config: read parallel config leaves via get_parallel() (#31816)

python/sglang/srt/batch_overlap/two_batch_overlap.py

@@ -43,7 +43,6 @@ from sglang.srt.runtime_context import (
     get_device,
     get_exec,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.speculative.spec_info import SpecInput
 from sglang.srt.utils import BumpAllocator, empty_context, get_bool_env_var, is_hip
@@ -762,7 +761,7 @@ class TboForwardBatchPreparer:
 
         # TODO improve, e.g. unify w/ `init_raw`
         if (
-            get_server_args().moe_dense_tp_size == 1
+            get_parallel().moe_dense_tp_size == 1
             and batch.global_dp_buffer_len is not None
         ):
             sum_len = end_token_index - start_token_index

python/sglang/srt/disaggregation/common/conn.py

@@ -572,7 +572,7 @@ class CommonKVManager(BaseKVManager):
         `Connection refused`, and the leader's `prefill_port_table` ends
         up missing rows.
         """
-        if not self.dist_init_addr or self.server_args.nnodes == 1:
+        if not self.dist_init_addr or get_parallel().nnodes == 1:
             return local_port
 
         if not (dist.is_available() and dist.is_initialized()):
@@ -624,7 +624,7 @@ class CommonKVManager(BaseKVManager):
             "rank_port": self.rank_port,
             "page_size": self.kv_args.page_size,
             "kv_cache_dtype": get_model().kv_cache_dtype,
-            "load_balance_method": self.server_args.load_balance_method,
+            "load_balance_method": get_parallel().load_balance_method,
             "enable_dsa_cache_layer_split": getattr(
                 self.server_args, "enable_dsa_cache_layer_split", False
             ),

python/sglang/srt/disaggregation/mooncake/conn.py

@@ -55,7 +55,7 @@ from sglang.srt.observability.trace import (
     TraceReqContext,
     trace_set_thread_info,
 )
-from sglang.srt.runtime_context import get_schedule
+from sglang.srt.runtime_context import get_parallel, get_schedule
 from sglang.srt.server_args import ServerArgs
 from sglang.srt.utils.network import NetworkAddress
 
@@ -948,7 +948,7 @@ class MooncakeKVManager(CommonKVManager):
         if (
             self.attn_cp_size > 1
             and self.attn_cp_rank != 0
-            and not self.server_args.enable_dsa_cache_layer_split
+            and not get_parallel().enable_dsa_cache_layer_split
         ):
             skip_state = True
 

python/sglang/srt/distributed/device_communicators/triton_symm_mem_ag.py

@@ -16,6 +16,8 @@ import torch.distributed._symmetric_memory as symm_mem
 import triton
 import triton.language as tl
 
+from sglang.srt.runtime_context import get_parallel
+
 logger = logging.getLogger(__name__)
 
 # Each thread moves _NUMEL_PER_THREAD bf16 via one 128-bit multimem op; the
@@ -466,7 +468,6 @@ class MultimemAllGatherer:
             # Lazy import avoids a module-load dependency on the distributed facade.
             from sglang.srt.distributed import get_tp_group
             from sglang.srt.distributed.parallel_state import in_the_same_node_as
-            from sglang.srt.runtime_context import get_server_args
 
             tp_group = get_tp_group()
             # Only probe node topology when the deployment can actually span
@@ -477,7 +478,7 @@ class MultimemAllGatherer:
             # EP/mooncake setups, and keep multimem enabled.
             if (
                 tp_group.world_size > 1
-                and get_server_args().nnodes > 1
+                and get_parallel().nnodes > 1
                 and not all(in_the_same_node_as(tp_group.cpu_group, source_rank=0))
             ):
                 logger.warning(

python/sglang/srt/entrypoints/engine.py

@@ -93,6 +93,7 @@ from sglang.srt.observability.trace import process_tracing_init, trace_set_threa
 from sglang.srt.parser.template_detection import resolve_auto_parsers
 from sglang.srt.parser.template_manager import TemplateManager
 from sglang.srt.plugins import load_plugins
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.server_args import PortArgs, ServerArgs
 from sglang.srt.utils import (
     MultiprocessingSerializer,
@@ -253,7 +254,7 @@ class Engine(EngineScoreMixin, EngineBase):
 
         # Initialize ZMQ sockets
         context = zmq.Context(2)
-        if self.server_args.node_rank == 0:
+        if server_args.node_rank == 0:
             self.send_to_rpc = get_zmq_socket(
                 context, zmq.DEALER, self.port_args.rpc_ipc_name, True
             )
@@ -301,7 +302,7 @@ class Engine(EngineScoreMixin, EngineBase):
                 routed_dp_rank = data_parallel_rank
 
         if routed_dp_rank is not None:
-            dp_size = self.server_args.dp_size
+            dp_size = get_parallel().dp_size
             if dp_size <= 1 and routed_dp_rank == 0:
                 logger.debug(
                     f"routed_dp_rank={routed_dp_rank} is ignored because dp_size={dp_size}"

python/sglang/srt/layers/attention/dsa/utils.py

@@ -12,7 +12,7 @@ from sglang.srt.model_executor.runner_backend_utils.breakable_cuda_graph import
 from sglang.srt.model_executor.runner_backend_utils.tc_piecewise_cuda_graph import (
     is_in_tc_piecewise_cuda_graph,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import get_bool_env_var, is_cuda, is_hip
 from sglang.srt.utils.common import ceil_align, ceil_div
 
@@ -76,20 +76,20 @@ def should_use_dsa_fused_topk(
 
 
 def is_dsa_enable_prefill_cp():
-    return get_server_args().enable_dsa_prefill_context_parallel
+    return get_parallel().enable_dsa_prefill_context_parallel
 
 
 def is_dsa_prefill_cp_in_seq_split():
     return (
         is_dsa_enable_prefill_cp()
-        and get_server_args().dsa_prefill_cp_mode == "in-seq-split"
+        and get_parallel().dsa_prefill_cp_mode == "in-seq-split"
     )
 
 
 def is_dsa_prefill_cp_round_robin_split():
     return (
         is_dsa_enable_prefill_cp()
-        and get_server_args().dsa_prefill_cp_mode == "round-robin-split"
+        and get_parallel().dsa_prefill_cp_mode == "round-robin-split"
     )
 
 

python/sglang/srt/layers/communicator.py

@@ -76,7 +76,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_spec,
 )
 from sglang.srt.speculative.spec_info import SpeculativeAlgorithm
@@ -271,7 +270,7 @@ class AttnTpContext:
     def init_context(self, q_lora_rank, is_dsa):
         self.is_dsa = is_dsa
         self.allow_input_scattered = (
-            get_server_args().enable_attn_tp_input_scattered
+            get_parallel().enable_attn_tp_input_scattered
             and (_is_cuda or _is_npu)
             and q_lora_rank is not None
             and not is_dsa
@@ -282,7 +281,7 @@ class AttnTpContext:
             and not check_cuda_graph_backend(Phase.PREFILL, Backend.TC_PIECEWISE)
             and get_spec().speculative_algorithm != "EAGLE3"
         )
-        if get_server_args().enable_attn_tp_input_scattered:
+        if get_parallel().enable_attn_tp_input_scattered:
             if not self.allow_input_scattered:
                 logging.info(
                     "attn_tp_input_scattered is not enabled while other conditions are not met"
@@ -440,11 +439,11 @@ class LayerScatterModes:
 
 
 def enable_moe_dense_fully_dp():
-    return get_server_args().moe_dense_tp_size == 1
+    return get_parallel().moe_dense_tp_size == 1
 
 
 def enable_dwdp():
-    return get_server_args().dwdp_size > 1
+    return get_parallel().dwdp_size > 1
 
 
 class LayerCommunicator:

python/sglang/srt/layers/logits_processor.py

@@ -47,7 +47,7 @@ from sglang.srt.model_executor.forward_batch_info import (
     ForwardBatch,
     ForwardMode,
 )
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_parallel
 from sglang.srt.utils.common import (
     is_cpu,
     is_npu,
@@ -345,7 +345,7 @@ class LogitsProcessor(nn.Module):
         self.config = config
         self.vocab_size = config.vocab_size
         self.logit_scale = logit_scale
-        self.use_attn_tp_group = get_server_args().enable_dp_lm_head
+        self.use_attn_tp_group = get_parallel().enable_dp_lm_head
         self.use_fp32_lm_head = get_exec().features.enable_fp32_lm_head
         if self.use_attn_tp_group:
             self.attn_tp_size = get_parallel().attn_tp_size

python/sglang/srt/layers/moe/token_dispatcher/nixl.py

@@ -23,6 +23,7 @@ from sglang.srt.layers.moe.token_dispatcher.deepep import (
 )
 from sglang.srt.layers.moe.topk import TopKOutput
 from sglang.srt.layers.moe.utils import DeepEPMode
+from sglang.srt.runtime_context import get_parallel
 
 try:
     from nixl_ep import Buffer
@@ -127,9 +128,7 @@ class NixlEPBuffer:
         offset = ElasticEPStateManager.get_ep_join_rank_offset()
         global_rank = rank + offset
 
-        from sglang.srt.runtime_context import get_server_args
-
-        max_ep_size = get_server_args().max_ep_size or world_size
+        max_ep_size = get_parallel().max_ep_size or world_size
         nixl_max_ranks = max_ep_size
 
         num_rdma_bytes = 0
@@ -226,9 +225,8 @@ class _NixlEPDispatcherImplBase:
             elastic_state.active_ranks if elastic_state is not None else None
         )
         self._active_world_size = dist.get_world_size(group)
-        from sglang.srt.runtime_context import get_server_args
 
-        _max_ep = get_server_args().max_ep_size or self._active_world_size
+        _max_ep = get_parallel().max_ep_size or self._active_world_size
         self._mask_buffer = (
             torch.zeros(_max_ep, dtype=torch.int32, device="cuda")
             if self.active_ranks is not None

python/sglang/srt/layers/utils/cp_utils.py

@@ -58,13 +58,13 @@ class ContextParallelMetadata:
 
 
 def is_prefill_context_parallel_enabled():
-    return get_server_args().enable_prefill_context_parallel
+    return get_parallel().enable_prefill_context_parallel
 
 
 def is_prefill_cp_in_seq_split():
     return (
         is_prefill_context_parallel_enabled()
-        and get_server_args().prefill_cp_mode == "in-seq-split"
+        and get_parallel().prefill_cp_mode == "in-seq-split"
     )
 
 

python/sglang/srt/managers/scheduler.py

@@ -1198,7 +1198,7 @@ class Scheduler(
                 gloo_group=self.attn_tp_cpu_group,
                 tp_rank=self.ps.tp_rank,
                 tp_size=self.ps.tp_size,
-                dp_size=self.server_args.dp_size,
+                dp_size=get_parallel().dp_size,
                 gpu_id=self.ps.gpu_id,
                 bootstrap_port=get_disagg().disaggregation_bootstrap_port,
                 max_total_num_tokens=self.max_total_num_tokens,
@@ -4313,7 +4313,7 @@ class Scheduler(
 
         old_ep_size = ElasticEPStateManager.get_effective_ep_size()
         new_ep_size = recv_req.new_ep_size
-        max_ep_size = self.server_args.max_ep_size or old_ep_size
+        max_ep_size = get_parallel().max_ep_size or old_ep_size
 
         logger.debug(
             "[Elastic EP][scale] request received: new_ep_size=%d "

python/sglang/srt/managers/scheduler_components/dp_attn.py

@@ -24,7 +24,7 @@ from sglang.srt.model_executor.cuda_graph_config import (
 )
 from sglang.srt.model_executor.forward_batch_info import ForwardMode
 from sglang.srt.observability.metrics_collector import DPCooperationInfo
-from sglang.srt.runtime_context import get_schedule
+from sglang.srt.runtime_context import get_parallel, get_schedule
 from sglang.srt.server_args import ServerArgs
 from sglang.srt.speculative.spec_info import SpeculativeAlgorithm
 from sglang.srt.utils.common import require_mlp_tp_gather
@@ -377,7 +377,7 @@ class SchedulerDPAttnAdapter:
     def prepare_mlp_sync_batch(self, local_batch: ScheduleBatch):
         return prepare_mlp_sync_batch_raw(
             local_batch,
-            dp_size=self.server_args.dp_size,
+            dp_size=get_parallel().dp_size,
             attn_tp_size=self.ps.attn_tp_size,
             attn_cp_size=self.ps.attn_cp_size,
             tp_group=self.tp_group,

python/sglang/srt/managers/scheduler_components/request_receiver.py

@@ -16,7 +16,7 @@ from sglang.srt.managers.io_struct import (
     sock_recv,
 )
 from sglang.srt.managers.mm_utils import has_shm_features, unwrap_shm_features
-from sglang.srt.runtime_context import get_disagg
+from sglang.srt.runtime_context import get_disagg, get_parallel
 from sglang.srt.utils import broadcast_pyobj, point_to_point_pyobj
 from sglang.srt.utils.nvtx_utils import scheduler_nvtx_method
 
@@ -127,7 +127,7 @@ class SchedulerRequestReceiver:
         return recv_reqs
 
     def _broadcast_reqs_across_ranks(self, recv_reqs: Optional[List]) -> List:
-        if self.server_args.enable_dp_attention:
+        if get_parallel().enable_dp_attention:
             if self.ps.attn_tp_rank == 0 and self.ps.attn_cp_rank == 0:
                 work_reqs, control_reqs = self._split_work_and_control_reqs(recv_reqs)
             else:
@@ -156,7 +156,7 @@ class SchedulerRequestReceiver:
             # instead of the full tp_group.  This avoids an expensive
             # all-ranks gloo sync.
             _local_ctrl = (
-                self.server_args.enable_dp_attention_local_control_broadcast
+                get_parallel().enable_dp_attention_local_control_broadcast
                 or self.server_args.is_ep_scale_joiner
             )
             if _local_ctrl:
@@ -233,7 +233,7 @@ class SchedulerRequestReceiver:
                 # peer ranks may still be unpickling ShmPointerMMData
                 # (-> shm_open).  Synchronize the same CPU groups that carried
                 # SHM-backed work requests before materialize() unlinks them.
-                if self.server_args.enable_dp_attention:
+                if get_parallel().enable_dp_attention:
                     if self.ps.attn_tp_size > 1:
                         barrier(group=self.attn_tp_cpu_group)
                     if self.ps.attn_cp_size > 1:

python/sglang/srt/managers/scheduler_pp_mixin.py

@@ -36,7 +36,7 @@ from sglang.srt.model_executor.forward_batch_info import (
     PPProxyTensors,
 )
 from sglang.srt.observability.req_time_stats import set_time_batch
-from sglang.srt.runtime_context import get_disagg
+from sglang.srt.runtime_context import get_disagg, get_parallel
 from sglang.srt.sampling.sampling_params import SamplingParams
 from sglang.srt.utils import DynamicGradMode, broadcast_pyobj, point_to_point_pyobj
 from sglang.srt.utils.common import get_device_module, is_xpu
@@ -123,7 +123,7 @@ class SchedulerPPMixin:
                 next_pp_outputs = None
                 next_batch_result = None
                 d2h_event = None
-                if self.server_args.pp_async_batch_depth > 0:
+                if get_parallel().pp_async_batch_depth > 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -139,7 +139,7 @@ class SchedulerPPMixin:
                         self.mb_metadata,
                         self.last_rank_comm_queue,
                     )
-                if self.server_args.pp_async_batch_depth == 0:
+                if get_parallel().pp_async_batch_depth == 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -269,7 +269,7 @@ class SchedulerPPMixin:
                     server_is_idle = False
                     pp_proxy_tensors = self._pp_recv_proxy_tensors()
 
-                if self.server_args.pp_async_batch_depth > 0:
+                if get_parallel().pp_async_batch_depth > 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -285,7 +285,7 @@ class SchedulerPPMixin:
                         self.mb_metadata,
                         self.last_rank_comm_queue,
                     )
-                if self.server_args.pp_async_batch_depth == 0:
+                if get_parallel().pp_async_batch_depth == 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -428,7 +428,7 @@ class SchedulerPPMixin:
                         pp_proxy_tensors = self._pp_recv_proxy_tensors()
 
                 # early send output if possible
-                if self.server_args.pp_async_batch_depth > 0:
+                if get_parallel().pp_async_batch_depth > 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -446,7 +446,7 @@ class SchedulerPPMixin:
                         self.last_rank_comm_queue,
                     )
 
-                if self.server_args.pp_async_batch_depth == 0:
+                if get_parallel().pp_async_batch_depth == 0:
                     next_pp_outputs, next_batch_result, d2h_event = (
                         self._pp_commit_send_output_work_and_preprocess_output_tensors(
                             next_first_rank_mb_id,
@@ -557,10 +557,10 @@ class SchedulerPPMixin:
                 self.on_idle()
 
     def init_pp_loop_state(self: Scheduler):
-        self.pp_loop_size: int = self.ps.pp_size + self.server_args.pp_async_batch_depth
+        self.pp_loop_size: int = self.ps.pp_size + get_parallel().pp_async_batch_depth
         # In CP mode, attention weights are duplicated, eliminating the need for the attention TP all-gather operation.
         self.require_attn_tp_allgather = (
-            not self.server_args.enable_dsa_prefill_context_parallel
+            not get_parallel().enable_dsa_prefill_context_parallel
         )
         self.mbs = [None] * self.pp_loop_size
         self.last_mbs = [None] * self.pp_loop_size

python/sglang/srt/managers/tokenizer_control_mixin.py

@@ -74,7 +74,7 @@ from sglang.srt.managers.io_struct import (
     UpdateWeightsFromTensorReqOutput,
 )
 from sglang.srt.managers.load_snapshot import LoadSnapshot
-from sglang.srt.runtime_context import get_lora
+from sglang.srt.runtime_context import get_lora, get_parallel
 from sglang.srt.server_args import LoRARef, ServerArgs
 from sglang.srt.utils import (
     get_bool_env_var,
@@ -146,8 +146,8 @@ class TokenizerControlMixin:
 
     def update_control_communicator_fan_out(self: TokenizerManager, worker_count: int):
         primary_group_control = (
-            self.server_args.enable_dp_attention
-            and not self.server_args.enable_dp_attention_local_control_broadcast
+            get_parallel().enable_dp_attention
+            and not get_parallel().enable_dp_attention_local_control_broadcast
         )
         if primary_group_control:
             control_fan_out = (
@@ -397,7 +397,7 @@ class TokenizerControlMixin:
     ) -> Tuple[bool, str]:
         self.auto_create_handle_loop()
         assert (
-            self.server_args.dp_size == 1 or self.server_args.enable_dp_attention
+            get_parallel().dp_size == 1 or get_parallel().enable_dp_attention
         ), "dp_size must be 1 or dp attention must be enabled for update weights from distributed"
 
         results = await self.init_weights_update_group_communicator(obj)
@@ -410,7 +410,7 @@ class TokenizerControlMixin:
     ) -> Tuple[bool, str]:
         self.auto_create_handle_loop()
         assert (
-            self.server_args.dp_size == 1 or self.server_args.enable_dp_attention
+            get_parallel().dp_size == 1 or get_parallel().enable_dp_attention
         ), "dp_size must be 1 or dp attention must be enabled for destroy parameter update group"
 
         results = await self.destroy_weights_update_group_communicator(obj)
@@ -423,7 +423,7 @@ class TokenizerControlMixin:
     ) -> Tuple[bool, str]:
         self.auto_create_handle_loop()
         assert (
-            self.server_args.dp_size == 1 or self.server_args.enable_dp_attention
+            get_parallel().dp_size == 1 or get_parallel().enable_dp_attention
         ), "dp_size must be 1 or dp attention must be enabled for update weights from distributed"
 
         if obj.abort_all_requests:
@@ -454,7 +454,7 @@ class TokenizerControlMixin:
         self.auto_create_handle_loop()
         # TODO: support DP
         assert (
-            self.server_args.dp_size == 1
+            get_parallel().dp_size == 1
         ), "dp_size must be 1 for init_weights_send_group_for_remote_instance"
         result = (
             await self.init_weights_send_group_for_remote_instance_communicator(obj)
@@ -469,7 +469,7 @@ class TokenizerControlMixin:
         self.auto_create_handle_loop()
         # TODO: support DP
         assert (
-            self.server_args.dp_size == 1
+            get_parallel().dp_size == 1
         ), "dp_size must be 1 for send_weights_to_remote_instance"
         result = (await self.send_weights_to_remote_instance_communicator(obj))[0]
         return result.success, result.message
@@ -481,7 +481,7 @@ class TokenizerControlMixin:
     ) -> Tuple[bool, str]:
         self.auto_create_handle_loop()
         assert (
-            self.server_args.dp_size == 1 or self.server_args.enable_dp_attention
+            get_parallel().dp_size == 1 or get_parallel().enable_dp_attention
         ), "dp_size must be 1 or dp attention must be enabled for update weights from tensor"
 
         if obj.abort_all_requests:
@@ -517,7 +517,7 @@ class TokenizerControlMixin:
         try:
             # For now, we only support single data parallel instance
             assert (
-                self.server_args.dp_size == 1 or self.server_args.enable_dp_attention
+                get_parallel().dp_size == 1 or get_parallel().enable_dp_attention
             ), "dp_size must be 1 or dp attention must be enabled for update weights from IPC"
             logger.info("Starting IPC weight update")
 
@@ -578,7 +578,7 @@ class TokenizerControlMixin:
             # TODO (lifuhuang): Remove this after we verify that dynamic lora loading works
             # with dp_size > 1.
             assert (
-                self.server_args.dp_size == 1
+                get_parallel().dp_size == 1
             ), "dp_size must be 1 for dynamic lora loading"
             logger.info(
                 "Start load Lora adapter. Lora name=%s, path=%s",
@@ -654,7 +654,7 @@ class TokenizerControlMixin:
                 )
 
             assert (
-                self.server_args.dp_size == 1
+                get_parallel().dp_size == 1
             ), "dp_size must be 1 for dynamic lora loading"
             logger.info(
                 "Start load Lora adapter from tensors. Lora name=%s",
@@ -730,7 +730,7 @@ class TokenizerControlMixin:
             # TODO (lifuhuang): Remove this after we verify that dynamic lora loading works
             # with dp_size > 1.
             assert (
-                self.server_args.dp_size == 1
+                get_parallel().dp_size == 1
             ), "dp_size must be 1 for dynamic lora loading"
             logger.info(
                 "Start unload Lora adapter. Lora name=%s",
@@ -750,7 +750,7 @@ class TokenizerControlMixin:
         self.auto_create_handle_loop()
         results = await self.get_weights_by_name_communicator(obj)
         all_parameters = [r.parameter for r in results]
-        if self.server_args.dp_size == 1:
+        if get_parallel().dp_size == 1:
             return all_parameters[0]
         else:
             return all_parameters

python/sglang/srt/managers/tokenizer_manager.py

@@ -116,6 +116,7 @@ from sglang.srt.runtime_context import (
     get_lora,
     get_model,
     get_observability,
+    get_parallel,
     get_serving,
 )
 from sglang.srt.sampling.sampling_params import SamplingParams
@@ -1365,7 +1366,7 @@ class TokenizerManager(TokenizerControlMixin, TokenizerManagerScoreMixin):
         return batch_size > 0 and (
             self.server_args.enable_tokenizer_batch_encode
             or (
-                (not self.server_args.enable_dp_attention)
+                (not get_parallel().enable_dp_attention)
                 and (not self._batch_has_text(batch_size, requests))
             )
         )

python/sglang/srt/model_executor/model_runner.py

@@ -150,6 +150,7 @@ from sglang.srt.runtime_context import (
     get_global_dwdp_manager,
     get_lora,
     get_model,
+    get_parallel,
     get_schedule,
     set_global_dwdp_manager,
 )
@@ -392,12 +393,12 @@ class ModelRunner:
         is_scale_join = get_exec().moe.ep_join_mode == "scale"
         if is_scale_join:
             join_effective_ep_size = (
-                self.server_args.ep_join_rank_offset + self.ps.tp_size
+                get_parallel().ep_join_rank_offset + self.ps.tp_size
             )
             dist.barrier(group=self.tp_group.cpu_group)
             if self.ps.tp_rank == 0:
                 register_scale_cohort(
-                    self.server_args.ep_join_rank_offset,
+                    get_parallel().ep_join_rank_offset,
                     join_effective_ep_size,
                 )
             join_scale_process_group()
@@ -407,7 +408,7 @@ class ModelRunner:
         else:
             join_process_groups()
 
-        global_ep_rank = self.ps.tp_rank + self.server_args.ep_join_rank_offset
+        global_ep_rank = self.ps.tp_rank + get_parallel().ep_join_rank_offset
         broadcast_global_expert_location_metadata(
             model_config=self.model_config,
             moe_ep_rank=global_ep_rank,
@@ -441,9 +442,9 @@ class ModelRunner:
             new_dp_size=join_effective_ep_size,
             new_dp_rank=global_ep_rank,
         )
-        self.server_args.override(
-            "elastic_ep.scale_join", dp_size=join_effective_ep_size
-        )
+        from sglang.srt.runtime_context import get_context
+
+        get_context().override("elastic_ep.scale_join", dp_size=join_effective_ep_size)
         if self.eplb_manager is not None:
             self.eplb_manager.disable_rebalance(
                 "EPLB rebalance is disabled after elastic EP scale-up"
@@ -617,7 +618,7 @@ class ModelRunner:
         if self.is_draft_worker:
             return
         expert_rank = self.ps.moe_ep_rank + (
-            self.server_args.ep_join_rank_offset
+            get_parallel().ep_join_rank_offset
             if self.server_args.is_ep_scale_joiner
             else 0
         )
@@ -797,7 +798,7 @@ class ModelRunner:
             device=self.device,
             tp_group=(
                 self.attention_tp_group.cpu_group
-                if self.server_args.enable_dp_attention
+                if get_parallel().enable_dp_attention
                 else self.tp_group.cpu_group
             ),
             host_to_device_ratio=hisparse_cfg.host_to_device_ratio,
@@ -1608,7 +1609,7 @@ class ModelRunner:
         if added <= 0:
             return
 
-        initial_ep_size = self.server_args.elastic_ep_initial_size
+        initial_ep_size = get_parallel().elastic_ep_initial_size
         assert initial_ep_size is not None
         self.server_args.override("elastic_ep.scale", ep_size=effective_size)
 
@@ -1627,7 +1628,7 @@ class ModelRunner:
         set_global_expert_location_metadata(new_metadata, allow_overwrite=True)
 
     def _elastic_global_rank(self) -> int:
-        return self.ps.tp_rank + self.server_args.ep_join_rank_offset
+        return self.ps.tp_rank + get_parallel().ep_join_rank_offset
 
     def _report_elastic_scale_failure(self, error: str, effective_size: int) -> None:
         if self.ps.tp_rank != 0 or self.server_args.is_ep_scale_joiner:
@@ -1704,7 +1705,9 @@ class ModelRunner:
             new_dp_size=target_size,
             new_dp_rank=self._elastic_global_rank(),
         )
-        self.server_args.override("elastic_ep.scale", dp_size=target_size)
+        from sglang.srt.runtime_context import get_context
+
+        get_context().override("elastic_ep.scale", dp_size=target_size)
 
         ElasticEPStateManager.mark_syncing_new_world()
         self._elastic_scale_ready_barrier(

python/sglang/srt/model_executor/model_runner_components/remote_instance_weight_transporter.py

@@ -11,7 +11,7 @@ from sglang.srt.model_loader.remote_instance_weight_loader_utils import (
     RemoteInstanceWeightLoaderBackend,
     register_memory_region,
 )
-from sglang.srt.runtime_context import get_model
+from sglang.srt.runtime_context import get_model, get_parallel
 from sglang.srt.server_args import ServerArgs
 from sglang.srt.utils.network import NetworkAddress, get_local_ip_auto
 
@@ -76,11 +76,11 @@ class RemoteInstanceWeightTransporter:
         """
         import requests as http_requests
 
-        if self.server_args.dist_init_addr:
+        if get_parallel().dist_init_addr:
             # Multi-node: bootstrap server is on the head node (node_rank==0).
             # Derive host from dist_init_addr (shared across all nodes).
             bootstrap_host = (
-                NetworkAddress.parse(self.server_args.dist_init_addr).resolved().host
+                NetworkAddress.parse(get_parallel().dist_init_addr).resolved().host
             )
         else:
             bootstrap_host = "127.0.0.1"

python/sglang/srt/models/apertus.py

@@ -26,9 +26,7 @@ import torch
 from torch import nn
 from transformers import ApertusConfig
 
-from sglang.srt.distributed import (
-    get_pp_group,
-)
+from sglang.srt.distributed import get_pp_group
 from sglang.srt.layers.activation import XIELU
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import (
@@ -52,7 +50,7 @@ from sglang.srt.model_loader.weight_utils import (
     kv_cache_scales_loader,
     maybe_remap_kv_scale_name,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix, make_layers
 
 logger = logging.getLogger(__name__)
@@ -442,7 +440,7 @@ class ApertusForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.logits_processor = LogitsProcessor(config)
         self.pooler = Pooler(pooling_type=PoolingType.LAST, normalize=True)

python/sglang/srt/models/arcee.py

@@ -20,9 +20,7 @@ import torch
 from torch import nn
 from transformers import LlamaConfig
 
-from sglang.srt.distributed import (
-    get_pp_group,
-)
+from sglang.srt.distributed import get_pp_group
 from sglang.srt.layers.activation import get_act_fn
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import (
@@ -46,7 +44,7 @@ from sglang.srt.model_loader.weight_utils import (
     kv_cache_scales_loader,
     maybe_remap_kv_scale_name,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix, make_layers
 
 logger = logging.getLogger(__name__)
@@ -405,7 +403,7 @@ class ArceeForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         self.pooler = Pooler(pooling_type=PoolingType.LAST, normalize=True)

python/sglang/srt/models/bailing_moe.py

@@ -79,7 +79,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import add_prefix, is_cuda, is_non_idle_and_non_empty, make_layers
@@ -821,7 +820,7 @@ class BailingMoEForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/bailing_moe_linear.py

@@ -57,7 +57,6 @@ from sglang.srt.runtime_context import (
     get_device,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -1085,7 +1084,7 @@ class BailingMoELinearForCausalLM(nn.Module):
                     config.hidden_size,
                     params_dtype=torch.float32,
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                 )
             )
             self.logits_processor = LogitsProcessor(config)

python/sglang/srt/models/bailing_moe_nextn.py

@@ -42,7 +42,7 @@ from sglang.srt.models.bailing_moe_linear import (
     BailingMoeV2_5ForCausalLM,
 )
 from sglang.srt.models.utils import WeightsMapper
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import BumpAllocator, add_prefix
 
 LoraConfig = None
@@ -208,7 +208,7 @@ class BailingMoeForCausalLMNextN(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         if hasattr(self.config, "model_type") and config.model_type == "bailing_hybrid":

python/sglang/srt/models/deepseek_nextn.py

@@ -62,7 +62,6 @@ from sglang.srt.models.utils import WeightsMapper
 from sglang.srt.runtime_context import (
     get_model,
     get_parallel,
-    get_server_args,
     get_spec,
 )
 from sglang.srt.utils import BumpAllocator, add_prefix, is_cuda, is_npu
@@ -381,7 +380,7 @@ class DeepseekV3ForCausalLMNextN(DeepseekV3ForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/deepseek_v2.py

@@ -2719,7 +2719,7 @@ class DeepseekV2ForCausalLM(nn.Module, DeepseekV2WeightLoaderMixin):
                     config.hidden_size,
                     quant_config=quant_config,
                     prefix=add_prefix("lm_head", prefix),
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                 )
         else:
             # ranks other than the last rank will have a placeholder layer

python/sglang/srt/models/deepseek_v4.py

@@ -134,7 +134,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 
 if not _is_hip:
@@ -2404,7 +2403,7 @@ class DeepseekV4ForCausalLM(nn.Module):
                     config.hidden_size,
                     quant_config=quant_config,
                     prefix=add_prefix("lm_head", prefix),
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                 )
         else:
             self.lm_head = PPMissingLayer()

python/sglang/srt/models/deepseek_v4_nextn.py

@@ -38,7 +38,7 @@ from sglang.srt.layers.vocab_parallel_embedding import (
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.model_executor.forward_context import get_attn_backend
 from sglang.srt.models.deepseek_v4 import DeepseekV4DecoderLayer, DeepseekV4ForCausalLM
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix
 
 logger = logging.getLogger(__name__)
@@ -233,7 +233,7 @@ class DeepseekV4ForCausalLMNextN(DeepseekV4ForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/exaone4.py

@@ -28,7 +28,7 @@ from sglang.srt.model_loader.weight_utils import (
     default_weight_loader,
     maybe_remap_kv_scale_name,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix, make_layers
 from sglang.utils import get_exception_traceback, logger
 
@@ -439,7 +439,7 @@ class Exaone4ForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
 
         self.logits_processor = LogitsProcessor(config)

python/sglang/srt/models/exaone_moe.py

@@ -60,7 +60,6 @@ from sglang.srt.model_loader.weight_utils import default_weight_loader
 from sglang.srt.runtime_context import (
     get_exec,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import LazyValue, add_prefix, is_cuda, make_layers
@@ -643,7 +642,7 @@ class ExaoneMoEForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.logits_processor = LogitsProcessor(config)
         # For EAGLE3 support

python/sglang/srt/models/exaone_moe_mtp.py

@@ -30,7 +30,7 @@ from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.vocab_parallel_embedding import ParallelLMHead
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.models.exaone_moe import ExaoneMoEForCausalLM, ExaoneMoEModel
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix
 
 logger = logging.getLogger(__name__)
@@ -63,7 +63,7 @@ class ExaoneMoEForCausalLMMTP(ExaoneMoEForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/falcon_h1.py

@@ -13,9 +13,7 @@ from sglang.srt.layers.attention.hybrid_linear_attn_backend import (
 )
 from sglang.srt.layers.attention.mamba.mamba import MambaMixer2
 from sglang.srt.layers.communicator import LayerCommunicator, LayerScatterModes
-from sglang.srt.layers.dp_attention import (
-    is_dp_attention_enabled,
-)
+from sglang.srt.layers.dp_attention import is_dp_attention_enabled
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import (
     MergedColumnParallelLinear,
@@ -36,7 +34,6 @@ from sglang.srt.model_loader.weight_utils import default_weight_loader
 from sglang.srt.runtime_context import (
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import add_prefix, is_cuda, make_layers
@@ -477,7 +474,7 @@ class FalconH1ForCausalLM(nn.Module):
                 quant_config=quant_config,
                 org_num_embeddings=config.vocab_size,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.lm_head = self.lm_head.float()
         self.lm_head_multiplier = config.lm_head_multiplier

python/sglang/srt/models/glm4_moe.py

@@ -87,7 +87,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -1171,7 +1170,7 @@ class Glm4MoeForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/glm4_moe_lite.py

@@ -78,7 +78,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -908,7 +907,7 @@ class Glm4MoeLiteForCausalLM(nn.Module, DeepseekV2WeightLoaderMixin):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/glm4_moe_lite_nextn.py

@@ -35,7 +35,7 @@ from sglang.srt.models.glm4_moe_lite import (
     Glm4MoeLiteDecoderLayer,
     Glm4MoeLiteForCausalLM,
 )
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args, get_spec
+from sglang.srt.runtime_context import get_exec, get_parallel, get_spec
 from sglang.srt.utils import BumpAllocator, add_prefix, is_npu
 
 logger = logging.getLogger(__name__)
@@ -151,7 +151,7 @@ class Glm4MoeLiteForCausalLMNextN(Glm4MoeLiteForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/glm4_moe_nextn.py

@@ -32,7 +32,7 @@ from sglang.srt.layers.vocab_parallel_embedding import (
 )
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.models.glm4_moe import Glm4MoeDecoderLayer, Glm4MoeForCausalLM
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args, get_spec
+from sglang.srt.runtime_context import get_exec, get_parallel, get_spec
 from sglang.srt.utils import add_prefix, is_npu
 
 logger = logging.getLogger(__name__)
@@ -137,7 +137,7 @@ class Glm4MoeForCausalLMNextN(Glm4MoeForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/glm4v_moe.py

@@ -18,7 +18,7 @@ from sglang.srt.layers.vocab_parallel_embedding import ParallelLMHead
 from sglang.srt.model_loader.weight_utils import default_weight_loader
 from sglang.srt.models.glm4_moe import Glm4MoeModel
 from sglang.srt.models.glm4v import Glm4vForConditionalGeneration, Glm4vVisionModel
-from sglang.srt.runtime_context import get_exec, get_mm, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_mm, get_parallel
 from sglang.srt.utils import add_prefix, get_device_sm, is_cuda, log_info_on_rank0
 from sglang.srt.utils.hf_transformers_utils import get_processor
 
@@ -69,7 +69,7 @@ class Glm4vMoeForConditionalGeneration(Glm4vForConditionalGeneration):
                     config.hidden_size,
                     quant_config=quant_config,
                     prefix=add_prefix("lm_head", prefix),
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                 )
         else:
             # ranks other than the last rank will have a placeholder layer

python/sglang/srt/models/glm_ocr_nextn.py

@@ -33,7 +33,7 @@ from sglang.srt.layers.vocab_parallel_embedding import (
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.models.glm4 import Glm4DecoderLayer
 from sglang.srt.models.glm_ocr import GlmOcrForConditionalGeneration
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_parallel
 from sglang.srt.utils import add_prefix
 
 logger = logging.getLogger(__name__)
@@ -134,7 +134,7 @@ class GlmOcrForConditionalGenerationNextN(GlmOcrForConditionalGeneration):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/gpt_oss.py

@@ -70,7 +70,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import (
     LazyValue,
@@ -257,7 +256,7 @@ class GptOssSparseMoeBlock(nn.Module):
         hidden_states: torch.Tensor,
         forward_batch: Optional[ForwardBatch] = None,
     ) -> torch.Tensor:
-        if get_server_args().dwdp_size > 1:
+        if get_parallel().dwdp_size > 1:
             return self.forward_dwdp(hidden_states)
 
         if not get_moe_a2a_backend().is_deepep():
@@ -775,7 +774,7 @@ class GptOssForCausalLM(nn.Module):
             config.hidden_size,
             # quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         self.capture_aux_hidden_states = False

python/sglang/srt/models/laguna.py

@@ -49,7 +49,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import LazyValue, add_prefix, make_layers
 
@@ -637,7 +636,7 @@ class LagunaForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         else:
             self.lm_head = PPMissingLayer()

python/sglang/srt/models/llada2.py

@@ -78,7 +78,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -828,7 +827,7 @@ class LLaDA2MoeModelLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.logits_processor = LogitsProcessor(config, return_full_logits=True)
 

python/sglang/srt/models/llama.py

@@ -25,10 +25,7 @@ import torch
 from torch import nn
 from transformers import LlamaConfig
 
-from sglang.srt.distributed import (
-    get_pp_group,
-    get_pp_indices,
-)
+from sglang.srt.distributed import get_pp_group, get_pp_indices
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import (
@@ -53,7 +50,7 @@ from sglang.srt.model_loader.weight_utils import (
     maybe_remap_kv_scale_name,
 )
 from sglang.srt.platforms import current_platform
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix, is_cuda, is_npu, is_xpu, make_layers
 from sglang.utils import get_exception_traceback
 
@@ -530,7 +527,7 @@ class LlamaForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         self.logits_processor = LogitsProcessor(config)
         self.pooler = Pooler(pooling_type=PoolingType.LAST, normalize=True)

python/sglang/srt/models/longcat_flash.py

@@ -41,17 +41,13 @@ from sglang.jit_kernel.dsv4 import linear_bf16_fp32
 from sglang.kernels.ops.moe.ep_moe_kernels import zero_experts_compute_triton
 from sglang.kernels.ops.quantization.fp8_kernel import is_fp8_fnuz
 from sglang.srt.configs import LongcatFlashConfig
-from sglang.srt.distributed import (
-    tensor_model_parallel_all_reduce,
-)
+from sglang.srt.distributed import tensor_model_parallel_all_reduce
 from sglang.srt.eplb.expert_distribution import get_global_expert_distribution_recorder
 from sglang.srt.eplb.expert_location import ModelConfigForExpertLocation
 from sglang.srt.layers import deep_gemm_wrapper
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.communicator import LayerCommunicator, LayerScatterModes
-from sglang.srt.layers.dp_attention import (
-    is_dp_attention_enabled,
-)
+from sglang.srt.layers.dp_attention import is_dp_attention_enabled
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import (
     MergedColumnParallelLinear,
@@ -87,7 +83,7 @@ from sglang.srt.model_loader.utils import (
 )
 from sglang.srt.model_loader.weight_utils import default_weight_loader
 from sglang.srt.models.deepseek_v2 import DeepseekV2AttentionMLA
-from sglang.srt.runtime_context import get_parallel, get_server_args, get_stream
+from sglang.srt.runtime_context import get_parallel, get_stream
 from sglang.srt.utils import (
     BumpAllocator,
     add_prefix,
@@ -714,7 +710,7 @@ class LongcatFlashForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         self.capture_aux_hidden_states = False

python/sglang/srt/models/mellum.py

@@ -51,7 +51,7 @@ from sglang.srt.models.utils import (
     create_fused_set_kv_buffer_arg,
     enable_fused_set_kv_buffer,
 )
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_parallel
 from sglang.srt.utils import add_prefix, is_cuda
 
 _is_cuda = is_cuda()
@@ -520,7 +520,7 @@ class MellumForCausalLM(Qwen3MoeForCausalLM):
             cfg.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(cfg)
         self.capture_aux_hidden_states = False

python/sglang/srt/models/mimo_v2.py

@@ -77,7 +77,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import (
     LazyValue,
@@ -1187,7 +1186,7 @@ class MiMoV2ForCausalLM(nn.Module, AudioEncoderMixin):
                     config.hidden_size,
                     quant_config=quant_config,
                     prefix=add_prefix("lm_head", prefix),
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                 )
             else:
                 self.lm_head = PPMissingLayer()

python/sglang/srt/models/mimo_v2_nextn.py

@@ -26,9 +26,7 @@ from sglang.srt.layers.communicator import (
     LayerScatterModes,
     enable_moe_dense_fully_dp,
 )
-from sglang.srt.layers.dp_attention import (
-    is_dp_attention_enabled,
-)
+from sglang.srt.layers.dp_attention import is_dp_attention_enabled
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.logits_processor import LogitsProcessor
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
@@ -44,7 +42,7 @@ from sglang.srt.models.mimo_v2 import (
     MiMoV2MLP,
     load_mimo_v2_qkv_proj_weight,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix
 
 MiMoV2Config = None
@@ -259,7 +257,7 @@ class MiMoV2MTP(MiMoV2ForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/minimax_m3.py

@@ -76,7 +76,7 @@ from sglang.srt.model_loader.weight_utils import (
     maybe_remap_kv_scale_name,
 )
 from sglang.srt.models.minimax_m2 import MiniMaxM2RMSNormTP
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_parallel
 from sglang.srt.utils import (
     add_prefix,
     get_device_sm,
@@ -1438,7 +1438,7 @@ class MiniMaxM3SparseForCausalLM(nn.Module):
                 config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
 
             self.logits_processor = LogitsProcessor(config)

python/sglang/srt/models/minimax_m3_vl.py

@@ -105,7 +105,7 @@ class MiniMaxM3SparseForConditionalGeneration(nn.Module):
                 text_config.hidden_size,
                 quant_config=quant_config,
                 prefix=add_prefix("language_model.lm_head", prefix),
-                use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                use_attn_tp_group=get_parallel().enable_dp_lm_head,
             )
         else:
             self.lm_head = PPMissingLayer()

python/sglang/srt/models/nemotron_h.py

@@ -90,7 +90,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import (
     add_prefix,
@@ -939,7 +938,7 @@ class NemotronHForCausalLM(nn.Module):
                         else lora_config.lora_vocab_padding_size
                     ),
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                     prefix=add_prefix("lm_head", prefix),
                 )
         else:

python/sglang/srt/models/nemotron_h_mtp.py

@@ -19,10 +19,7 @@ from torch import nn
 
 from sglang.srt.configs import NemotronHConfig
 from sglang.srt.distributed import get_pp_group
-from sglang.srt.layers.dp_attention import (
-    attn_tp_all_reduce,
-    is_dp_attention_enabled,
-)
+from sglang.srt.layers.dp_attention import attn_tp_all_reduce, is_dp_attention_enabled
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.linear import ColumnParallelLinear
 from sglang.srt.layers.logits_processor import LogitsProcessor
@@ -38,7 +35,7 @@ from sglang.srt.models.nemotron_h import (
     NemotronHMoEDecoderLayer,
 )
 from sglang.srt.models.nemotron_h_utils import is_attn_layer
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix
 
 
@@ -338,7 +335,7 @@ class NemotronHForCausalLMMTP(NemotronHForCausalLM):
             self.config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
 
         self.logits_processor = LogitsProcessor(config)

python/sglang/srt/models/qwen2_moe.py

@@ -93,7 +93,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import (
     add_prefix,
@@ -1011,7 +1010,7 @@ class Qwen2MoeForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         # For EAGLE3 support

python/sglang/srt/models/qwen3.py

@@ -34,7 +34,6 @@ from sglang.srt.models.utils import apply_qk_norm
 from sglang.srt.runtime_context import (
     get_exec,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import add_prefix, get_bool_env_var, is_cuda, is_hip, is_npu
@@ -495,7 +494,7 @@ class Qwen3ForCausalLM(nn.Module):
                     config.vocab_size,
                     config.hidden_size,
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                     prefix=add_prefix("lm_head", prefix),
                 )
         else:

python/sglang/srt/models/qwen3_moe.py

@@ -76,7 +76,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -956,7 +955,7 @@ class Qwen3MoeForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         self.capture_aux_hidden_states = False

python/sglang/srt/models/qwen3_moe_mtp.py

@@ -30,7 +30,7 @@ from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.vocab_parallel_embedding import ParallelLMHead
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.models.qwen3_moe import Qwen3MoeForCausalLM, Qwen3MoeModel
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import add_prefix
 
 logger = logging.getLogger(__name__)
@@ -63,7 +63,7 @@ class Qwen3MoeForCausalLMMTP(Qwen3MoeForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/qwen3_next.py

@@ -15,9 +15,7 @@ from sglang.srt.eplb.expert_distribution import get_global_expert_distribution_r
 from sglang.srt.eplb.expert_location import ModelConfigForExpertLocation
 from sglang.srt.layers.attention.mamba.mamba import mamba_v2_sharded_weight_loader
 from sglang.srt.layers.communicator import LayerCommunicator, LayerScatterModes
-from sglang.srt.layers.dp_attention import (
-    is_dp_attention_enabled,
-)
+from sglang.srt.layers.dp_attention import is_dp_attention_enabled
 from sglang.srt.layers.layernorm import GemmaRMSNorm
 from sglang.srt.layers.linear import (
     ColumnParallelLinear,
@@ -50,7 +48,6 @@ from sglang.srt.models.qwen2_moe import Qwen2MoeMLP, Qwen2MoeSparseMoeBlock
 from sglang.srt.runtime_context import (
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import (
@@ -831,9 +828,7 @@ class Qwen3HybridAttentionDecoderLayer(nn.Module):
 
         if self.attn_output_gate:
             if _is_hip:
-                from sglang.jit_kernel.triton.sigmoid_gate_mul import (
-                    sigmoid_gate_mul,
-                )
+                from sglang.jit_kernel.triton.sigmoid_gate_mul import sigmoid_gate_mul
 
                 attn_output = sigmoid_gate_mul(attn_output, gate)
             else:
@@ -1030,7 +1025,7 @@ class Qwen3NextForCausalLM(nn.Module):
             quant_config=quant_config,
             org_num_embeddings=config.vocab_size,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         # For EAGLE3 support

python/sglang/srt/models/qwen3_next_mtp.py

@@ -35,7 +35,6 @@ from sglang.srt.models.qwen3_next import Qwen3NextForCausalLM, Qwen3NextModel
 from sglang.srt.runtime_context import (
     get_model,
     get_parallel,
-    get_server_args,
     get_spec,
 )
 from sglang.srt.utils import add_prefix, is_npu
@@ -85,7 +84,7 @@ class Qwen3NextForCausalLMMTP(Qwen3NextForCausalLM):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("model.shared_head.head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
         # Mirror Qwen3NextForCausalLM.__init__'s shared-expert fusion setup so

python/sglang/srt/models/qwen3_vl.py

@@ -68,7 +68,7 @@ from sglang.srt.models.utils import (
 )
 from sglang.srt.multimodal.mm_utils import run_dp_sharded_mrope_vision_model
 from sglang.srt.multimodal.vit_cuda_graph_runner import ViTCudaGraphRunner
-from sglang.srt.runtime_context import get_exec, get_mm, get_parallel, get_server_args
+from sglang.srt.runtime_context import get_exec, get_mm, get_parallel
 from sglang.srt.utils import add_prefix, cpu_has_amx_support, is_cpu, is_npu, round_up
 from sglang.srt.utils.hf_transformers_utils import get_processor
 
@@ -1269,7 +1269,7 @@ class Qwen3VLForConditionalGeneration(nn.Module):
                         self.config.vocab_size,
                         self.config.hidden_size,
                         quant_config=quant_config,
-                        use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                        use_attn_tp_group=get_parallel().enable_dp_lm_head,
                         prefix=add_prefix("lm_head", prefix),
                     )
             else:

python/sglang/srt/models/sarvam_moe.py

@@ -1226,7 +1226,7 @@ class SarvamMLAForCausalLM(nn.Module):
             config.hidden_size,
             quant_config=quant_config,
             prefix=add_prefix("lm_head", prefix),
-            use_attn_tp_group=get_server_args().enable_dp_lm_head,
+            use_attn_tp_group=get_parallel().enable_dp_lm_head,
         )
         self.logits_processor = LogitsProcessor(config)
 

python/sglang/srt/models/sdar.py

@@ -43,7 +43,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import add_prefix, is_cuda, make_layers
@@ -473,7 +472,7 @@ class SDARForCausalLM(nn.Module):
                     config.vocab_size,
                     config.hidden_size,
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                     prefix=add_prefix("lm_head", prefix),
                 )
         else:

python/sglang/srt/models/sdar_moe.py

@@ -56,7 +56,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import LazyValue, add_prefix, is_cuda, make_layers
@@ -557,7 +556,7 @@ class SDARMoeForCausalLM(nn.Module):
                     config.vocab_size,
                     config.hidden_size,
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                     prefix=add_prefix("lm_head", prefix),
                 )
         else:

python/sglang/srt/models/step3p5.py

@@ -45,7 +45,6 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_forward,
     get_parallel,
-    get_server_args,
     get_stream,
 )
 from sglang.srt.utils import add_prefix, is_cuda, is_non_idle_and_non_empty, make_layers
@@ -817,7 +816,7 @@ class Step3p5ForCausalLM(nn.Module):
                     config.vocab_size,
                     config.hidden_size,
                     quant_config=quant_config,
-                    use_attn_tp_group=get_server_args().enable_dp_lm_head,
+                    use_attn_tp_group=get_parallel().enable_dp_lm_head,
                     prefix=add_prefix("lm_head", prefix),
                 )
         else:

python/sglang/srt/speculative/dspark_components/dspark_worker_v2.py

@@ -375,7 +375,7 @@ class DSparkWorkerV2(BaseSpecWorker):
         self, batch: ScheduleBatch, on_publish
     ) -> GenerationBatchResult:
         if batch.forward_mode.is_idle():
-            if self.server_args.enable_dp_attention:
+            if get_parallel().enable_dp_attention:
                 self.target_worker.forward_batch_generation(
                     batch, capture_hidden_mode=CaptureHiddenMode.FULL
                 )
@@ -443,7 +443,7 @@ class DSparkWorkerV2(BaseSpecWorker):
     def _dp_verify_tier_num_tokens(self, batch: ScheduleBatch) -> Optional[int]:
         if not (
             self._draft_is_moe
-            and self.server_args.enable_dp_attention
+            and get_parallel().enable_dp_attention
             and batch.global_num_tokens is not None
             and self._verify_planner.is_compact_mode
         ):
@@ -487,7 +487,7 @@ class DSparkWorkerV2(BaseSpecWorker):
 
         if batch.forward_mode.is_idle():
             self._observers.note_idle_decode_step()
-            if self.server_args.enable_dp_attention:
+            if get_parallel().enable_dp_attention:
                 if self._draft_is_moe:
                     self._proposer.run_idle_participation(batch)
                 self._verify_executor.run_idle_participation(
@@ -549,7 +549,7 @@ class DSparkWorkerV2(BaseSpecWorker):
         global_num_reqs = (
             max(batch.global_num_tokens)
             if self._draft_is_moe
-            and self.server_args.enable_dp_attention
+            and get_parallel().enable_dp_attention
             and batch.global_num_tokens is not None
             else None
         )