spec_info
self.capture_for_decode(logits_output, forward_batch.spec_info)
has_finished, unfinished_req_index = False, []
for i, req in enumerate(batch.reqs):
if req.finished():
has_finished = True
else:
unfinished_req_index.append(i)
if has_finished:
unfinished_index_device = torch.tensor(
unfinished_req_index, dtype=torch.int64, device=batch.spec_info.topk_p.device
)
batch.spec_info.filter_batch(unfinished_index_device, has_been_filtered=False)
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medium

This block of code for finding and filtering finished requests can be made more concise and Pythonic using a list comprehension. This improves readability and reduces the number of lines.

        unfinished_req_index = [
            i for i, req in enumerate(batch.reqs) if not req.finished()
        ]
        if len(unfinished_req_index) < len(batch.reqs):
            unfinished_index_device = torch.tensor(
                unfinished_req_index, dtype=torch.int64, device=batch.spec_info.topk_p.device
            )
            batch.spec_info.filter_batch(unfinished_index_device, has_been_filtered=False)


def forward_draft_extend_after_decode(self, batch: ScheduleBatch):
assert isinstance(batch.spec_info, EagleDraftInput)
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