[Qwen3.5] Fix broken pipeline parallelism layer splitting (#21070)

Co-authored-by: Alison Shao <alison.shao@Mac.attlocal.net>

python/sglang/srt/models/qwen3_5.py

@@ -29,7 +29,7 @@ from sglang.srt.configs.qwen3_5 import (
 )
 
 # Distributed
-from sglang.srt.distributed import get_pp_group, get_pp_indices
+from sglang.srt.distributed import get_pp_group
 from sglang.srt.eplb.expert_distribution import get_global_expert_distribution_recorder
 from sglang.srt.eplb.expert_location import ModelConfigForExpertLocation
 
@@ -721,25 +721,14 @@ class Qwen3_5ForCausalLM(nn.Module):
                 is_nextn=is_nextn,
             )
 
-        self.layers = make_layers(
+        self.layers, self._start_layer, self._end_layer = make_layers(
             config.num_hidden_layers,
             get_layer,
+            pp_rank=self.pp_group.rank_in_group,
+            pp_size=self.pp_group.world_size,
             prefix=f"{prefix}.layers",
         )
 
-        pp_rank = self.pp_group.rank_in_group
-        pp_size = self.pp_group.world_size
-        num_layers = config.num_hidden_layers
-        self._start_layer, self._end_layer = (
-            get_pp_indices(
-                num_layers,
-                pp_rank,
-                pp_size,
-            )
-            if pp_rank is not None and pp_size is not None
-            else (0, num_layers)
-        )
-
         # Final normalization
         if self.pp_group.is_last_rank:
             self.norm = GemmaRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
@@ -945,6 +934,8 @@ class Qwen3_5MoeForCausalLM(Qwen3_5ForCausalLM):
             shard_id: str,
             num_experts: int,
         ):
+            if name not in params_dict:
+                return False
             param = params_dict[name]
             weight_loader = param.weight_loader
             # let ep moe layer to gracefully handle expert_ids that do not belong to local moe rank
@@ -1270,6 +1261,8 @@ class Qwen3_5MoeForConditionalGeneration(Qwen3VLForConditionalGeneration):
             shard_id: str,
             num_experts: int,
         ):
+            if name not in params_dict:
+                return False
             param = params_dict[name]
             weight_loader = param.weight_loader
             # let ep moe layer to gracefully handle expert_ids that do not belong to local moe rank