Tiny fix mimo model conflicts with main (#15483)

python/sglang/srt/managers/scheduler.py

@@ -494,7 +494,7 @@ class Scheduler(
                     tp_rank=self.tp_rank,
                     moe_ep_rank=self.moe_ep_rank,
                     server_args=self.server_args,
-                    nccl_port=self.port_args.nccl_port,
+                    nccl_port=self.nccl_port,
                     target_worker=self.tp_worker,
                     dp_rank=self.dp_rank,
                 )
@@ -506,7 +506,7 @@ class Scheduler(
                     tp_rank=self.tp_rank,
                     moe_ep_rank=self.moe_ep_rank,
                     server_args=self.server_args,
-                    nccl_port=self.port_args.nccl_port,
+                    nccl_port=self.nccl_port,
                     target_worker=self.tp_worker,
                     dp_rank=self.dp_rank,
                 )

python/sglang/srt/speculative/mtp_worker_v2.py

@@ -14,7 +14,7 @@
 
 import contextlib
 import logging
-from typing import List, Optional, Tuple
+from typing import TYPE_CHECKING, List, Optional, Tuple
 
 import torch
 
@@ -48,6 +48,10 @@ from sglang.srt.speculative.spec_utils import (
 )
 from sglang.srt.utils.common import empty_context, fast_topk, next_power_of_2
 
+if TYPE_CHECKING:
+    from sglang.srt.model_executor.model_runner import ModelRunnerOutput
+
+
 logger = logging.getLogger(__name__)
 
 
@@ -376,8 +380,10 @@ class MTPDraftWorker(BaseDraftWorker):
         topk_p_list = []
         topk_index_list = []
         for step in range(self.speculative_num_steps):
-            logits_output, _ = self.draft_runner_list[step].forward(forward_batch)
+            output: ModelRunnerOutput = self.draft_runner_list[step].forward(
-            probs = torch.softmax(logits_output.next_token_logits, dim=-1)
+                forward_batch
+            )
+            probs = torch.softmax(output.logits_output.next_token_logits, dim=-1)
             topk_p, topk_index = fast_topk(probs, self.topk, dim=-1)
             topk_p_list.append(topk_p)
             topk_index_list.append(topk_index)
@@ -390,7 +396,6 @@ class MTPDraftWorker(BaseDraftWorker):
                 )
         next_draft_input.topk_p = torch.cat(topk_p_list, dim=1)
         next_draft_input.topk_index = torch.cat(topk_index_list, dim=1)
-        # next_draft_input.hidden_states = logits_output.hidden_states
 
         # Update req_to_hidden_states_pool for KV Cache reversion
         if forward_batch.extend_seq_lens is not None: