[6/N] MoE Refactor: Cleanup MoE-related configs (#8849)

python/sglang/srt/managers/schedule_batch.py

@@ -52,6 +52,7 @@ from sglang.srt.disaggregation.decode_schedule_batch_mixin import (
     ScheduleBatchDisaggregationDecodeMixin,
 )
 from sglang.srt.distributed.parallel_state import get_tensor_model_parallel_rank
+from sglang.srt.layers.moe import is_tbo_enabled
 from sglang.srt.mem_cache.allocator import (
     BaseTokenToKVPoolAllocator,
     SWATokenToKVPoolAllocator,
@@ -84,17 +85,10 @@ GLOBAL_SERVER_ARGS_KEYS = [
     "device",
     "disable_chunked_prefix_cache",
     "disable_radix_cache",
-    "enable_two_batch_overlap",
-    "tbo_token_distribution_threshold",
     "enable_dp_lm_head",
-    "moe_a2a_backend",
-    "deepep_mode",
-    "enable_flashinfer_cutlass_moe",
-    "enable_flashinfer_trtllm_moe",
     "enable_flashinfer_allreduce_fusion",
     "moe_dense_tp_size",
     "ep_dispatch_algorithm",
-    "deepep_config",
     "ep_num_redundant_experts",
     "enable_nan_detection",
     "flashinfer_mla_disable_ragged",
@@ -107,8 +101,6 @@ GLOBAL_SERVER_ARGS_KEYS = [
     "triton_attention_reduce_in_fp32",
     "num_reserved_decode_tokens",
     "weight_loader_disable_mmap",
-    "enable_triton_kernel_moe",
-    "enable_flashinfer_mxfp4_moe",
     "enable_multimodal",
     "enable_symm_mem",
     "quantization",

python/sglang/srt/managers/scheduler.py

@@ -64,7 +64,7 @@ from sglang.srt.hf_transformers_utils import (
 )
 from sglang.srt.layers.dp_attention import compute_dp_attention_world_info
 from sglang.srt.layers.logits_processor import LogitsProcessorOutput
-from sglang.srt.layers.moe.utils import DeepEPMode, MoeA2ABackend
+from sglang.srt.layers.moe import initialize_moe_config
 from sglang.srt.managers.io_struct import (
     AbortReq,
     CloseSessionReqInput,
@@ -245,6 +245,9 @@ class Scheduler(
             )
         )
 
+        # Init model config
+        self.model_config = ModelConfig.from_server_args(server_args)
+
         # Init inter-process communication
         context = zmq.Context(2)
         self.idle_sleeper = None
@@ -292,6 +295,9 @@ class Scheduler(
         # Init tokenizer
         self.init_tokenizer()
 
+        # Init moe config
+        self.init_moe_config()
+
         # Set reasoning_parser and think_end_id if --reasoning_parser is enabled
         if self.server_args.reasoning_parser and self.tokenizer:
             reasoning_parser = ReasoningParser(
@@ -538,8 +544,6 @@ class Scheduler(
 
     def init_tokenizer(self):
         server_args = self.server_args
-
-        self.model_config = ModelConfig.from_server_args(server_args)
         self.is_generation = self.model_config.is_generation
 
         if server_args.skip_tokenizer_init:
@@ -761,6 +765,10 @@ class Scheduler(
             # The prefill requests that are in the middle of kv sending
             self.disagg_prefill_inflight_queue: List[Req] = []
 
+    def init_moe_config(self):
+        if hasattr(self.model_config.hf_config, "num_experts_per_tok"):
+            initialize_moe_config(self.server_args)
+
     @DynamicGradMode()
     def event_loop_normal(self):
         """A normal scheduler loop."""
@@ -1823,11 +1831,6 @@ class Scheduler(
             disable_cuda_graph=self.server_args.disable_cuda_graph,
             spec_algorithm=self.spec_algorithm,
             speculative_num_draft_tokens=self.server_args.speculative_num_draft_tokens,
-            enable_two_batch_overlap=self.server_args.enable_two_batch_overlap,
-            enable_deepep_moe=MoeA2ABackend(
-                self.server_args.moe_a2a_backend
-            ).is_deepep(),
-            deepep_mode=DeepEPMode(self.server_args.deepep_mode),
             require_mlp_tp_gather=require_mlp_tp_gather(self.server_args),
             disable_overlap_schedule=self.server_args.disable_overlap_schedule,
         )
@@ -1922,9 +1925,6 @@ class Scheduler(
         disable_cuda_graph: bool,
         spec_algorithm,
         speculative_num_draft_tokens,
-        enable_two_batch_overlap: bool,
-        enable_deepep_moe: bool,
-        deepep_mode: DeepEPMode,
         require_mlp_tp_gather: bool,
         disable_overlap_schedule: bool,
     ):
@@ -1972,9 +1972,6 @@ class Scheduler(
                 is_extend_in_batch,
                 *tbo_preparer.prepare_all_gather(
                     local_batch,
-                    deepep_mode,
-                    enable_deepep_moe,
-                    enable_two_batch_overlap,
                 ),
             ],
             dtype=torch.int64,