Fix global scaling factor loading hang (#13484)

This commit is contained in:
Shu Wang
2025-11-21 18:07:06 -06:00
committed by GitHub
parent 1b48e1b974
commit a56f770277
2 changed files with 19 additions and 10 deletions

View File

@@ -284,9 +284,19 @@ class ExpertLocationMetadata:
# -------------------------------- usage ------------------------------------
def logical_to_all_physical(
self, layer_id: int, logical_expert_id: int
self,
layer_id: int,
logical_expert_id: int,
require_global_experts: bool = False,
) -> List[int]:
# Use CPU copy to avoid GPU→CPU sync on every call, which is expensive in update weights scenario
if require_global_experts:
num_physical_experts = self.logical_to_all_physical_map_cpu[layer_id].shape[
-1
]
return list(
range(logical_expert_id, num_physical_experts, self.num_logical_experts)
)
return [
physical_expert_id
for physical_expert_id in self.logical_to_all_physical_map_cpu[
@@ -355,14 +365,10 @@ def _compute_logical_to_all_physical_map(
)
# Replace by the nearest physical expert
mapped_physical_experts = logical_to_all_physical_map[layer_id][
logical_expert_id
]
if (
nearest_expert != -1
and nearest_expert not in mapped_physical_experts
):
mapped_physical_experts[0] = nearest_expert
if nearest_expert != -1:
logical_to_all_physical_map[layer_id][logical_expert_id] = [
nearest_expert
]
logical_to_all_physical_map = _pad_nested_array(
logical_to_all_physical_map, pad_value=-1

View File

@@ -548,9 +548,12 @@ class FusedMoE(torch.nn.Module):
# This is a shared expert.
physical_expert_ids = [expert_id]
else:
require_global_experts = getattr(
param, "_sglang_require_global_experts", False
)
physical_expert_ids = (
global_expert_location_metadata.logical_to_all_physical(
self.layer_id, expert_id
self.layer_id, expert_id, require_global_experts
)
)