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[misc] Drop redundant req_pool_indices_cpu guards; fold hisparse into GLM-5.1 e2e (#28607)

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Liangsheng Yin
2026-06-18 12:51:23 -07:00
committed by GitHub
parent 792cb3a5d0
commit 8f6d9ef9a5
4 changed files with 125 additions and 204 deletions
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python/sglang/srt/managers/schedule_batch.py
+2 -23
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@@ -2602,10 +2602,6 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
def prepare_for_decode(self):
self.forward_mode = ForwardMode.DECODE
bs = len(self.reqs)
if self.req_pool_indices_cpu is None and self.req_pool_indices is not None:
self.req_pool_indices_cpu = (
self.req_pool_indices.detach().cpu().to(dtype=torch.int64)
)
# Decode embeds the last output token via embed_tokens; clear the stale
# prefill-time tensor so it doesn't leak into ForwardBatch.
self.input_embeds = None
@@ -2699,17 +2695,9 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
]
if keep_indices is None or len(keep_indices) == 0:
# Filter out all requests
# Filter out all requests. Stale tensors are left as-is: is_empty()
# keys off reqs, so callers drop the batch before a forward reads them.
self.reqs = []
self.req_pool_indices = torch.empty(
0, dtype=torch.int64, device=self.device
)
self.req_pool_indices_cpu = torch.empty(0, dtype=torch.int64)
self.seq_lens = torch.empty(0, dtype=torch.int64, device=self.device)
self.seq_lens_cpu = torch.empty(0, dtype=torch.int64)
self.orig_seq_lens = torch.empty(0, dtype=torch.int32, device=self.device)
self.out_cache_loc = None
self.seq_lens_sum = 0
return
if len(keep_indices) == len(self.reqs):
@@ -2767,15 +2755,6 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
)
def merge_batch(self, other: ScheduleBatch):
if self.req_pool_indices_cpu is None and self.req_pool_indices is not None:
self.req_pool_indices_cpu = (
self.req_pool_indices.detach().cpu().to(dtype=torch.int64)
)
if other.req_pool_indices_cpu is None and other.req_pool_indices is not None:
other.req_pool_indices_cpu = (
other.req_pool_indices.detach().cpu().to(dtype=torch.int64)
)
# Penalizer orchestrator must be merged before Batch.reqs is merged. This is because
# orchestrator.merge() depends on Batch.reqs during preparation of each penalizers, so it
# needs to be called with pre-merged Batch.reqs.