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[bugfix] dep ineffective (#4417)

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### What this PR does / why we need it?
The expert mapping table and weights of the dynamic EPLB were not
updated, causing the accuracy to be correct but not effective. This bug
has now been fixed.

- vLLM version: v0.11.2
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.2

---------

Signed-off-by: shenchuxiaofugui <1311027364@qq.com>
This commit is contained in:
LI SHENGYONG
2025-11-29 15:18:29 +08:00
committed by GitHub
parent 8ebbf13c1a
commit 0151022ab8
3 changed files with 5 additions and 5 deletions
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6
vllm_ascend/eplb/adaptor/vllm_adaptor.py
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@@ -194,15 +194,15 @@ class VllmEplbAdaptor(EplbAdaptor):
json.dump(record, f, indent=4)
def do_update_expert_map(self, layer_id, updated_expert_map):
self.expert_map_per_layer[layer_id] = updated_expert_map.clone()
self.expert_map_per_layer_cpu[layer_id] = updated_expert_map.clone()
self.expert_map_per_layer[layer_id].copy_(updated_expert_map)
self.expert_map_per_layer_cpu[layer_id].copy_(updated_expert_map)
def do_update_expert_weight(self, layer_id, local_expert_to_replace,
buffer_tensor_id):
for expert_tensor, buffer_tensor in zip(
self.expert_param_per_layer[layer_id][local_expert_to_replace],
self.buffer_tensor_list[buffer_tensor_id]):
expert_tensor = buffer_tensor.clone()
expert_tensor.copy_(buffer_tensor)
logger.debug(f"Expert tensor shape is :{expert_tensor.shape}")
def do_update_log2phy_map(self, layer_id, updated_log2phy_map):