config: business code no longer reads the published ServerArgs (#34081)

python/sglang/srt/hardware_backend/mlx/model_runner.py

@@ -49,7 +49,9 @@ from sglang.srt.hardware_backend.mlx.kv_cache import (
     uses_sliding_window_attention,
 )
 from sglang.srt.mem_cache.memory_pool import ReqToTokenPool
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import (
+    mamba_cache_chunk_size,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -281,7 +283,7 @@ class MlxModelRunner:
         ):
             return None
 
-        chunk_size = get_server_args().mamba_cache_chunk_size
+        chunk_size = mamba_cache_chunk_size()
         track_len = prefix_len + (new_token_count // chunk_size) * chunk_size
         branching_len = getattr(req, "mamba_branching_seqlen", None)
         if (

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

@@ -40,11 +40,11 @@ from sglang.srt.model_executor.runner_backend_utils.tc_piecewise_cuda_graph impo
     is_in_tc_piecewise_cuda_graph,
 )
 from sglang.srt.runtime_context import (
+    configured_pp_size,
     get_device,
     get_exec,
     get_parallel,
     get_schedule,
-    get_server_args,
 )
 from sglang.srt.state_capturer.indexer_topk import (
     maybe_capture_indexer_topk,
@@ -249,7 +249,7 @@ class Indexer(DSANPUIndexerMixin, BaseFusedOp):
         if _is_cuda:
             self.sm_count = deep_gemm.get_num_sms()
             self.half_device_sm_count = ceil_align(self.sm_count // 2, 8)
-            pp_size = get_server_args().pp_size
+            pp_size = configured_pp_size()
             self.logits_with_pp_recv = pp_size > 1 and not get_pp_group().is_last_rank
         else:
             self.logits_with_pp_recv = False

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

@@ -12,7 +12,10 @@ 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,
+    process_model_config,
+)
 from sglang.srt.utils import get_bool_env_var, is_cuda, is_hip
 from sglang.srt.utils.common import ceil_align, ceil_div
 
@@ -113,7 +116,7 @@ def is_dsa_enable_prefill_cp():
         return False
     from sglang.srt.configs.model_config import is_deepseek_dsa, is_deepseek_v4
 
-    hf_config = get_server_args().get_model_config().hf_config
+    hf_config = process_model_config().hf_config
     return is_deepseek_dsa(hf_config) or is_deepseek_v4(hf_config)
 
 

python/sglang/srt/layers/attention/hybrid_linear_attn_backend.py

@@ -25,7 +25,11 @@ from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.mem_cache.memory_pool import HybridReqToTokenPool
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
 from sglang.srt.model_executor.model_runner import ModelRunner
-from sglang.srt.runtime_context import get_exec, get_memory, get_server_args
+from sglang.srt.runtime_context import (
+    get_exec,
+    get_memory,
+    mamba_cache_chunk_size,
+)
 from sglang.srt.speculative.eagle_info import EagleDraftInput, EagleVerifyInput
 from sglang.srt.speculative.spec_info import SpecInput
 
@@ -297,8 +301,8 @@ class MambaAttnBackendBase(AttentionBackend):
         lens_to_track = (
             forward_batch.mamba_track_seqlens - forward_batch.extend_prefix_lens
         )
-        mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        chunk_size = mamba_cache_chunk_size()
-        aligned_len = (lens_to_track // mamba_cache_chunk_size) * mamba_cache_chunk_size
+        aligned_len = (lens_to_track // chunk_size) * chunk_size
         start_indices = query_start_loc[:-1] + aligned_len - conv_state_len
         start_indices = start_indices[forward_batch.mamba_track_mask]
 
@@ -316,7 +320,7 @@ class MambaAttnBackendBase(AttentionBackend):
         """src/dst indices to track SSM states for prefix caching: aligned seqs
         cache last_recurrent_state, unaligned cache intermediate `h` at the last
         chunk boundary."""
-        mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        chunk_size = mamba_cache_chunk_size()
         # CPU to avoid kernel launches for the masking ops
         mamba_track_mask = forward_batch.mamba_track_mask.cpu()
         extend_seq_lens = forward_batch.extend_seq_lens.cpu()
@@ -326,9 +330,9 @@ class MambaAttnBackendBase(AttentionBackend):
         prefix_lens = forward_batch.extend_prefix_lens.cpu()
 
         if isinstance(self, Mamba2AttnBackend):
-            num_h_states = extend_seq_lens // mamba_cache_chunk_size
+            num_h_states = extend_seq_lens // chunk_size
         else:
-            num_h_states = (extend_seq_lens - 1) // mamba_cache_chunk_size + 1
+            num_h_states = (extend_seq_lens - 1) // chunk_size + 1
 
         track_ssm_src_offset = torch.zeros_like(num_h_states)
         track_ssm_src_offset[1:] = torch.cumsum(num_h_states[:-1], dim=0)
@@ -338,17 +342,17 @@ class MambaAttnBackendBase(AttentionBackend):
         offset_masked = track_ssm_src_offset[mamba_track_mask]
         dst_masked = mamba_track_indices[mamba_track_mask]
 
-        is_aligned = (lens_masked % mamba_cache_chunk_size) == 0
+        is_aligned = (lens_masked % chunk_size) == 0
 
         # Aligned: last_recurrent_state from ssm_states.
         track_ssm_final_src = mamba_cache_indices[mamba_track_mask][is_aligned]
         track_ssm_final_dst = dst_masked[is_aligned]
 
         # Unaligned: intermediate state from h.
-        # TODO: handle mamba_cache_chunk_size % page size != 0
+        # TODO: handle chunk_size % page size != 0
         not_aligned = ~is_aligned
         track_ssm_h_src = offset_masked[not_aligned] + (
-            lens_masked[not_aligned] // mamba_cache_chunk_size
+            lens_masked[not_aligned] // chunk_size
         )
         track_ssm_h_dst = dst_masked[not_aligned]
 

python/sglang/srt/layers/attention/linear/inkling_sconv_backend.py

@@ -62,7 +62,11 @@ from sglang.srt.models.inkling_common.kernels.sconv import (
     fused_extend_sconv_metadata,
     precompute_helion_extend_metadata,
 )
-from sglang.srt.runtime_context import get_exec, get_server_args, get_spec
+from sglang.srt.runtime_context import (
+    get_exec,
+    get_spec,
+    mamba_cache_chunk_size,
+)
 from sglang.srt.speculative.eagle_info import EagleDraftExtendInput
 
 if TYPE_CHECKING:
@@ -99,7 +103,7 @@ class InklingShortConvAttnBackend(ShortConvAttnBackend):
         # [n_layers, n_slots, conv_kernel - 1, conv_dim].
         self._mamba_cache = self.req_to_token_pool.mamba_pool.mamba_cache
         self.conv_state_len: int = self.conv_states_shape[2]
-        self.mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        self.mamba_cache_chunk_size = mamba_cache_chunk_size()
         # A plain table lookup is recordable; the unified pool's translate is an
         # allocator lookup and must stay in the out-of-graph replay prep.
         self._slot_gather_recordable = (

python/sglang/srt/layers/attention/linear/kernels/gdn_flashinfer.py

@@ -19,7 +19,9 @@ import torch
 from sglang.srt.layers.attention.linear.kernels.kernel_backend import (
     LinearAttnKernelBase,
 )
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import (
+    mamba_cache_chunk_size,
+)
 from sglang.srt.utils import is_cuda
 
 if TYPE_CHECKING:
@@ -50,7 +52,7 @@ def maybe_build_flashinfer_checkpoint_plan(
     ):
         return
 
-    checkpoint_every_n_tokens = get_server_args().mamba_cache_chunk_size
+    checkpoint_every_n_tokens = mamba_cache_chunk_size()
     extend_seq_lens = forward_batch.extend_seq_lens.to(device="cpu", dtype=torch.int64)
     track_mask = forward_batch.mamba_track_mask.to(device="cpu", dtype=torch.bool)
     relative_track_lens = forward_batch.mamba_track_seqlens.to(

python/sglang/srt/layers/attention/linear/kernels/kda_ptx.py

@@ -37,6 +37,7 @@ from sglang.srt.layers.attention.linear.kernels.kda_triton import TritonKDAKerne
 from sglang.srt.layers.attention.linear.kernels.kernel_backend import (
     LinearAttnKernelBase,
 )
+from sglang.srt.runtime_context import mamba_cache_chunk_size
 
 logger = logging.getLogger(__name__)
 
@@ -194,11 +195,8 @@ class PtxKDAKernel(LinearAttnKernelBase):
             # which may be larger (for example 256 for Nemotron-H). Returning
             # the raw 64-token rows in that case would silently select the
             # wrong boundary and compute wrong offsets for later sequences.
-            from sglang.srt.runtime_context import get_server_args
 
-            intermediate_stride_supported = (
+            intermediate_stride_supported = mamba_cache_chunk_size() == _CHUNK
-                get_server_args().mamba_cache_chunk_size == _CHUNK
-            )
         seq_lens = (
             [int(length) for length in seq_lens_cpu] if seq_lens_cpu is not None else []
         )

python/sglang/srt/layers/attention/linear/lightning_backend.py

@@ -15,7 +15,10 @@ from sglang.srt.layers.attention.linear.linear_metadata import (
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.model_executor.model_runner import ModelRunner
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import (
+    get_parallel,
+    mamba_cache_chunk_size,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -299,7 +302,7 @@ class LightningAttentionBackend(MambaAttnBackendBase):
         if h_dst is None or h_dst.numel() == 0:
             return None, None
 
-        mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        chunk_size = mamba_cache_chunk_size()
         num_prefills = metadata.num_prefills
         track_mask = forward_batch.mamba_track_mask[:num_prefills]
         extend_lens = forward_batch.extend_seq_lens[:num_prefills]
@@ -307,9 +310,7 @@ class LightningAttentionBackend(MambaAttnBackendBase):
         track_seqlens = forward_batch.mamba_track_seqlens[:num_prefills]
 
         lens_to_track = track_seqlens - prefix_lens
-        boundary_lens = (
+        boundary_lens = (lens_to_track // chunk_size) * chunk_size
-            lens_to_track // mamba_cache_chunk_size
-        ) * mamba_cache_chunk_size
         track_rows = (track_mask & (boundary_lens < extend_lens)).nonzero(
             as_tuple=True
         )[0]

python/sglang/srt/layers/cp/base.py

@@ -230,12 +230,15 @@ class ContextParallelStrategy(ABC):
 
 
 def _is_dsa_active() -> bool:
-    from sglang.srt.runtime_context import get_server_args
+    from sglang.srt.runtime_context import get_parallel, get_server_args
 
-    sa = get_server_args()
+    # `_is_dsa_model_arch` is set nowhere in the tree, so this predicate is
+    # inert today (the getattr default makes it False). Kept verbatim rather
+    # than "fixed" here, because deciding what it should name is the CP path's
+    # call; the ratchet exempts it with that reason.
     return bool(
-        getattr(sa, "enable_prefill_cp", False)
+        get_parallel().enable_prefill_cp
-        and getattr(sa, "_is_dsa_model_arch", False)
+        and getattr(get_server_args(), "_is_dsa_model_arch", False)
     )
 
 
@@ -288,7 +291,7 @@ def get_cp_strategy() -> Optional[ContextParallelStrategy]:
             server_args = get_server_args()
         except ValueError:
             return None
-        if server_args is not None and getattr(server_args, "enable_prefill_cp", False):
+        if server_args is not None and get_parallel().enable_prefill_cp:
             init_cp_strategy(server_args)
     return _STRATEGY
 

python/sglang/srt/layers/dp_attention.py

@@ -27,7 +27,11 @@ from sglang.srt.distributed import (
 from sglang.srt.distributed.device_communicators.pynccl_allocator import (
     use_symmetric_memory,
 )
-from sglang.srt.runtime_context import get_flags, get_server_args
+from sglang.srt.runtime_context import (
+    configured_attn_cp_size,
+    configured_moe_dp_size,
+    get_flags,
+)
 from sglang.srt.utils import get_bool_env_var, is_hip
 
 if TYPE_CHECKING:
@@ -986,8 +990,7 @@ def is_enable_moe_cp_allgather() -> bool:
     (``parallel_state.py``), so the live sizes are equal and the comparison would
     always be false.
     """
-    server_args = get_server_args()
+    return configured_attn_cp_size() > configured_moe_dp_size()
-    return server_args.attn_cp_size > server_args.moe_dp_size
 
 
 def moe_cp_all_gather_into_tensor(output: torch.Tensor, input: torch.Tensor):

python/sglang/srt/layers/k3_ar_fusion.py

@@ -67,16 +67,17 @@ def _get_state() -> Optional[_State]:
 
         if get_device_sm() not in (100, 103):
             return None
-        server_args = ctx.get_server_args()
+        symm_mem = ctx.get_exec().comm.enable_symm_mem
-        if server_args.enable_symm_mem or server_args.moe_a2a_backend != "none":
+        a2a_backend = ctx.get_exec().moe.moe_a2a_backend
+        if symm_mem or a2a_backend != "none":
             logger.info(
                 "K3 all-reduce fusion auto-probe: skipping "
                 "(enable_symm_mem=%s, moe_a2a_backend=%s; under symm-mem the "
                 "allocator contexts conflict, and under EP a2a the model's "
                 "symm-pool allocation contract does not hold on every AR "
                 "call-site. Set SGLANG_K3_AR_FUSION=1 to force.)",
-                server_args.enable_symm_mem,
+                symm_mem,
-                server_args.moe_a2a_backend,
+                a2a_backend,
             )
             return None
     from sglang.srt.distributed.device_communicators.custom_all_reduce_v2 import (
@@ -131,11 +132,11 @@ _BUFS: List[_Buffer] = []
 @cache_once
 def _max_buffer_rows() -> int:
     """Rows to reserve per buffer: the largest batch the server args allow."""
-    server_args = ctx.get_server_args()
+    schedule = ctx.get_schedule()
-    chunked = server_args.chunked_prefill_size
+    chunked = schedule.chunked_prefill_size
     if chunked is not None and chunked > 0:
         return int(chunked)
-    return int(server_args.max_prefill_tokens or 0)
+    return int(schedule.max_prefill_tokens or 0)
 
 
 def _create_buffer(

python/sglang/srt/layers/moe/moe_runner/flashinfer_cutedsl.py

@@ -12,7 +12,10 @@ from sglang.srt.layers.moe.moe_runner.base import (
     register_fused_func,
 )
 from sglang.srt.model_executor.cuda_graph_config import cuda_graph_fully_disabled
-from sglang.srt.runtime_context import get_parallel
+from sglang.srt.runtime_context import (
+    cutedsl_moe_max_num_tokens,
+    get_parallel,
+)
 from sglang.srt.utils.common import log_info_on_rank0, print_warning_once
 
 if TYPE_CHECKING:
@@ -256,14 +259,11 @@ def ensure_cutedsl_wrapper(layer: torch.nn.Module) -> None:
             "Install with: pip install flashinfer"
         ) from e
 
-    from sglang.srt.runtime_context import get_server_args
-
     assert layer.intermediate_size_per_partition > 0, (
         f"CuteDSL MoE: intermediate_size_per_partition must be > 0, "
         f"got {layer.intermediate_size_per_partition}. Check EP/TP configuration."
     )
 
-    server_args = get_server_args()
     # CuteDSL wrapper preallocates CG buffers used by any captured graph
     # that routes through this MoE — decode and prefill alike.
     use_cuda_graph = not cuda_graph_fully_disabled()
@@ -277,9 +277,7 @@ def ensure_cutedsl_wrapper(layer: torch.nn.Module) -> None:
     else:
         # Standard allgather path: the MoE sees up to dp_size local forwards
         # gathered together, so scale the per-rank forward bound by dp_size.
-        max_num_tokens = (
+        max_num_tokens = get_parallel().dp_size * cutedsl_moe_max_num_tokens()
-            get_parallel().dp_size * server_args.cutedsl_moe_max_num_tokens()
-        )
     top_k = layer.top_k if layer.top_k is not None else layer.moe_runner_config.top_k
     # inference_mode(False) ensures the wrapper's pre-allocated CUDA-graph
     # buffers are normal tensors.  This call typically happens inside

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

@@ -15,7 +15,10 @@ from sglang.srt.layers.dp_attention import (
 from sglang.srt.layers.moe import get_moe_a2a_backend
 from sglang.srt.mem_cache.memory_pool import KVWriteLoc
 from sglang.srt.model_executor.forward_context import get_token_to_kv_pool
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import (
+    get_parallel,
+    uses_mla_backend,
+)
 
 
 @dataclass
@@ -69,8 +72,7 @@ def is_prefill_cp_in_seq_split():
 
 
 def is_mla_prefill_cp_enabled() -> bool:
-    sa = get_server_args()
+    return get_parallel().enable_prefill_context_parallel and uses_mla_backend()
-    return get_parallel().enable_prefill_context_parallel and sa.use_mla_backend()
 
 
 def mla_use_prefill_cp(forward_batch, mla_enable_prefill_cp=None):

python/sglang/srt/managers/schedule_batch.py

@@ -7,6 +7,7 @@ from sglang.srt.runtime_context import (
     get_schedule,
     get_serving,
     get_spec,
+    mamba_cache_chunk_size,
     mamba_extra_buffer_enabled,
     mamba_extra_buffer_lazy_enabled,
 )
@@ -118,7 +119,7 @@ from sglang.srt.observability.req_time_stats import (
     DPControllerReqTimeStats,
     SchedulerReqTimeStats,
 )
-from sglang.srt.runtime_context import get_parallel, get_server_args
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.sampling.sampling_batch_info import SamplingBatchInfo
 from sglang.srt.sampling.sampling_params import SamplingParams
 from sglang.srt.server_args import ServerArgs
@@ -2616,21 +2617,20 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
         self,
         req: Req,
     ) -> _MambaRadixCacheV2TrackEntry:
-        server_args = get_server_args()
+        chunk_size = mamba_cache_chunk_size()
-        mamba_cache_chunk_size = server_args.mamba_cache_chunk_size
 
         def _force_track_h(i: int) -> int:
-            assert i % mamba_cache_chunk_size == 0
+            assert i % chunk_size == 0
             # There are 3 cases for mamba_track_seqlen passed to mamba_track_seqlens_cpu:
-            # 1) aligned with mamba_cache_chunk_size-> retrieve from last_recurrent_state
+            # 1) aligned with chunk_size-> retrieve from last_recurrent_state
             #    a) is the last position -> retrieve from last_recurrent_state
             #    b) is NOT the last position -> retrieve from h
-            # 2) unaligned with mamba_cache_chunk_size -> retrieve from h
+            # 2) unaligned with chunk_size -> retrieve from h
             # Currently, the math calculation only supports case 1a and 2. So for 1b, we need to add 1
             # to force the math calculation to retrieve the correct mamba state from h.
             return i + 1
 
-        mask = req.extend_range.length >= mamba_cache_chunk_size
+        mask = req.extend_range.length >= chunk_size
         track_index = req.mamba_ping_pong_track_buffer[req.mamba_next_track_idx].item()
         mamba_track_seqlen = -1
         if mask:
@@ -2647,18 +2647,16 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
             # mamba radix cache to track which seqlen this mamba state should store at.
             mamba_track_seqlen_aligned = (
                 len(req.prefix_indices)
-                + (req.extend_range.length // mamba_cache_chunk_size)
+                + (req.extend_range.length // chunk_size) * chunk_size
-                * mamba_cache_chunk_size
             )
 
-            # mamba_track_fla_chunk_aligned is the aligned seqlen based on mamba_cache_chunk_size
+            # mamba_track_fla_chunk_aligned is the aligned seqlen based on chunk_size
             # If mamba_track_fla_chunk_aligned != mamba_track_seqlen_aligned, which can be true when
-            # page_size > mamba_cache_chunk_size, we need to force the math calculation to retrieve the correct mamba state from h
+            # page_size > chunk_size, we need to force the math calculation to retrieve the correct mamba state from h
             # by _force_track_h()
             mamba_track_fla_chunk_aligned = (
                 len(req.prefix_indices)
-                + (req.extend_range.length // mamba_cache_chunk_size)
+                + (req.extend_range.length // chunk_size) * chunk_size
-                * mamba_cache_chunk_size
             )
             if mamba_track_fla_chunk_aligned != mamba_track_seqlen_aligned:
                 # We want to track mamba_track_seqlen_aligned, and it's not the last position,
@@ -2679,7 +2677,7 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
                 # is within the current extend batch.
                 branching_seqlen_aligned_mask = (
                     req.mamba_branching_seqlen - len(req.prefix_indices)
-                ) % mamba_cache_chunk_size == 0
+                ) % chunk_size == 0
                 if (
                     req.mamba_branching_seqlen > len(req.prefix_indices)
                     and req.mamba_branching_seqlen < mamba_track_seqlen

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

@@ -37,8 +37,8 @@ from sglang.srt.runtime_context import (
     get_exec,
     get_memory,
     get_observability,
-    get_server_args,
     mamba_extra_buffer_lazy_enabled,
+    max_speculative_num_draft_tokens,
 )
 from sglang.srt.speculative.base_spec_worker import BaseSpecWorker
 from sglang.srt.state_capturer.indexer_topk import get_global_indexer_capturer
@@ -1163,7 +1163,6 @@ class SchedulerBatchResultProcessor:
             keep_written_by_this_step = (
                 crossed and planned_pos == req.mamba_next_track_idx
             )
-            server_args = get_server_args()
             other_idx = 1 - req.mamba_next_track_idx
             # Recompute the in-flight verify's plan (kv_committed_len is
             # frozen since its prepare, so the recompute is exact).
@@ -1172,7 +1171,7 @@ class SchedulerBatchResultProcessor:
             ].item() == -1 and mamba_lazy_spec_in_window(
                 req,
                 get_exec().mamba.mamba_track_interval,
-                server_args.max_speculative_num_draft_tokens,
+                max_speculative_num_draft_tokens(),
             )
             if (
                 planned_pos is None

python/sglang/srt/mem_cache/mamba_radix_cache.py

@@ -50,7 +50,9 @@ from sglang.srt.mem_cache.multi_ended_allocator import (
 )
 from sglang.srt.mem_cache.radix_cache import RadixKey
 from sglang.srt.mem_cache.utils import split_node_hash_value
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import (
+    mamba_cache_chunk_size,
+)
 
 if TYPE_CHECKING:
     from sglang.srt.managers.schedule_batch import Req
@@ -450,7 +452,7 @@ class MambaRadixCache(KVCacheEventMixin, BasePrefixCache):
         )
         self.req_to_token_pool: HybridReqToTokenPool = params.req_to_token_pool
         self.token_to_kv_pool_allocator = params.token_to_kv_pool_allocator
-        self.mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        self.mamba_cache_chunk_size = mamba_cache_chunk_size()
 
         self.page_size = params.page_size
         self.disable = params.disable

python/sglang/srt/mem_cache/unified_cache/components/mamba_component.py

@@ -35,7 +35,10 @@ from sglang.srt.mem_cache.unified_cache.components.tree_component import (
     TreeComponent,
     get_and_increase_time_counter,
 )
-from sglang.srt.runtime_context import get_exec, get_server_args
+from sglang.srt.runtime_context import (
+    get_exec,
+    mamba_cache_chunk_size,
+)
 
 if TYPE_CHECKING:
     from sglang.srt.managers.schedule_batch import Req
@@ -65,7 +68,7 @@ class MambaComponent(TreeComponent):
                 params.page_size == 1
             ), f"MambaComponent requires page_size=1 when mamba_extra_buffer is disabled, got {params.page_size}"
         super().__init__(cache, params)
-        self.mamba_cache_chunk_size = get_server_args().mamba_cache_chunk_size
+        self.mamba_cache_chunk_size = mamba_cache_chunk_size()
         self.mamba_max_states_per_path = get_exec().mamba.mamba_max_states_per_path
         # HiCache state
         self._mamba_pool_host = None  # set to host mamba pool when HiCache enabled

python/sglang/srt/model_loader/loader.py

@@ -48,6 +48,7 @@ from sglang.srt.model_loader.remote_instance_weight_loader_utils import (
     register_memory_region,
 )
 from sglang.srt.runtime_context import (
+    configured_moe_dp_size,
     get_exec,
     get_model,
     get_parallel,
@@ -1776,14 +1777,13 @@ class PreshardedModelLoader(DefaultModelLoader):
                 return 1
 
         parallel = get_parallel()
-        server_args = get_server_args()
         return {
             "tp": _safe(lambda: parallel.tp_size),
             "dp": _safe(lambda: parallel.moe_dp_size),
             "ep": _safe(lambda: parallel.moe_ep_size),
             "pp": _safe(lambda: parallel.pp_size),
             "moe_dense_tp_size": parallel.moe_dense_tp_size,
-            "moe_dp_size": server_args.moe_dp_size,
+            "moe_dp_size": configured_moe_dp_size(),
             "enable_dp_lm_head": parallel.enable_dp_lm_head,
             "enable_fp32_lm_head": get_exec().features.enable_fp32_lm_head,
             "quantization": model_config.quantization,

python/sglang/srt/models/deepseek_v2.py

@@ -193,12 +193,12 @@ from sglang.srt.models.deepseek_common.utils import (
     is_wint4afp8_or_wint4a16_config,
 )
 from sglang.srt.runtime_context import (
+    attention_backends,
     get_device,
     get_exec,
     get_forward,
     get_model,
     get_parallel,
-    get_server_args,
     get_spec,
 )
 from sglang.srt.speculative.spec_info import SpeculativeAlgorithm
@@ -1999,8 +1999,7 @@ class DeepseekV2AttentionMLA(
         # Determine attention backend name for current forward batch: prefer the
         # name stamped per-runner on the backend object, else resolve from server args.
         backend = get_attn_backend()
-        server_args = get_server_args()
+        default_prefill_str, default_decode_str = attention_backends()
-        default_prefill_str, default_decode_str = server_args.get_attention_backends()
         prefill_backend_str = (
             backend.prefill_attention_backend_str or default_prefill_str
         )

python/sglang/srt/models/kimi_k25.py

@@ -46,10 +46,9 @@ from sglang.srt.multimodal.mm_utils import (
     run_dp_sharded_mrope_vision_model,
 )
 from sglang.srt.runtime_context import (
+    configured_tp_size,
     get_exec,
     get_mm,
-    get_parallel,
-    get_server_args,
 )
 from sglang.srt.utils import add_prefix, is_cuda, is_npu
 
@@ -731,13 +730,10 @@ class KimiK25ForConditionalGeneration(nn.Module):
             acknowledges the entire TP group so the bounded IPC pool remains
             recyclable.
             """
-            parallel = get_parallel()
+            # Same source as MmItemMemoryPool.try_to_recycle(), which waits on
-            server_args = get_server_args()
+            # configured_tp_size(): the live world size agrees once dist is up,
-            # Match MmItemMemoryPool.try_to_recycle(), which waits for the
+            # but a refcount that disagrees with the waiter would strand items.
-            # server TP size rather than the attention subgroup size.
+            ipc_consumer_count = max(configured_tp_size(), 1)
-            ipc_consumer_count = max(
-                getattr(server_args, "tp_size", parallel.attn_tp_size), 1
-            )
             device_index = device.index
             if device.type == "cuda" and device_index is None:
                 device_index = torch.cuda.current_device()

python/sglang/srt/models/kimi_k3.py

@@ -111,7 +111,12 @@ from sglang.srt.multimodal.kimi_k3_image_processing import (
     to_chw_uint8,
 )
 from sglang.srt.multimodal.mm_utils import materialize_multimodal_features
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import (
+    configured_tp_size,
+    get_exec,
+    get_parallel,
+    get_server_args,
+)
 from sglang.srt.utils import is_blackwell_supported, is_hip, make_layers
 from sglang.srt.utils.common import (
     BumpAllocator,
@@ -3082,7 +3087,10 @@ class KimiK3ForConditionalGeneration(nn.Module):
 
         def materialize_item_features(image_indices: List[int]) -> torch.Tensor:
             """Materialize only the images assigned to this vision-DP rank."""
-            ipc_consumer_count = max(get_parallel().tp_size, 1)
+            # Same source as MmItemMemoryPool.try_to_recycle(), which waits on
+            # configured_tp_size(): the live world size agrees once dist is up,
+            # but a refcount that disagrees with the waiter would strand items.
+            ipc_consumer_count = max(configured_tp_size(), 1)
             device_index = device.index
             if device.type == "cuda" and device_index is None:
                 device_index = torch.cuda.current_device()

python/sglang/srt/models/minimax_m2.py

@@ -85,7 +85,7 @@ from sglang.srt.runtime_context import (
     get_forward,
     get_parallel,
     get_schedule,
-    get_server_args,
+    process_model_config,
 )
 
 # get_bool_env_var is defined in sglang.srt.utils.common, not sglang.srt.distributed.
@@ -431,10 +431,9 @@ class MiniMaxM2QKRMSNorm:
 
         props = torch.cuda.get_device_properties(device)
         # probe the maximum tokens for one prefill
-        server_args = get_server_args()
         max_tokens = get_schedule().chunked_prefill_size
         if max_tokens is None:
-            max_tokens = server_args.model_config.context_len
+            max_tokens = process_model_config().context_len
         max_tokens = max(max_tokens, get_schedule().max_prefill_tokens)
         logger.info(f"[AR] Using CustomAllReduceV2 for MiniMaxM2 with {max_tokens = }")
         ALIGN = 512

python/sglang/srt/models/sarvam_moe.py

@@ -61,8 +61,10 @@ from sglang.srt.models.deepseek_common.attention_forward_methods.forward_mha imp
     DeepseekMHAForwardMixin,
 )
 from sglang.srt.runtime_context import (
+    attention_backends,
     get_exec,
     get_forward,
+    get_memory,
     get_model,
     get_parallel,
     get_server_args,
@@ -609,18 +611,12 @@ class SarvamMoEMLAAttention(nn.Module):
         return k
 
     def _set_current_attention_backend(self, forward_batch: ForwardBatch) -> None:
-        if self._server_args is None:
+        prefill_backend, decode_backend = attention_backends()
-            self._server_args = get_server_args()
+        self.current_attention_backend = (
-        if forward_batch.forward_mode.is_decode_or_idle():
+            decode_backend
-            self.current_attention_backend = (
+            if forward_batch.forward_mode.is_decode_or_idle()
-                self._server_args.decode_attention_backend
+            else prefill_backend
-                or self._server_args.attention_backend
+        )
-            )
-        else:
-            self.current_attention_backend = (
-                self._server_args.prefill_attention_backend
-                or self._server_args.attention_backend
-            )
 
     def _maybe_fp8_bmm(
         self,
@@ -684,7 +680,7 @@ class SarvamMoEMLAAttention(nn.Module):
         )
 
         self._set_current_attention_backend(forward_batch)
-        can_use_prefix_cache = not self._server_args.disable_radix_cache
+        can_use_prefix_cache = not get_memory().disable_radix_cache
         do_prefix_merge = has_extend_prefix and can_use_prefix_cache
 
         if do_prefix_merge and forward_batch.num_prefix_chunks is None:

python/sglang/srt/runtime_context.py

@@ -47,6 +47,7 @@ test-only ``override(**kw)``.
 from __future__ import annotations
 
 import dataclasses
+import functools
 import os
 import sys
 from contextlib import contextmanager
@@ -827,6 +828,10 @@ class RuntimeContext:
             server_args, "enable_torch_compile", False
         )
         self._server_args = server_args
+        # The adaptive draft-token bound memoizes on the config *path*, so a new
+        # publication that reuses the path must not inherit the bound computed
+        # from the file's previous contents.
+        _adaptive_draft_token_bound.cache_clear()
         # Snapshot resolved config into the namespace bags (the single source of
         # truth for config reads). Driven by NS(...) metadata; a mock/partial
         # config with no NS markers yields an empty tree (no bags projected).
@@ -1376,6 +1381,7 @@ def reset_context() -> None:
     """
     _CONTEXT._server_args = None
     _CONTEXT._config_bags = None
+    _adaptive_draft_token_bound.cache_clear()
     _CONTEXT._overrides_log = []
     _CONTEXT._publish_role = None
     _CONTEXT.parallel._config = None
@@ -1406,3 +1412,144 @@ def mamba_extra_buffer_lazy_enabled() -> bool:
         get_memory().disable_radix_cache is False
         and get_exec().mamba.mamba_radix_cache_strategy == "extra_buffer_lazy"
     )
+
+
+# --- Derived config accessors ------------------------------------------------
+#
+# A few values are computed from several config fields plus the HF config, so
+# they are ``ServerArgs`` members rather than namespace leaves. Business code
+# must not reach for the startup record to get them: these accessors are the
+# named home, and this module — which owns the slot — is the only place that
+# reads it. Each one keeps the member's exact semantics, including which model
+# config it derives from (always the process's, i.e. the target's).
+
+
+def mamba_cache_chunk_size() -> int:
+    """The caching point granularity for mamba state: ``max(the model's mamba
+    chunk size, page_size)``. Cached on the config after the first call."""
+    return get_server_args().mamba_cache_chunk_size
+
+
+def max_speculative_num_draft_tokens() -> int | None:
+    """The largest draft-token count speculative decoding may use.
+
+    All three inputs are ``spec`` leaves, so this derives from the bags and
+    follows a post-publish override; ``ServerArgs.max_speculative_num_draft_tokens``
+    is the pre-publish equivalent. Adaptive spec resolves the count from its
+    candidate-step table instead of the flat field.
+    """
+    spec = get_spec()
+    if spec.speculative_num_draft_tokens is None:
+        return None
+    if not spec.speculative_adaptive:
+        return spec.speculative_num_draft_tokens
+    # The adaptive branch parses a JSON config, and this is called per decode
+    # batch (`spec_prepare_for_decode`), so memoize on the inputs -- keyed, not
+    # cached once, so a post-publish override still recomputes.
+    return _adaptive_draft_token_bound(spec.speculative_adaptive_config)
+
+
+@functools.lru_cache(maxsize=8)
+def _adaptive_draft_token_bound(cfg_path: str | None) -> int:
+    from sglang.srt.speculative.adaptive_spec_params import (
+        resolve_candidate_steps_from_config,
+    )
+
+    candidate_steps = resolve_candidate_steps_from_config(cfg_path=cfg_path)
+    # Adaptive spec requires topk=1 today, so each runtime state needs
+    # steps + 1 draft-token slots (mirrors the ServerArgs member).
+    return max(candidate_steps) + 1
+
+
+def uses_mla_backend() -> bool:
+    """Whether this process's model runs the MLA attention path."""
+    return get_server_args().use_mla_backend()
+
+
+def attention_backends() -> tuple:
+    """The configured ``(prefill, decode)`` backend pair, split fields falling
+    back to ``attention_backend``.
+
+    All three inputs are ``exec.kernel`` leaves, so this derives from the bags
+    and follows a post-publish override; ``ServerArgs.get_attention_backends``
+    is the pre-publish equivalent the resolution pipeline uses. A built runner
+    stamps its own resolved pair (``ModelRunner.prefill_attention_backend_str``);
+    read that when there is a runner in hand.
+    """
+    from sglang.srt.arg_groups.overrides import attention_backends_of
+
+    # All three leaves live in the same bag, so the resolution pipeline's own
+    # helper applies directly -- one definition of the fallback rule.
+    return attention_backends_of(get_exec().kernel)
+
+
+def process_model_config():
+    """The process's ``ModelConfig`` (built once from the published config)."""
+    return get_server_args().get_model_config()
+
+
+def cutedsl_moe_max_num_tokens() -> int:
+    """The CuteDSL A2A per-rank token budget.
+
+    Every input is a published leaf (``spec``, ``schedule``, ``exec.graph``), so
+    this derives from the bags and follows a post-publish override;
+    ``ServerArgs.cutedsl_moe_max_num_tokens`` is the pre-publish equivalent the
+    resolution pipeline uses. Max over the prefill bound, the piecewise-prefill
+    capture, and the decode/verify bound.
+    """
+    from sglang.srt.model_executor.cuda_graph_config import Backend
+
+    spec = get_spec()
+    num_tokens_per_req = (
+        (spec.speculative_num_draft_tokens or 1) if spec.speculative_algorithm else 1
+    )
+    prefill_tokens = get_schedule().max_prefill_tokens
+    cg_config = get_exec().graph.cuda_graph_config
+    if cg_config is not None and cg_config.prefill.backend == Backend.TC_PIECEWISE:
+        prefill_tokens = max(prefill_tokens, cg_config.prefill.max_bs or 0)
+    decode_max_bs = (cg_config.decode.max_bs if cg_config is not None else 0) or 0
+    return max(prefill_tokens, decode_max_bs * num_tokens_per_req)
+
+
+# --- Configured (not live) parallel sizes ------------------------------------
+#
+# ``get_parallel()`` shadows these names with the LIVE topology, which is the
+# right answer almost everywhere. A handful of call sites need what was
+# *configured* instead — before the groups exist, in a process that has none,
+# or where the live value is deliberately aliased to another dimension. Each
+# accessor below names that intent so no business call site has to reach for
+# the startup record; the per-site reasons live in the read ratchet.
+#
+# They read the published leaf rather than the record: the bag is what
+# ``override`` writes, and once the instance holds only the user's raw input
+# the record would answer with what was *typed* instead of what resolution
+# produced. Going through the bag directly is what gets past the live property
+# that shadows these four names on ``get_parallel()``.
+
+
+def _configured_parallel(name: str):
+    # The bag itself, not ParallelContext, whose live property shadows these
+    # four names. Read through the parallel slot the way the leaf accessor
+    # does — ``parallel`` is deliberately outside the per-role namespace table
+    # (every process reads topology config), so this must not route through
+    # ``config_bag()``'s role check, which would record or reject the read.
+    config = _CONTEXT.parallel._config
+    if config is None:
+        raise ValueError("config namespace 'parallel' not published")
+    return getattr(config, name)
+
+
+def configured_tp_size() -> int:
+    return _configured_parallel("tp_size")
+
+
+def configured_pp_size() -> int:
+    return _configured_parallel("pp_size")
+
+
+def configured_moe_dp_size() -> int:
+    return _configured_parallel("moe_dp_size")
+
+
+def configured_attn_cp_size() -> int:
+    return _configured_parallel("attn_cp_size")

python/sglang/srt/server_args.py

@@ -40,7 +40,12 @@ from sglang.srt.arg_groups.argparse_actions import (
     DeprecatedStoreTrueAction,
     LoRAPathAction,
 )
-from sglang.srt.arg_groups.overrides import resolved_view
+from sglang.srt.arg_groups.overrides import (
+    attention_backends_of,
+    mamba_extra_buffer_lazy_of,
+    mamba_extra_buffer_of,
+    resolved_view,
+)
 from sglang.srt.configs.embedding_model_spec import BCGPrefillPolicy
 from sglang.srt.configs.linear_attn_model_registry import get_linear_attn_spec_by_arch
 from sglang.srt.connector import ConnectorType
@@ -8689,17 +8694,7 @@ class ServerArgs:
         return attention_backends_of(resolved_view(self))
 
     def get_attention_backends(self):
-        prefill_attention_backend_str = (
+        return attention_backends_of(self)
-            self.prefill_attention_backend
-            if self.prefill_attention_backend
-            else self.attention_backend
-        )
-        decode_attention_backend_str = (
-            self.decode_attention_backend
-            if self.decode_attention_backend
-            else self.attention_backend
-        )
-        return prefill_attention_backend_str, decode_attention_backend_str
 
     def use_mla_backend(self):
         from sglang.srt.configs.model_config import AttentionArch
@@ -8715,16 +8710,10 @@ class ServerArgs:
         )
 
     def enable_mamba_extra_buffer(self) -> bool:
-        return (
+        return mamba_extra_buffer_of(self)
-            self.disable_radix_cache is False
-            and self.mamba_radix_cache_strategy in ("extra_buffer", "extra_buffer_lazy")
-        )
 
     def enable_mamba_extra_buffer_lazy(self) -> bool:
-        return (
+        return mamba_extra_buffer_lazy_of(self)
-            self.disable_radix_cache is False
-            and self.mamba_radix_cache_strategy == "extra_buffer_lazy"
-        )
 
     @cached_property
     def max_speculative_num_draft_tokens(self) -> Optional[int]:

python/sglang/srt/speculative/spec_utils.py

@@ -48,10 +48,10 @@ from sglang.srt.mem_cache.allocation import (
 )
 from sglang.srt.runtime_context import (
     get_exec,
-    get_server_args,
     get_spec,
     mamba_extra_buffer_enabled,
     mamba_extra_buffer_lazy_enabled,
+    max_speculative_num_draft_tokens,
 )
 from sglang.srt.utils import (
     is_cpu,
@@ -1030,12 +1030,11 @@ def spec_prepare_for_decode(batch: ScheduleBatch) -> None:
     """eagle/ngram share a stateless free function; dflash keeps stateful
     prep on its draft input -- the dispatcher routes.
     """
-    server_args = get_server_args()
     if mamba_extra_buffer_lazy_enabled():
         # Scheduler phase (outside forward isolation).
         batch.mamba_lazy_spec_prepare(
             get_exec().mamba.mamba_track_interval,
-            server_args.max_speculative_num_draft_tokens,
+            max_speculative_num_draft_tokens(),
         )
     if batch.spec_algorithm.is_dflash_family():
         batch.spec_info.prepare_for_decode(batch)

python/sglang/srt/utils/cuda_ipc_transport_utils.py

@@ -9,7 +9,9 @@ import numpy as np
 import torch
 
 from sglang.srt.environ import envs
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import (
+    configured_tp_size,
+)
 from sglang.srt.utils.stale_shm_cleanup import make_shm_name
 
 logger = logging.getLogger(__name__)
@@ -130,7 +132,7 @@ class MmItemMemoryChunk:
 
     def try_to_recycle(self) -> bool:
         try:
-            tp_num = get_server_args().tp_size
+            tp_num = configured_tp_size()
         except Exception:
             logger.info(
                 "server_args has not been published yet, skip this turn's recycle"

test/registered/unit/layers/attention/test_gdn_prefill_backend_policy.py

@@ -18,6 +18,7 @@ from sglang.srt.layers.attention.linear.kernels.gdn_flashinfer import (
 )
 from sglang.srt.layers.attention.linear.kernels.gdn_triton import TritonGDNKernel
 from sglang.srt.layers.attention.linear.utils import LinearAttnKernelBackend
+from sglang.srt.runtime_context import get_context
 from sglang.test.ci.ci_register import register_cpu_ci
 
 register_cpu_ci(est_time=5, suite="base-a-test-cpu")
@@ -151,12 +152,12 @@ class TestFlashInferGDNPrefillBackendPolicy(unittest.TestCase):
             track_ssm_h_dst=torch.empty(4),
         )
 
-        with patch(
+        # The chunk size is a derived config member; seed its private cache on a
-            "sglang.srt.layers.attention.linear.kernels.gdn_flashinfer."
+        # published config rather than patching an import binding.
-            "get_server_args",
+        override = get_context().override_server_args(_mamba_cache_chunk_size=64)
-            return_value=SimpleNamespace(mamba_cache_chunk_size=64),
+        override.install()
-        ):
+        self.addCleanup(override.restore)
-            maybe_build_flashinfer_checkpoint_plan(forward_batch, metadata, "cpu")
+        maybe_build_flashinfer_checkpoint_plan(forward_batch, metadata, "cpu")
 
         torch.testing.assert_close(
             metadata.state_checkpoint_cu_starts,

test/registered/unit/model_loader/test_presharded_loader.py

@@ -786,13 +786,6 @@ class TestShardConfig(unittest.TestCase):
         # `_collect_shard_config` is the exact failure mode that left
         # moe_dense_tp_size / LM-head flags out of the cache key before.
         loader = object.__new__(PreshardedModelLoader)
-        server_args = SimpleNamespace(
-            moe_dp_size=2,
-            enable_fp32_lm_head=True,
-            ep_num_redundant_experts=4,
-            enable_eplb=True,
-            init_expert_location="trivial",
-        )
         model_config = SimpleNamespace(quantization="fp8", dtype=torch.bfloat16)
         required = {
             "tp",
@@ -819,8 +812,8 @@ class TestShardConfig(unittest.TestCase):
             enable_dp_lm_head=True,
         )
         with mock.patch(
-            "sglang.srt.model_loader.loader.get_server_args",
+            "sglang.srt.model_loader.loader.configured_moe_dp_size",
-            return_value=server_args,
+            return_value=2,
         ), mock.patch(
             "sglang.srt.model_loader.loader.get_parallel",
             return_value=parallel,

test/registered/unit/models/test_kimi_k25.py

@@ -39,7 +39,7 @@ from sglang.srt.multimodal.processors.kimi_k25 import (
     _resize_bicubic_if_needed,
     _resize_images_by_source_shape,
 )
-from sglang.srt.runtime_context import get_parallel
+from sglang.srt.runtime_context import get_context, get_parallel
 from sglang.srt.utils.cuda_ipc_transport_utils import (
     DEFER_CUDA_IPC_FEATURE_RECONSTRUCTION_KEY,
     CudaIpcTensorTransportProxy,
@@ -317,7 +317,11 @@ def test_dp_helper_supports_moonvit3d_packed_embeddings_on_tp1():
     tower = _MoonViT3dTower()
     pixel_values = torch.randn(4, 2)
 
-    with get_parallel().override(tp_size=1, tp_rank=0, attn_tp_size=1, attn_tp_rank=0):
+    # The IPC consumer count asks for the *configured* TP size (matching
+    # MmItemMemoryPool.try_to_recycle), so the double publishes one too.
+    with get_context().override_server_args(tp_size=1), get_parallel().override(
+        tp_size=1, tp_rank=0, attn_tp_size=1, attn_tp_rank=0
+    ):
         output = run_dp_sharded_mrope_vision_model(
             tower, pixel_values, [[1, 2, 2]], rope_type="rope_2d_packed"
         )
@@ -331,7 +335,11 @@ def test_dp_helper_can_lazily_load_kimi_features_on_tp1():
     pixel_values = torch.randn(4, 2)
     loader = Mock(return_value=pixel_values)
 
-    with get_parallel().override(tp_size=1, tp_rank=0, attn_tp_size=1, attn_tp_rank=0):
+    # The IPC consumer count asks for the *configured* TP size (matching
+    # MmItemMemoryPool.try_to_recycle), so the double publishes one too.
+    with get_context().override_server_args(tp_size=1), get_parallel().override(
+        tp_size=1, tp_rank=0, attn_tp_size=1, attn_tp_rank=0
+    ):
         output = run_dp_sharded_mrope_vision_model(
             tower,
             None,
@@ -479,11 +487,10 @@ def test_kimi_non_dp_keeps_grid_thws_on_the_host():
     model.mm_projector = _IdentityProjector()
     items = [_image_item(torch.randn(4, 2), [[1, 2, 2]])]
 
-    with get_parallel().override(
+    # The IPC consumer count asks for the *configured* TP size (matching
+    # MmItemMemoryPool.try_to_recycle), so the double publishes one too.
+    with get_context().override_server_args(tp_size=1), get_parallel().override(
         tp_size=1, tp_rank=0, attn_tp_size=1, attn_tp_rank=0
-    ), patch(
-        "sglang.srt.models.kimi_k25.get_server_args",
-        return_value=SimpleNamespace(tp_size=1),
     ):
         model.get_image_feature(items)
 

test/registered/unit/models/test_kimi_k3_vision.py

@@ -464,15 +464,17 @@ def test_kimi_k3_encoder_dp_defers_feature_materialization(monkeypatch):
     ]
     sharded_embeddings = torch.randn(2, 2)
 
+    # The IPC consumer count asks for the *configured* TP size (matching
+    # MmItemMemoryPool.try_to_recycle), so publish it; the live topology the
+    # sharding helper reads is forced through the context's own override.
     with mock_patch(
         "sglang.srt.multimodal.mm_utils.run_dp_sharded_mrope_vision_model",
         return_value=sharded_embeddings,
-    ) as run_dp, mock_patch(
+    ) as run_dp, get_context().override_server_args(tp_size=1), get_parallel().override(
-        "sglang.srt.models.kimi_k3.get_parallel",
+        tp_size=1, attn_tp_size=1
-        return_value=SimpleNamespace(tp_size=1, attn_tp_size=1),
     ):
         output = model.get_image_feature(items)
-        # Exercise the loader while the runtime topology is patched.
+        # Exercise the loader while the runtime topology is forced.
         loader_in_scope = run_dp.call_args.kwargs["load_local_pixel_values"]
         local = loader_in_scope([1])
         both = loader_in_scope([0, 1])
@@ -545,12 +547,13 @@ def test_kimi_k3_preprocesses_only_dp_owner_images(monkeypatch):
         calls.append([int(image[0, 0, 0]) for image in images])
         return torch.tensor([[float(calls[-1][0]), 0.0]]), torch.tensor([[1, 1, 1]])
 
+    # Configured TP size (the IPC consumer count) comes from the published
+    # bags; the live topology is forced through the context's own override.
     with mock_patch(
         "sglang.srt.multimodal.mm_utils.run_dp_sharded_mrope_vision_model",
         return_value=torch.zeros(1, 2),
-    ) as run_dp, mock_patch(
+    ) as run_dp, get_context().override_server_args(tp_size=1), get_parallel().override(
-        "sglang.srt.models.kimi_k3.get_parallel",
+        tp_size=1, attn_tp_size=1
-        return_value=SimpleNamespace(tp_size=1, attn_tp_size=1),
     ), mock_patch(
         "sglang.srt.multimodal.processors.kimi_k25._gpu_preprocess_images",
         side_effect=fake_preprocess,

test/registered/unit/spec/test_ngram_mamba_verify_update.py

@@ -197,9 +197,6 @@ class TestNgramMambaVerifyUpdate(CustomTestCase):
         with patch(
             "sglang.srt.speculative.spec_utils.mambaish_config",
             return_value={"some": "config"},
-        ), patch(
-            "sglang.srt.speculative.spec_utils.get_server_args",
-            return_value=MagicMock(mamba_track_interval=256),
         ), patch(
             "sglang.srt.speculative.spec_utils.get_exec",
             return_value=MagicMock(mamba=MagicMock(mamba_track_interval=256)),

test/registered/unit/test_context_accessor_shadowing.py

@@ -0,0 +1,191 @@
+"""No local may shadow a ``runtime_context`` accessor it also calls.
+
+A mechanical sweep that rewrites ``self.server_args.mamba_cache_chunk_size``
+into ``mamba_cache_chunk_size()`` turns
+
+    mamba_cache_chunk_size = self.server_args.mamba_cache_chunk_size
+
+into ``mamba_cache_chunk_size = mamba_cache_chunk_size()``, which is a
+self-referential local: the name is local for the whole function, so the call
+raises ``UnboundLocalError`` the first time that line runs. Five of these
+shipped in one sweep and only one had unit coverage — a mamba model on the
+radix-cache-v2 path found it at request time.
+
+This scans for the shape directly: a function-scope assignment whose target
+name is an imported accessor.
+"""
+
+import ast
+import unittest
+from pathlib import Path
+
+import sglang
+from sglang.test.ci.ci_register import register_cpu_ci
+from sglang.test.test_utils import CustomTestCase
+
+register_cpu_ci(est_time=5, suite="base-a-test-cpu")
+
+_PACKAGE_ROOT = Path(next(iter(sglang.__path__)))
+_CONTEXT_MODULE = "sglang.srt.runtime_context"
+
+
+def _module_level_accessor_imports(tree: ast.AST) -> set[str]:
+    """Accessors imported at module scope — visible in every function.
+
+    A *function-local* import is visible only inside its own scope, so it is
+    collected per function in the scan below: charging it file-wide would flag
+    an unrelated sibling function that binds the same name, where no shadowing
+    can occur.
+    """
+    names: set[str] = set()
+    stack = list(tree.body)
+    while stack:
+        stmt = stack.pop()
+        if isinstance(
+            stmt, (ast.FunctionDef, ast.AsyncFunctionDef, ast.Lambda, ast.ClassDef)
+        ):
+            continue
+        if isinstance(stmt, ast.ImportFrom) and stmt.module == _CONTEXT_MODULE:
+            for alias in stmt.names:
+                names.add(alias.asname or alias.name)
+        stack.extend(ast.iter_child_nodes(stmt))
+    return names
+
+
+def _bound_names(target):
+    """Every name a binding target introduces, unpacking included.
+
+    ``a, (b, c) = ...`` and ``for x, y in ...`` bind through Tuple/List/Starred
+    nodes, so a check that only accepts a bare ``ast.Name`` misses them.
+    """
+    if isinstance(target, ast.Name):
+        yield target.id
+    elif isinstance(target, ast.Starred):
+        yield from _bound_names(target.value)
+    elif isinstance(target, (ast.Tuple, ast.List)):
+        for element in target.elts:
+            yield from _bound_names(element)
+
+
+def _own_scope_statements(node) -> tuple:
+    """This function's OWN scope: its statements, plus the (name, lineno) of
+    each nested ``def``/``class`` — the definition's *name* is a binding in
+    this scope (an earlier accessor call raises UnboundLocalError just like an
+    assignment), while its *body* is the nested scope's own and descending into
+    it would misattribute bindings."""
+    own_scope = []
+    nested_def_bindings = []
+    pending = list(node.body)
+    while pending:
+        stmt = pending.pop()
+        if isinstance(stmt, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)):
+            nested_def_bindings.append((stmt.name, stmt.lineno))
+            continue
+        if isinstance(stmt, ast.Lambda):
+            continue
+        own_scope.append(stmt)
+        pending.extend(ast.iter_child_nodes(stmt))
+    return own_scope, nested_def_bindings
+
+
+def _child_functions(body) -> list:
+    """Function defs directly beneath this scope — descending through plain
+    statements and class bodies (a method closes over the enclosing function's
+    names, not the class's), but never into another function."""
+    funcs = []
+    pending = list(body)
+    while pending:
+        stmt = pending.pop()
+        if isinstance(stmt, (ast.FunctionDef, ast.AsyncFunctionDef)):
+            funcs.append(stmt)
+            continue
+        if isinstance(stmt, ast.Lambda):
+            continue
+        pending.extend(ast.iter_child_nodes(stmt))
+    return funcs
+
+
+def _shadowing_assignments(tree: ast.AST, module_accessors: set[str]):
+    """Function-local bindings whose name shadows an accessor visible in that
+    scope -- every statement form that binds a local, not just ``=``.
+
+    Python decides a name is local from *any* binding in the function, so a
+    loop variable, a ``with ... as``, a walrus, a comprehension target, or an
+    ``except ... as`` all shadow the accessor for the whole function body,
+    exactly like an assignment does.
+
+    Visibility follows lexical scope: module-level imports reach every
+    function; a function-local import reaches its own scope and nested
+    functions (closure), but NOT an unrelated sibling — charging it file-wide
+    would flag bindings where no shadowing occurs. A function-scope *re-import*
+    of the accessor is itself fine: it binds the name to the same callable, so
+    calls after it behave identically (and the module is full of deliberate
+    local imports).
+    """
+    stack = [(fn, module_accessors) for fn in _child_functions(tree.body)]
+    while stack:
+        node, inherited = stack.pop()
+        own_scope, nested_def_bindings = _own_scope_statements(node)
+        local_imports = {
+            alias.asname or alias.name
+            for stmt in own_scope
+            if isinstance(stmt, ast.ImportFrom) and stmt.module == _CONTEXT_MODULE
+            for alias in stmt.names
+        }
+        visible = inherited | local_imports
+        # ``def get_exec(): ...`` nested in the function binds the name in
+        # THIS scope, exactly like an assignment would.
+        for name, lineno in nested_def_bindings:
+            if name in visible:
+                yield node.name, name, lineno
+        for inner in own_scope:
+            targets = []
+            if isinstance(inner, ast.Assign):
+                targets = inner.targets
+            elif isinstance(inner, (ast.AnnAssign, ast.AugAssign)):
+                targets = [inner.target]
+            elif isinstance(inner, (ast.For, ast.AsyncFor, ast.comprehension)):
+                targets = [inner.target]
+            elif isinstance(inner, ast.NamedExpr):
+                targets = [inner.target]
+            elif isinstance(inner, (ast.With, ast.AsyncWith)):
+                targets = [i.optional_vars for i in inner.items if i.optional_vars]
+            elif isinstance(inner, ast.ExceptHandler) and inner.name:
+                targets = [ast.Name(id=inner.name, ctx=ast.Store())]
+            for target in targets:
+                for name in _bound_names(target):
+                    if name in visible:
+                        yield node.name, name, getattr(inner, "lineno", node.lineno)
+        for nested in _child_functions(node.body):
+            stack.append((nested, visible))
+
+
+class TestNoAccessorShadowing(CustomTestCase):
+    def test_no_local_shadows_a_context_accessor(self):
+        offenders = []
+        for path in sorted(_PACKAGE_ROOT.rglob("*.py")):
+            rel = path.relative_to(_PACKAGE_ROOT).as_posix()
+            if rel.startswith("srt/runtime_context.py"):
+                continue
+            source = path.read_text()
+            # A file that never names the module cannot import an accessor
+            # from it, at module scope or inside any function.
+            if _CONTEXT_MODULE not in source:
+                continue
+            try:
+                tree = ast.parse(source)
+            except SyntaxError:
+                continue
+            module_accessors = _module_level_accessor_imports(tree)
+            for func, name, lineno in _shadowing_assignments(tree, module_accessors):
+                offenders.append(f"{rel}:{lineno}: {func}() binds {name!r}")
+        self.assertFalse(
+            offenders,
+            "locals shadow a runtime_context accessor imported in the same "
+            "module; the name is local for the whole function, so any call to "
+            "the accessor there raises UnboundLocalError:\n" + "\n".join(offenders),
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/unit/test_global_config_read_ratchet.py

@@ -6,22 +6,24 @@ startup record. Config decisions read the namespace accessors instead
 including post-publish overrides, and per-runner values come from the runner
 that owns them.
 
-Two shapes count as a read: the direct ``get_server_args().field``, and the
+Business code no longer reads the published record for a config value at all:
-alias ``sa = get_server_args()`` followed by ``sa.field`` in the same function.
+the baselines are zero for both shapes, over the whole package minus the two
-A whole-object pass (``def f(server_args)``) is not a global read and is not
+modules that own the slot.
-counted — there the caller decided which instance to hand over.
 
-What legitimately remains:
+Where the remaining reads live (``runtime_context.py``, exempt by module):
 
-- **Derived APIs.** ``@property`` and method members of ``ServerArgs``
+- **Derived members.** ``@property`` / method members of ``ServerArgs``
-  (``mamba_cache_chunk_size``, ``get_model_config()``,
+  (``mamba_cache_chunk_size``, ``max_speculative_num_draft_tokens``,
-  ``enable_mamba_extra_buffer()``, …) are computed from several fields plus the
+  ``use_mla_backend()``, ``get_attention_backends()``, ``get_model_config()``,
-  HF config, so they are not namespace leaves and ``ServerArgs`` is their only
+  ``cutedsl_moe_max_num_tokens()``) are computed from several fields plus the HF
-  home. Exempt by name below.
+  config, so they are not namespace leaves and ``ServerArgs`` is their only
+  home. ``runtime_context`` exposes each one as a named accessor
+  (``mamba_cache_chunk_size()`` …) and is the only module that reads the slot
+  for them.
 - **Config-intent reads of live-shadowed sizes.** ``get_parallel()`` shadows
-  ``tp/pp/dcp/attn_cp/moe_dp_size`` with the live topology, so a config-intent
+  ``tp/pp/dcp/attn_cp/moe_dp_size`` with the live topology, and a few call sites
-  read of one has nowhere else to go. Each exempt site needs an answer the live
+  need what was *configured*: the ``configured_*_size()`` accessors. Their
-  property cannot give:
+  reasons, per call site:
 
   - ``dsa_indexer.pp_size`` gates ``pp_size > 1 and not get_pp_group()...``, and
     the short circuit is the point: with PP off the group is never touched, which
@@ -35,8 +37,23 @@ What legitimately remains:
     sizes are equal there and a live comparison is always false.
   - ``model_loader/loader.py`` reports both: the same dict carries the live
     ``moe_dp_size`` under ``"dp"``, so this entry is the configured intent.
-- The alias-form baseline is not zero yet. Lowering it is the next slice; the
+
-  failure message lists the sites whenever the count moves.
+What the ratchet sees, syntactically: ``get_server_args().field``,
+``sa = get_server_args()`` followed by ``sa.field`` (function-local, module-level,
+or parked on an instance attribute -- ``self._sa = get_server_args()`` read from
+another method of the same class), function-local copies of an alias to a
+fixpoint (``cfg = sa`` then ``cfg.field``), and the dynamic form of each --
+``getattr(<either>, "field")`` -- since a string-named read reaches the same
+slot. What it cannot see is a name computed at runtime (``getattr(sa, name)``)
+or indirection deeper than a local name copy (through a container, an
+attribute of another object, a cross-scope copy); the census tool in the
+context repo is what audits those.
+
+A whole-object pass (``def f(server_args)``) is not a global read and is not
+counted -- there the caller decided which instance to hand over. An optional
+parameter that falls back to the global (``f(server_args=None)``) hides one,
+so those fallbacks were removed; the ratchet cannot see them and the census
+tool in the context repo is what audits that shape.
 """
 
 from sglang.test.ci.ci_register import register_cpu_ci
@@ -54,48 +71,92 @@ from sglang.test.test_utils import CustomTestCase
 # scanned so a new one cannot appear there unnoticed.
 _PACKAGE_ROOT = Path(next(iter(sglang.__path__)))
 
-_DERIVED_MEMBERS = frozenset(
+# The modules that own the slot: runtime_context publishes it and exposes the
-    {
+# named accessors for the derived members, server_args/arg_groups ARE the
-        "cutedsl_moe_max_num_tokens",
+# resolution pipeline.
-        "enable_mamba_extra_buffer",
+_SLOT_OWNERS = ("srt/runtime_context.py", "srt/server_args.py", "srt/arg_groups/")
-        "enable_mamba_extra_buffer_lazy",
-        "get_attention_backends",
-        "get_model_config",
-        "mamba_cache_chunk_size",
-        "max_speculative_num_draft_tokens",
-        "model_config",
-        "use_mla_backend",
-    }
-)
 
-_CONFIG_INTENT_SIZES = frozenset(
+# Every call site of a ``configured_*_size()`` accessor, with the reason the
-    {
+# live topology cannot answer there. The test below asserts this map is exactly
-        ("srt/layers/attention/dsa/dsa_indexer.py", "pp_size"),
+# the set of call sites, so the reasons cannot drift away from the code.
-        ("srt/layers/dp_attention.py", "attn_cp_size"),
+_CONFIGURED_SIZE_CALL_SITES = {
-        ("srt/layers/dp_attention.py", "moe_dp_size"),
+    ("srt/layers/attention/dsa/dsa_indexer.py", "configured_pp_size"): (
-        ("srt/model_loader/loader.py", "moe_dp_size"),
+        "gates `pp_size > 1 and not get_pp_group()...`; the short circuit is the "
-        ("srt/utils/cuda_ipc_transport_utils.py", "tp_size"),
+        "point, since with PP off the group is never touched, which is what lets "
-    }
+        "the Indexer be constructed before distributed init"
-)
+    ),
+    ("srt/layers/dp_attention.py", "configured_attn_cp_size"): (
+        "compared against the configured moe_dp_size below"
+    ),
+    ("srt/layers/dp_attention.py", "configured_moe_dp_size"): (
+        "the configuration this predicate detects (attn_cp_size > moe_dp_size) is "
+        "the one where initialize_model_parallel aliases _MOE_DP to _ATTN_CP, so "
+        "the live sizes are equal there and a live comparison is always false"
+    ),
+    ("srt/model_loader/loader.py", "configured_moe_dp_size"): (
+        "the same dict already carries the live moe_dp_size under 'dp'; this entry "
+        "is the configured intent"
+    ),
+    ("srt/utils/cuda_ipc_transport_utils.py", "configured_tp_size"): (
+        "runs in the tokenizer process, which has no parallel groups at all"
+    ),
+    ("srt/models/kimi_k25.py", "configured_tp_size"): (
+        "the IPC refcount has to name the same number the recycler waits on, and "
+        "that waiter (MmItemMemoryPool.try_to_recycle) reads configured_tp_size() "
+        "because it runs in the tokenizer process; a refcount taken from the live "
+        "attention subgroup would strand items in the bounded pool"
+    ),
+    ("srt/models/kimi_k3.py", "configured_tp_size"): (
+        "same as kimi_k25: the IPC refcount must agree with the recycler's waiter"
+    ),
+}
+
+# A dynamic read whose name is set nowhere in the tree, so the predicate it
+# feeds is inert (the ``getattr`` default decides it). Converting it would mean
+# choosing what it should have named, which is the CP path's call, not this
+# sweep's -- so it is listed here rather than silently counted or "fixed".
+_INERT_DYNAMIC_READS = frozenset({("srt/layers/cp/base.py", "_is_dsa_model_arch")})
 
 _DIRECT_BASELINE = 0
 _ALIAS_BASELINE = 0
 
 
 def _is_global_call(node) -> bool:
-    return (
+    """``get_server_args()`` however it is spelled: bare, or module-qualified
-        isinstance(node, ast.Call)
+    (``ctx.get_server_args()``), which an ast.Name check alone would miss."""
-        and isinstance(node.func, ast.Name)
+    if not isinstance(node, ast.Call):
-        and node.func.id == "get_server_args"
+        return False
-    )
+    func = node.func
+    if isinstance(func, ast.Name):
+        return func.id == "get_server_args"
+    return isinstance(func, ast.Attribute) and func.attr == "get_server_args"
 
 
-def _collect(rel: str, tree: ast.AST):
+def _collect(rel: str, tree: ast.AST, inert: frozenset = frozenset()):
-    """The (direct, alias) field reads in one module."""
+    """The (direct, alias) field reads in one module.
+
+    ``inert`` names the fields listed in ``_INERT_DYNAMIC_READS`` for this file;
+    they are dropped here, at the point the read is recognized, so the filter
+    matches on the field name rather than on the rendered message.
+    """
     direct, alias = [], []
 
     def counted(attr: str) -> bool:
-        return attr not in _DERIVED_MEMBERS and (rel, attr) not in _CONFIG_INTENT_SIZES
+        return attr not in inert
+
+    def _getattr_name(node):
+        """``getattr(<record>, "field")`` names a field just as ``.field`` does;
+        matching only ast.Attribute would let a dynamic read walk past."""
+        if not (
+            isinstance(node, ast.Call)
+            and isinstance(node.func, ast.Name)
+            and node.func.id == "getattr"
+            and len(node.args) >= 2
+            and isinstance(node.args[1], ast.Constant)
+            and isinstance(node.args[1].value, str)
+        ):
+            return None
+        return node.args[1].value
 
     for node in ast.walk(tree):
         if (
@@ -105,17 +166,54 @@ def _collect(rel: str, tree: ast.AST):
         ):
             direct.append(f"{rel}:{node.lineno}: get_server_args().{node.attr}")
 
+        name = _getattr_name(node)
+        if name is not None and _is_global_call(node.args[0]) and counted(name):
+            direct.append(f"{rel}:{node.lineno}: getattr(get_server_args(), {name!r})")
+
         if not isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
             continue
         params = {a.arg for a in list(node.args.args) + list(node.args.kwonlyargs)}
         bound = {}
         for inner in ast.walk(node):
-            if isinstance(inner, ast.Assign) and _is_global_call(inner.value):
+            # ``sa = get_server_args()`` and its annotated form
-                for target in inner.targets:
+            # ``sa: ServerArgs = get_server_args()``.
-                    if isinstance(target, ast.Name) and target.id not in params:
+            if isinstance(inner, (ast.Assign, ast.AnnAssign)) and _is_global_call(
-                        bound.setdefault(target.id, inner.lineno)
+                getattr(inner, "value", None)
+            ):
+                targets = (
+                    inner.targets if isinstance(inner, ast.Assign) else [inner.target]
+                )
+                for target in targets:
+                    if not isinstance(target, ast.Name):
+                        continue
+                    # A parameter reassigned from the global is the
+                    # optional-injection shape (``f(server_args=None)`` then
+                    # ``server_args = get_server_args()``): the reads that
+                    # follow are global reads wearing a parameter's name, so
+                    # they count from the bind on.
+                    bound.setdefault(target.id, inner.lineno)
         if not bound:
             continue
+        # A copy of an alias reaches the same record (``cfg = sa`` after
+        # ``sa = get_server_args()``), so follow Name-to-Name assignments to a
+        # fixpoint. Deeper indirection (through containers, attributes of
+        # other objects, cross-scope copies) stays census-tool territory.
+        changed = True
+        while changed:
+            changed = False
+            for inner in ast.walk(node):
+                if not isinstance(inner, (ast.Assign, ast.AnnAssign)):
+                    continue
+                value = getattr(inner, "value", None)
+                if not (isinstance(value, ast.Name) and value.id in bound):
+                    continue
+                targets = (
+                    inner.targets if isinstance(inner, ast.Assign) else [inner.target]
+                )
+                for target in targets:
+                    if isinstance(target, ast.Name) and target.id not in bound:
+                        bound[target.id] = inner.lineno
+                        changed = True
         for inner in ast.walk(node):
             if (
                 isinstance(inner, ast.Attribute)
@@ -128,6 +226,170 @@ def _collect(rel: str, tree: ast.AST):
                     f"{rel}:{inner.lineno}: {inner.value.id}.{inner.attr} "
                     f"(bound from get_server_args() at line {bound[inner.value.id]})"
                 )
+            name = _getattr_name(inner)
+            if (
+                name is not None
+                and isinstance(inner.args[0], ast.Name)
+                and inner.args[0].id in bound
+                and inner.lineno >= bound[inner.args[0].id]
+                and counted(name)
+            ):
+                alias.append(
+                    f"{rel}:{inner.lineno}: getattr({inner.args[0].id}, {name!r}) "
+                    f"(bound from get_server_args() at line {bound[inner.args[0].id]})"
+                )
+    # A module-level alias is visible to every function in the file, so it needs
+    # its own pass -- the per-function scan above deliberately does not reach
+    # across scopes.
+    module_bound = {}
+    module_stack = list(tree.body)
+    while module_stack:
+        stmt = module_stack.pop()
+        # A module-level bind can sit inside an `if` / `try` / `with`, so the
+        # walk descends into those bodies -- but not into a nested function or
+        # class, whose binds are that scope's own.
+        if isinstance(
+            stmt, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef, ast.Lambda)
+        ):
+            continue
+        module_stack.extend(ast.iter_child_nodes(stmt))
+        if isinstance(stmt, (ast.Assign, ast.AnnAssign)) and _is_global_call(
+            getattr(stmt, "value", None)
+        ):
+            targets = stmt.targets if isinstance(stmt, ast.Assign) else [stmt.target]
+            for target in targets:
+                if isinstance(target, ast.Name):
+                    module_bound.setdefault(target.id, stmt.lineno)
+    if module_bound:
+        # Shadowing is per lexical scope: a function with its own `sa` hides the
+        # module alias *inside that function only*. Aggregating the names
+        # file-wide would suppress every read in the module, including the
+        # top-level ones and the ones in functions that do resolve to the alias.
+        parents = {}
+        scope_binds = {}
+        stack = [tree]
+        while stack:
+            node = stack.pop()
+            enclosing = parents.get(id(node))
+            for child in ast.iter_child_nodes(node):
+                parents[id(child)] = (
+                    node
+                    if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+                    else enclosing
+                )
+                stack.append(child)
+            if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
+                names = {
+                    a.arg for a in list(node.args.args) + list(node.args.kwonlyargs)
+                }
+                # Only this scope's own stores: a nested function's local `sa`
+                # shadows the alias inside *that* function, not in its parent.
+                pending = list(node.body)
+                while pending:
+                    inner = pending.pop()
+                    if isinstance(
+                        inner,
+                        (
+                            ast.FunctionDef,
+                            ast.AsyncFunctionDef,
+                            ast.Lambda,
+                            ast.ClassDef,
+                        ),
+                    ):
+                        continue
+                    if isinstance(inner, ast.Name) and isinstance(inner.ctx, ast.Store):
+                        names.add(inner.id)
+                    pending.extend(ast.iter_child_nodes(inner))
+                scope_binds[id(node)] = names
+
+        def _shadowed(node, name):
+            scope = parents.get(id(node))
+            while scope is not None:
+                if name in scope_binds.get(id(scope), ()):
+                    return True
+                scope = parents.get(id(scope))
+            return False
+
+        for node in ast.walk(tree):
+            base = attr = None
+            if (
+                isinstance(node, ast.Attribute)
+                and isinstance(node.value, ast.Name)
+                and node.value.id in module_bound
+            ):
+                base, attr = node.value.id, node.attr
+                shown = f"{base}.{attr}"
+            else:
+                attr_name = _getattr_name(node)
+                if (
+                    attr_name is not None
+                    and isinstance(node.args[0], ast.Name)
+                    and node.args[0].id in module_bound
+                ):
+                    base, attr = node.args[0].id, attr_name
+                    shown = f"getattr({base}, {attr!r})"
+            if base and not _shadowed(node, base) and counted(attr):
+                alias.append(
+                    f"{rel}:{node.lineno}: {shown} "
+                    f"(module-level bind from get_server_args() at line "
+                    f"{module_bound[base]})"
+                )
+
+    # An alias parked on an instance attribute (``self._sa = get_server_args()``
+    # in one method, ``self._sa.field`` in another) reaches the same slot and
+    # crosses function scopes, so it is collected per class rather than per
+    # function.
+    for node in ast.walk(tree):
+        if not isinstance(node, ast.ClassDef):
+            continue
+        attr_bound = {}
+        for inner in ast.walk(node):
+            if isinstance(inner, (ast.Assign, ast.AnnAssign)) and _is_global_call(
+                getattr(inner, "value", None)
+            ):
+                targets = (
+                    inner.targets if isinstance(inner, ast.Assign) else [inner.target]
+                )
+                for target in targets:
+                    if (
+                        isinstance(target, ast.Attribute)
+                        and isinstance(target.value, ast.Name)
+                        and target.value.id in ("self", "cls")
+                    ):
+                        attr_bound.setdefault(
+                            (target.value.id, target.attr), inner.lineno
+                        )
+        if not attr_bound:
+            continue
+
+        def _bound_attr(value):
+            """``self._sa`` when that attribute was bound from the global."""
+            if (
+                isinstance(value, ast.Attribute)
+                and isinstance(value.value, ast.Name)
+                and (value.value.id, value.attr) in attr_bound
+            ):
+                return (value.value.id, value.attr)
+            return None
+
+        for inner in ast.walk(node):
+            key = shown = None
+            if isinstance(inner, ast.Attribute):
+                key = _bound_attr(inner.value)
+                if key is not None and counted(inner.attr):
+                    shown = f"{key[0]}.{key[1]}.{inner.attr}"
+            else:
+                name = _getattr_name(inner)
+                if name is not None:
+                    key = _bound_attr(inner.args[0])
+                    if key is not None and counted(name):
+                        shown = f"getattr({key[0]}.{key[1]}, {name!r})"
+            if shown is not None:
+                alias.append(
+                    f"{rel}:{inner.lineno}: {shown} "
+                    f"(attribute bind from get_server_args() at line "
+                    f"{attr_bound[key]})"
+                )
     return direct, alias
 
 
@@ -135,11 +397,14 @@ def _field_reads():
     direct, alias = [], []
     for path in sorted(_PACKAGE_ROOT.rglob("*.py")):
         rel = path.relative_to(_PACKAGE_ROOT).as_posix()
+        if rel.startswith(_SLOT_OWNERS):
+            continue
         try:
             tree = ast.parse(path.read_text())
         except SyntaxError:
             continue
-        module_direct, module_alias = _collect(rel, tree)
+        inert = frozenset(name for path_, name in _INERT_DYNAMIC_READS if path_ == rel)
+        module_direct, module_alias = _collect(rel, tree, inert)
         direct += module_direct
         alias += module_alias
     return direct, alias
@@ -167,5 +432,90 @@ class TestGlobalConfigReadRatchet(CustomTestCase):
         self._check("alias-form", alias, _ALIAS_BASELINE)
 
 
+class TestConfiguredSizeCallSites(CustomTestCase):
+    """The configured-vs-live exceptions are enumerated, with reasons.
+
+    ``configured_*_size()`` answers what the user asked for where
+    ``get_parallel()`` would answer what the process ended up with. Each such
+    exception is listed above with why the live property cannot serve it, and
+    this case fails if the code and that list disagree.
+
+    The unit is **(file, accessor)**, not the individual call: a second
+    `configured_pp_size()` in a file already registered for it collapses into
+    the same entry, so the reason has to cover the file's use of that accessor
+    rather than one line. A new file, or a new accessor in a listed file, is
+    what this catches -- in either call form (bare or module-qualified).
+    """
+
+    def test_the_call_sites_match_the_documented_set(self):
+        found = set()
+        for path in sorted(_PACKAGE_ROOT.rglob("*.py")):
+            rel = path.relative_to(_PACKAGE_ROOT).as_posix()
+            if rel.startswith(_SLOT_OWNERS):
+                continue
+            try:
+                tree = ast.parse(path.read_text())
+            except SyntaxError:
+                continue
+            for node in ast.walk(tree):
+                if not isinstance(node, ast.Call):
+                    continue
+                func = node.func
+                name = (
+                    func.id
+                    if isinstance(func, ast.Name)
+                    else (func.attr if isinstance(func, ast.Attribute) else None)
+                )
+                if name and name.startswith("configured_") and name.endswith("_size"):
+                    found.add((rel, name))
+        documented = set(_CONFIGURED_SIZE_CALL_SITES)
+        self.assertEqual(
+            documented,
+            found,
+            "configured-size call sites drifted from their documented reasons.\n"
+            f"  undocumented: {sorted(found - documented)}\n"
+            f"  stale entries: {sorted(documented - found)}",
+        )
+
+
+class TestNoRenamedAccessorImports(CustomTestCase):
+    """The scanners above match ``get_server_args`` and ``configured_*_size``
+    by their literal names, so an ``import ... as`` rename would walk a read
+    straight past both the zero baseline and the call-site registry. Renaming
+    these accessors buys nothing (the names are already short and unambiguous),
+    so it is banned outright — which is exactly what makes literal-name
+    matching sound."""
+
+    def test_the_scanned_accessors_are_never_import_renamed(self):
+        offenders = []
+        for path in sorted(_PACKAGE_ROOT.rglob("*.py")):
+            rel = path.relative_to(_PACKAGE_ROOT).as_posix()
+            try:
+                tree = ast.parse(path.read_text())
+            except SyntaxError:
+                continue
+            for node in ast.walk(tree):
+                if not isinstance(node, (ast.ImportFrom, ast.Import)):
+                    continue
+                for imported in node.names:
+                    if imported.asname is None or imported.asname == imported.name:
+                        continue
+                    base = imported.name.rsplit(".", 1)[-1]
+                    if base == "get_server_args" or (
+                        base.startswith("configured_") and base.endswith("_size")
+                    ):
+                        offenders.append(
+                            f"{rel}:{node.lineno}: {imported.name} as "
+                            f"{imported.asname}"
+                        )
+        self.assertFalse(
+            offenders,
+            "get_server_args / configured_*_size imported under another name; "
+            "the read ratchet and the configured-size registry match these "
+            "accessors by their literal names, so a rename silently escapes "
+            "both:\n" + "\n".join(offenders),
+        )
+
+
 if __name__ == "__main__":
     unittest.main()

test/registered/unit/test_runtime_context.py

@@ -5,7 +5,10 @@ from sglang.test.ci.ci_register import register_cpu_ci
 register_cpu_ci(est_time=5, suite="base-a-test-cpu")
 
 import dataclasses
+import json
 import os
+import shutil
+import tempfile
 import unittest
 from unittest.mock import patch
 
@@ -20,8 +23,10 @@ from sglang.srt.runtime_context import (
     get_flags,
     get_parallel,
     get_server_args,
+    max_speculative_num_draft_tokens,
     reset_context,
 )
+from sglang.srt.server_args import ServerArgs
 from sglang.test.test_utils import CustomTestCase
 
 _PS = "sglang.srt.distributed.parallel_state"
@@ -378,6 +383,14 @@ class _FakeResolvedArgs:
     sampling_backend: A[
         str | None, Arg(help="s", resolvable=True), NS("exec.kernel")
     ] = None
+    attention_backend: A[str | None, Arg(help="ab"), NS("exec.kernel")] = None
+    prefill_attention_backend: A[str | None, Arg(help="pab"), NS("exec.kernel")] = None
+    decode_attention_backend: A[str | None, Arg(help="dab"), NS("exec.kernel")] = None
+    disable_radix_cache: A[bool, Arg(help="drc"), NS("memory")] = False
+    mamba_radix_cache_strategy: A[str, Arg(help="mrcs"), NS("exec.mamba")] = "auto"
+    speculative_num_draft_tokens: A[int | None, Arg(help="d"), NS("spec")] = None
+    speculative_adaptive: A[bool, Arg(help="a"), NS("spec")] = False
+    speculative_adaptive_config: A[str | None, Arg(help="c"), NS("spec")] = None
     _resolved_overrides: list = dataclasses.field(default_factory=list)
 
 
@@ -965,5 +978,180 @@ class TestPublishLifecycle(_IsolatedServerArgs):
         self.assertFalse(get_flags().capture.enable_torch_compile)
 
 
+class TestDerivedPredicatesAgreeAcrossTiers(_IsolatedServerArgs):
+    """One definition per predicate, checked rather than asserted in prose.
+
+    Each of these exists twice by construction -- once over a config-shaped
+    object (the resolution pipeline's `*_of` helper, which `ServerArgs`
+    delegates to) and once over the published bags. The pair must agree on
+    every input, or a decision made before publish differs from the same
+    decision made after it.
+    """
+
+    _STRATEGIES = ("auto", "no_buffer", "extra_buffer", "extra_buffer_lazy")
+
+    def test_mamba_extra_buffer_matches_the_member(self):
+        from sglang.srt.runtime_context import (
+            mamba_extra_buffer_enabled,
+            mamba_extra_buffer_lazy_enabled,
+        )
+
+        for disable_radix_cache in (False, True):
+            for strategy in self._STRATEGIES:
+                with self.subTest(radix=disable_radix_cache, strategy=strategy):
+                    args = _FakeResolvedArgs(
+                        disable_radix_cache=disable_radix_cache,
+                        mamba_radix_cache_strategy=strategy,
+                    )
+                    get_context().set_server_args(args)
+                    self.assertEqual(
+                        ServerArgs.enable_mamba_extra_buffer(args),
+                        mamba_extra_buffer_enabled(),
+                    )
+                    self.assertEqual(
+                        ServerArgs.enable_mamba_extra_buffer_lazy(args),
+                        mamba_extra_buffer_lazy_enabled(),
+                    )
+
+    def test_attention_backends_match_the_member(self):
+        from sglang.srt.runtime_context import attention_backends
+
+        backends = (None, "fa3", "triton")
+        for base in backends:
+            for prefill in backends:
+                for decode in backends:
+                    with self.subTest(base=base, prefill=prefill, decode=decode):
+                        args = _FakeResolvedArgs(
+                            attention_backend=base,
+                            prefill_attention_backend=prefill,
+                            decode_attention_backend=decode,
+                        )
+                        get_context().set_server_args(args)
+                        self.assertEqual(
+                            ServerArgs.get_attention_backends(args),
+                            attention_backends(),
+                        )
+
+
+class TestAdaptiveDraftBoundLifecycle(_IsolatedServerArgs):
+    """The adaptive draft-token bound is memoized on the config path, so the
+    memo has to end with the publication it was computed under.
+
+    Without that, a process that republishes with the same adaptive-config path
+    -- the file having been rewritten in between -- keeps the previous bound and
+    under-allocates the draft-token buffers sized from it.
+    """
+
+    def _write_config(self, steps):
+        path = os.path.join(tempfile.mkdtemp(prefix="adaptive_cfg_"), "adaptive.json")
+        self.addCleanup(shutil.rmtree, os.path.dirname(path), ignore_errors=True)
+        with open(path, "w") as handle:
+            json.dump({"1": {"candidate_steps": steps}}, handle)
+        return path
+
+    def test_republishing_recomputes_the_bound(self):
+        path = self._write_config([2])
+        get_context().set_server_args(
+            _FakeResolvedArgs(
+                speculative_num_draft_tokens=3,
+                speculative_adaptive=True,
+                speculative_adaptive_config=path,
+            )
+        )
+        self.assertEqual(max_speculative_num_draft_tokens(), 3)
+
+        with open(path, "w") as handle:
+            json.dump({"1": {"candidate_steps": [4]}}, handle)
+        # Same path, new contents: the memo must not survive the republish.
+        get_context().set_server_args(
+            _FakeResolvedArgs(
+                speculative_num_draft_tokens=3,
+                speculative_adaptive=True,
+                speculative_adaptive_config=path,
+            )
+        )
+        self.assertEqual(max_speculative_num_draft_tokens(), 5)
+
+    def test_reset_clears_the_bound(self):
+        path = self._write_config([2])
+        get_context().set_server_args(
+            _FakeResolvedArgs(
+                speculative_num_draft_tokens=3,
+                speculative_adaptive=True,
+                speculative_adaptive_config=path,
+            )
+        )
+        self.assertEqual(max_speculative_num_draft_tokens(), 3)
+        reset_context()
+        with open(path, "w") as handle:
+            json.dump({"1": {"candidate_steps": [6]}}, handle)
+        get_context().set_server_args(
+            _FakeResolvedArgs(
+                speculative_num_draft_tokens=3,
+                speculative_adaptive=True,
+                speculative_adaptive_config=path,
+            )
+        )
+        self.assertEqual(max_speculative_num_draft_tokens(), 7)
+
+
+class TestNamedAccessorsCallWhatTheyWrap(CustomTestCase):
+    """A named accessor must *call* a member that is a method.
+
+    `return get_server_args().x` hands back a bound method when `x` is defined
+    with `def`; the failure then lands far away, in whatever arithmetic the
+    caller does with it. Checked statically so accessors that need a real model
+    config are covered too.
+    """
+
+    def test_accessors_that_wrap_methods_call_them(self):
+        import ast
+        import functools
+        import inspect
+
+        import sglang.srt.runtime_context as rc
+        from sglang.srt.server_args import ServerArgs
+
+        tree = ast.parse(inspect.getsource(rc))
+        wrong = []
+        for node in tree.body:
+            if not isinstance(node, ast.FunctionDef):
+                continue
+            for inner in ast.walk(node):
+                if not (isinstance(inner, ast.Return) and inner.value is not None):
+                    continue
+                value = inner.value
+                called = isinstance(value, ast.Call)
+                target = value.func if called else value
+                if not (
+                    isinstance(target, ast.Attribute)
+                    and isinstance(target.value, ast.Call)
+                    and isinstance(target.value.func, ast.Name)
+                    and target.value.func.id == "get_server_args"
+                ):
+                    continue
+                member = getattr(ServerArgs, target.attr, None)
+                # A `property` / `functools.cached_property` member is already
+                # evaluated by the attribute access, so it is named here to keep
+                # the failure message from calling it "not a method" -- the fix
+                # for those is the opposite one.
+                kind = (
+                    "a property"
+                    if isinstance(member, (property, functools.cached_property))
+                    else "not a method"
+                )
+                if inspect.isfunction(member) and not called:
+                    wrong.append(
+                        f"{node.name}(): returns ServerArgs.{target.attr} without "
+                        "calling it, so callers get a bound method"
+                    )
+                if not inspect.isfunction(member) and called:
+                    wrong.append(
+                        f"{node.name}(): calls ServerArgs.{target.attr}, which is "
+                        f"{kind} -- the attribute access already produced the value"
+                    )
+        self.assertEqual([], wrong, "\n".join(wrong))
+
+
 if __name__ == "__main__":
     unittest.main()