Add DCP to runtime parallel context (#30478)

python/sglang/kernels/ops/kvcache/mla_buffer.py

@@ -5,11 +5,7 @@ import triton
 import triton.language as tl
 
 from sglang.jit_kernel.utils import is_arch_support_pdl
-from sglang.srt.layers.dcp import (
-    dcp_enabled,
-    get_attention_dcp_rank,
-    get_attention_dcp_world_size,
-)
+from sglang.srt.runtime_context import get_parallel
 
 
 @triton.jit
@@ -134,7 +130,7 @@ def set_mla_kv_buffer_triton(
         n_loc >= _TMA_BULK_STORE_MIN_LOCS
         and is_arch_support_pdl()
         and can_use_set_mla_kv_buffer(nope_bytes, rope_bytes)
-        and not dcp_enabled()
+        and not get_parallel().dcp_enabled
     ):
         jit_set_mla_kv_buffer(kv_buffer, loc, cache_k_nope, cache_k_rope)
         return
@@ -161,8 +157,8 @@ def set_mla_kv_buffer_triton(
         nope_dim,
         rope_dim,
         BLOCK=BLOCK,
-        DCP_RANK=get_attention_dcp_rank(),
-        DCP_WORLD_SIZE=get_attention_dcp_world_size(),
+        DCP_RANK=get_parallel().attn_dcp_rank,
+        DCP_WORLD_SIZE=get_parallel().attn_dcp_size,
         **pdl_kwargs,
     )
 

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

@@ -25,8 +25,6 @@ from sglang.srt.layers.attention.flashinfer_backend import (
 from sglang.srt.layers.attention.utils import assert_buffer_fits
 from sglang.srt.layers.dcp import (
     DecodeContextParallelMetadata,
-    dcp_enabled,
-    get_attention_dcp_world_size,
     update_local_kv_lens_for_dcp,
 )
 from sglang.srt.layers.dcp.planner import plan_dcp_decode_metadata
@@ -647,7 +645,9 @@ class FlashInferMLAAttnBackend(AttentionBackend):
             k_buffer[:, :, layer.v_head_dim :],
             out=o,
             # for decode forward_batch, each dcp rank computes total q and partial kv, thus, we need to return_lse for online softmax to get final attn_output
-            return_lse=forward_batch.forward_mode.is_decode() and dcp_enabled(),
+            return_lse=(
+                forward_batch.forward_mode.is_decode() and get_parallel().dcp_enabled
+            ),
         )
         if isinstance(o, tuple):
             out, lse = o
@@ -662,7 +662,7 @@ class FlashInferMLAIndicesUpdaterDecode:
         self.num_local_heads = (
             model_runner.model_config.num_attention_heads
             // get_parallel().attn_tp_size
-            * get_attention_dcp_world_size()
+            * get_parallel().attn_dcp_size
         )
         self.kv_lora_rank = model_runner.model_config.kv_lora_rank
         self.qk_nope_head_dim = model_runner.model_config.qk_nope_head_dim
@@ -733,7 +733,7 @@ class FlashInferMLAIndicesUpdaterDecode:
                 self.req_to_token.shape[1],
             )
 
-            if dcp_enabled():
+            if get_parallel().dcp_enabled:
                 plan_dcp_decode_metadata(
                     kv_lens,
                     kv_indptr,

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

@@ -17,11 +17,6 @@ from sglang.srt.layers.attention.utils import (
     create_flashmla_kv_indices_triton,
     get_num_kv_index_blocks_flashmla,
 )
-from sglang.srt.layers.dcp import (
-    dcp_enabled,
-    get_attention_dcp_rank,
-    get_attention_dcp_world_size,
-)
 from sglang.srt.layers.quantization.fp8_kernel import scaled_fp8_quant
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
 from sglang.srt.runtime_context import get_parallel
@@ -96,8 +91,8 @@ class FlashMLABackend(FlashInferMLAAttnBackend):
         self.cuda_graph_num_splits_view = None
 
         # get dcp info
-        self.dcp_world_size = get_attention_dcp_world_size()
-        self.dcp_rank = get_attention_dcp_rank()
+        self.dcp_world_size = get_parallel().attn_dcp_size
+        self.dcp_rank = get_parallel().attn_dcp_rank
 
     def init_forward_metadata_out_graph(
         self,
@@ -390,7 +385,7 @@ class FlashMLABackend(FlashInferMLAAttnBackend):
             # TODO uniform output for forward_decode and forward_extend to
             # return tuple instead of single output
             # decode context parallel needs lse to correct attn_output via online softmax
-            if dcp_enabled():
+            if get_parallel().dcp_enabled:
                 return o, lse
             return o
 

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

@@ -14,7 +14,6 @@ from sglang.srt.configs.model_config import AttentionArch
 from sglang.srt.distributed.device_communicators.pynccl_allocator import (
     use_symmetric_memory,
 )
-from sglang.srt.distributed.parallel_state import get_dcp_group
 from sglang.srt.environ import envs
 from sglang.srt.layers.attention.base_attn_backend import AttentionBackend
 from sglang.srt.layers.dcp import (
@@ -166,8 +165,8 @@ class TritonAttnBackend(AttentionBackend):
             and self.topk == 1
         )
         self.use_mla = model_runner.model_config.attention_arch == AttentionArch.MLA
-        self.dcp_size = getattr(model_runner, "dcp_size", 1)
-        self.dcp_rank = getattr(model_runner, "dcp_rank", 0)
+        self.dcp_size = get_parallel().attn_dcp_size
+        self.dcp_rank = get_parallel().attn_dcp_rank
         self.num_head = (
             model_runner.model_config.num_attention_heads // get_parallel().attn_tp_size
         ) * self.dcp_size
@@ -1387,7 +1386,7 @@ class TritonAttnBackend(AttentionBackend):
                 "DCP Triton extend does not support sliding window"
             )
 
-        group = get_dcp_group()
+        group = get_parallel().dcp_group
         q_local = q.view(-1, layer.tp_q_head_num, layer.qk_head_dim).contiguous()
         total_tokens, local_heads, _ = q_local.shape
 
@@ -1712,7 +1711,7 @@ class TritonAttnBackend(AttentionBackend):
             attn_logits = self.forward_metadata.swa_attn_logits
 
         if self.dcp_size > 1:
-            group = get_dcp_group()
+            group = get_parallel().dcp_group
             with use_symmetric_memory(group):
                 q_for_decode = q.view(
                     -1, layer.tp_q_head_num, layer.qk_head_dim

python/sglang/srt/layers/dcp/__init__.py

@@ -23,7 +23,11 @@ Only the symbols imported by code OUTSIDE this subpackage are re-exported here.
 Package-internal helpers (the @triton.jit kernels, ``CPTritonContext``,
 ``correct_attn_out``, ``create_dcp_kv_indices``, ``update_kv_lens_and_indices``,
 ``_all_gather_dcp_kv_cache``) stay private to their submodules — import them from
-``sglang.srt.layers.dcp.{kernels,comm}`` if ever needed internally."""
+``sglang.srt.layers.dcp.{kernels,comm}`` if ever needed internally.
+
+``dcp_enabled`` / ``get_attention_dcp_*`` remain compatibility exports for
+out-of-tree callers; in-tree code should use ``get_parallel().dcp_enabled`` and
+``get_parallel().attn_dcp_*``."""
 
 from sglang.srt.layers.dcp.comm import (
     all_gather_kv_cache_for_dcp,

python/sglang/srt/layers/dcp/comm.py

@@ -20,6 +20,7 @@ PR #25090 vs #14194):
   - cp_lse_ag_out_rs_mla: Triton (log2/exp2) correction / reduce-scatter
 """
 
+import warnings
 from typing import Optional
 
 import torch
@@ -27,37 +28,39 @@ import torch
 from sglang.srt.distributed.device_communicators.pynccl_allocator import (
     use_symmetric_memory,
 )
-from sglang.srt.distributed.parallel_state import (
-    GroupCoordinator,
-    get_dcp_group,
-    get_dcp_group_no_assert,
-)
+from sglang.srt.distributed.parallel_state import GroupCoordinator
 from sglang.srt.layers.dcp.kernels import CPTritonContext, correct_attn_out
 from sglang.srt.runtime_context import get_parallel
-from sglang.srt.utils import is_cuda
+
+
+def _warn_deprecated_dcp_accessor(name: str, replacement: str) -> None:
+    warnings.warn(
+        f"{name} is deprecated; use {replacement} instead.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
 
 
 def dcp_enabled() -> bool:
-    """
-    only checks whether dcp enabled for cuda platform
-    """
-    if get_dcp_group_no_assert() is None:
-        return False
-    if not is_cuda():
-        return False
-    return get_parallel().dcp_size > 1
+    """Deprecated: use ``get_parallel().dcp_enabled``."""
+    _warn_deprecated_dcp_accessor("dcp_enabled()", "get_parallel().dcp_enabled")
+    return get_parallel().dcp_enabled
 
 
 def get_attention_dcp_world_size() -> int:
-    if not dcp_enabled():
-        return 1
-    return get_parallel().dcp_size
+    """Deprecated: use ``get_parallel().attn_dcp_size``."""
+    _warn_deprecated_dcp_accessor(
+        "get_attention_dcp_world_size()", "get_parallel().attn_dcp_size"
+    )
+    return get_parallel().attn_dcp_size
 
 
 def get_attention_dcp_rank() -> int:
-    if not dcp_enabled():
-        return 0
-    return get_parallel().dcp_rank
+    """Deprecated: use ``get_parallel().attn_dcp_rank``."""
+    _warn_deprecated_dcp_accessor(
+        "get_attention_dcp_rank()", "get_parallel().attn_dcp_rank"
+    )
+    return get_parallel().attn_dcp_rank
 
 
 def _ag_lse(cp_attn_lse: torch.Tensor, cp_group: GroupCoordinator) -> torch.Tensor:
@@ -132,12 +135,13 @@ def cp_lse_ag_out_rs_mla(
 
 
 def _all_gather_dcp_kv_cache(kv_a: torch.Tensor):
-    dcp_world_size = get_parallel().dcp_size
+    parallel = get_parallel()
+    dcp_world_size = parallel.dcp_size
     # not use symmetric_memory unless torch mem_pool updated, see https://github.com/pytorch/pytorch/issues/178138
     gathered_kv_a = kv_a.new_empty(
         (kv_a.shape[0] * dcp_world_size, *kv_a.shape[1:]),
     )
-    get_dcp_group().all_gather_into_tensor(gathered_kv_a, kv_a)
+    parallel.dcp_group.all_gather_into_tensor(gathered_kv_a, kv_a)
     gathered_kv_a = (
         gathered_kv_a.reshape((dcp_world_size,) + kv_a.shape)
         .transpose(0, 1)
@@ -152,7 +156,7 @@ def all_gather_kv_cache_for_mha_chunk_extend(
     prefix_kv_lens_cpu: torch.Tensor,
     prefix_starts_cpu: torch.Tensor = None,
 ):
-    if dcp_enabled():
+    if get_parallel().dcp_enabled:
         kv_a = kv_a.unsqueeze(1)
         gathered_kv = all_gather_kv_cache_for_dcp(
             kv_a,
@@ -218,10 +222,11 @@ def all_gather_q_for_mla_decode(
     q_nope_out: torch.Tensor,
     q_pe: torch.Tensor,
 ):
-    with use_symmetric_memory(get_dcp_group()):
+    group = get_parallel().dcp_group
+    with use_symmetric_memory(group):
         # transpose q_pe and q_nope_out from [B, H, L] to [H, B, L]
         combined = torch.cat([q_pe.transpose(0, 1), q_nope_out.transpose(0, 1)], dim=-1)
-    gathered = get_dcp_group().all_gather(combined, dim=0)
+    gathered = group.all_gather(combined, dim=0)
     d_pe = q_pe.size(-1)
     d_nope = q_nope_out.size(-1)
     q_pe, q_nope_out = gathered.split([d_pe, d_nope], dim=-1)
@@ -278,11 +283,12 @@ def all_gather_kv_cache_for_dcp(
     """
     prefix_kv_a and prefix_k_pe should have same shape, expect for last dim
     """
-    if not dcp_enabled():
+    parallel = get_parallel()
+    if not parallel.dcp_enabled:
         return torch.cat([prefix_kv_a, prefix_k_pe], dim=-1)
     # 1. compute max kv_lens for each seq
-    dcp_world_size = get_parallel().dcp_size
-    dcp_rank = get_parallel().dcp_rank
+    dcp_world_size = parallel.dcp_size
+    dcp_rank = parallel.dcp_rank
 
     if prefix_starts_cpu is None:
         prefix_starts_cpu = torch.zeros_like(prefix_kv_lens_cpu)

python/sglang/srt/layers/dcp/layout.py

@@ -17,7 +17,6 @@ the owner-rule local-index filter."""
 
 import torch
 
-from sglang.srt.layers.dcp.comm import dcp_enabled
 from sglang.srt.runtime_context import get_parallel
 
 
@@ -43,10 +42,11 @@ def get_dcp_lens(
 
 
 def filter_dcp_local_kv_indices(kv_indices: torch.Tensor):
-    if dcp_enabled():
+    parallel = get_parallel()
+    if parallel.dcp_enabled:
         kv_indices = (
-            kv_indices[kv_indices % get_parallel().dcp_size == get_parallel().dcp_rank]
-            // get_parallel().dcp_size
+            kv_indices[kv_indices % parallel.dcp_size == parallel.dcp_rank]
+            // parallel.dcp_size
         )
     return kv_indices
 
@@ -59,8 +59,7 @@ def update_local_kv_lens_for_dcp(kv_len_arr):
     in-place mutation because callers (plan_dcp_decode_metadata, the FlashInfer-MLA
     cuda-graph replay path) rely on it.
     """
-    if not dcp_enabled():
+    parallel = get_parallel()
+    if not parallel.dcp_enabled:
         return
-    kv_len_arr.copy_(
-        get_dcp_lens(kv_len_arr, get_parallel().dcp_size, get_parallel().dcp_rank)
-    )
+    kv_len_arr.copy_(get_dcp_lens(kv_len_arr, parallel.dcp_size, parallel.dcp_rank))

python/sglang/srt/layers/dcp/planner.py

@@ -20,7 +20,6 @@ from typing import Optional
 
 import torch
 
-from sglang.srt.layers.dcp.comm import dcp_enabled
 from sglang.srt.layers.dcp.kernels import (
     create_dcp_kv_indices,
     update_kv_lens_and_indices,
@@ -43,7 +42,8 @@ def prepare_decode_context_parallel_metadata(
     kv_cache_device,
     create_chunked_prefix_cache_kv_indices_fn,
 ) -> Optional[DecodeContextParallelMetadata]:
-    if not dcp_enabled():
+    parallel = get_parallel()
+    if not parallel.dcp_enabled:
         return None
     # dcp_kv_buffer tokens' layout
     # [ rank0_r1.prefix_tokens, rank1_r1.prefix_tokens, ..., rank7_r1.prefix_tokens,
@@ -107,13 +107,13 @@ def prepare_decode_context_parallel_metadata(
         extend_cu_prefix_lens,
         dcp_kv_indices,
         extend_prefix_lens_sum,
-        get_parallel().dcp_size,
+        parallel.dcp_size,
     )
     dcp_local_prefix_kv_indices = (
         dcp_prefix_kv_indices[
-            dcp_prefix_kv_indices % get_parallel().dcp_size == get_parallel().dcp_rank
+            dcp_prefix_kv_indices % parallel.dcp_size == parallel.dcp_rank
         ]
-        // get_parallel().dcp_size
+        // parallel.dcp_size
     )
     dcp_kv_buffer = torch.empty(
         (
@@ -141,6 +141,7 @@ def plan_dcp_decode_metadata(
     fast_decode_kwargs: dict,
     bs: int,
 ):
+    parallel = get_parallel()
     local_kv_lens = kv_lens.clone()
     update_local_kv_lens_for_dcp(local_kv_lens)
     local_kv_lens.clamp_(min=0)
@@ -178,8 +179,8 @@ def plan_dcp_decode_metadata(
         local_kv_lens,
         local_kv_lens_cumsum,
         local_kv_indices,
-        dcp_rank=get_parallel().dcp_rank,
-        dcp_world_size=get_parallel().dcp_size,
+        dcp_rank=parallel.dcp_rank,
+        dcp_world_size=parallel.dcp_size,
         BLOCK_SIZE=BLOCK_SIZE,
     )
     kv_indices[:total_local_len] = local_kv_indices[:total_local_len]

python/sglang/srt/mem_cache/kv_cache_builder.py

@@ -25,11 +25,11 @@ from typing import TYPE_CHECKING
 
 from sglang.srt.configs.model_config import ModelImpl
 from sglang.srt.environ import envs
-from sglang.srt.layers.dcp import dcp_enabled
 from sglang.srt.managers.mm_utils import init_mm_embedding_cache
 from sglang.srt.mem_cache.cache_init_params import CacheInitParams
 from sglang.srt.mem_cache.registry import TreeCacheBuildContext, create_tree_cache
 from sglang.srt.model_loader.utils import get_resolved_model_impl
+from sglang.srt.runtime_context import get_parallel
 
 if TYPE_CHECKING:
 
@@ -204,7 +204,9 @@ def build_kv_cache(
         # TreeCache.page_size should keep the same as allocator.page_size to
         # avoid kv page eviction conflicts.
         page_size=(
-            page_size if not dcp_enabled() else token_to_kv_pool_allocator.page_size
+            page_size
+            if not get_parallel().dcp_enabled
+            else token_to_kv_pool_allocator.page_size
         ),
         is_eagle=spec_algorithm.is_eagle(),
         tp_cache_group=(

python/sglang/srt/mem_cache/memory_pool.py

@@ -50,11 +50,6 @@ from sglang.srt.layers.attention.dsa.quant_k_cache import (
     quantize_k_cache_separate,
 )
 from sglang.srt.layers.attention.dsa.utils import aiter_can_use_preshuffle_paged_mqa
-from sglang.srt.layers.dcp import (
-    dcp_enabled,
-    get_attention_dcp_rank,
-    get_attention_dcp_world_size,
-)
 from sglang.srt.layers.quantization.fp8_kernel import fp8_dtype, is_fp8_fnuz
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.mem_cache.allocator.mamba import MambaSlotAllocator
@@ -73,6 +68,7 @@ from sglang.srt.mem_cache.utils import (
     set_mla_kv_scale_buffer_triton,
 )
 from sglang.srt.platforms import current_platform
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.utils import (
     cpu_has_amx_support,
     is_cpu,
@@ -2834,10 +2830,9 @@ class MLATokenToKVPool(KVCache):
         maybe_detect_oob(loc, 0, self.size + self.page_size, "set_kv_buffer (MLA)")
         layer_id = layer.layer_id
         assert not self.dsa_kv_cache_store_fp8
-        if dcp_enabled():
-            valid_mask = (
-                loc % get_attention_dcp_world_size() == get_attention_dcp_rank()
-            )
+        parallel = get_parallel()
+        if parallel.dcp_enabled:
+            valid_mask = loc % parallel.attn_dcp_size == parallel.attn_dcp_rank
             if not valid_mask.all():
                 loc = loc[valid_mask]
                 cache_k = cache_k[valid_mask]

python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mha.py

@@ -12,7 +12,6 @@ from sglang.srt.layers.communicator import get_attn_tp_context
 from sglang.srt.layers.dcp import (
     all_gather_kv_cache_for_mha_chunk_extend,
     all_gather_kv_cache_for_mha_extend,
-    dcp_enabled,
     filter_dcp_local_kv_indices,
 )
 from sglang.srt.layers.quantization.fp8_utils import (
@@ -31,7 +30,7 @@ from sglang.srt.models.deepseek_common.utils import (
     _use_aiter_bpreshuffle_gfx95,
     _use_aiter_gfx95,
 )
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import get_parallel, get_server_args
 from sglang.srt.utils import BumpAllocator, get_bool_env_var, next_power_of_2
 
 _use_fp8_prefill_attn = (
@@ -287,7 +286,7 @@ class DeepseekMHAForwardMixin:
                 kv_a, k_pe = self._get_mla_kv_buffer_from_fp8_for_dsa(forward_batch)
             else:
                 # BF16/FP16 path: directly fetch from cache
-                if dcp_enabled():
+                if get_parallel().dcp_enabled:
                     kv_a, k_pe = all_gather_kv_cache_for_mha_extend(
                         get_token_to_kv_pool(),
                         self.attn_mha,

python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mla.py

@@ -7,7 +7,6 @@ from typing import TYPE_CHECKING, Optional
 import torch
 
 from sglang.srt.compilation.compilation_config import register_split_op
-from sglang.srt.distributed.parallel_state import get_dcp_group
 from sglang.srt.environ import envs
 from sglang.srt.layers import deep_gemm_wrapper
 from sglang.srt.layers.attention.dsa.utils import (
@@ -19,8 +18,6 @@ from sglang.srt.layers.dcp import (
     all_gather_kv_cache_for_mla_extend,
     all_gather_q_for_mla_decode,
     cp_lse_ag_out_rs_mla,
-    dcp_enabled,
-    get_attention_dcp_world_size,
 )
 from sglang.srt.layers.quantization.fp8_kernel import (
     fp8_dtype,
@@ -67,7 +64,7 @@ from sglang.srt.models.deepseek_common.utils import (
     _use_aiter_bpreshuffle_gfx95,
     _use_aiter_gfx95,
 )
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import get_parallel, get_server_args
 from sglang.srt.state_capturer.indexer_topk import (
     maybe_capture_indexer_topk,
 )
@@ -572,7 +569,7 @@ class DeepseekMLAForwardMixin:
             )
 
         # all_gather q_pe, q_nope_out,take tp8 as an example， q_pe [B, H, ROPE_DIM], q_nope_out [B, H, NOPE_DIM] gathered to [B, H * dcp_world_size, ROPE_DIM] [B, H * dcp_world_size, NOPE_DIM] for decode batch, and all gather k_pe, k_nope for extend batch.
-        if dcp_enabled():
+        if get_parallel().dcp_enabled:
             if forward_batch.forward_mode.is_decode():
                 # if forward_batch.forward_mode is decode, gather q
                 q_nope_out, q_pe = all_gather_q_for_mla_decode(
@@ -726,7 +723,10 @@ class DeepseekMLAForwardMixin:
                         topk_indices=topk_indices,
                     )
                     attn_output = fusion_plan.attn_output_buf
-                elif forward_batch.forward_mode.is_decode() and dcp_enabled():
+                elif (
+                    forward_batch.forward_mode.is_decode()
+                    and get_parallel().dcp_enabled
+                ):
                     # set return_lse=True to correct attn_output
                     attn_output, lse = self.attn_mqa_for_dcp_decode(
                         q_nope_out,
@@ -800,13 +800,15 @@ class DeepseekMLAForwardMixin:
             )
 
         # correct attn_output with respect to lse from other ranks
-        if forward_batch.forward_mode.is_decode() and dcp_enabled():
+        if forward_batch.forward_mode.is_decode() and get_parallel().dcp_enabled:
             attn_output = attn_output.view(
                 -1,
-                self.num_local_heads * get_attention_dcp_world_size(),
+                self.num_local_heads * get_parallel().attn_dcp_size,
                 self.kv_lora_rank,
             )
-            attn_output = cp_lse_ag_out_rs_mla(attn_output, lse, get_dcp_group())
+            attn_output = cp_lse_ag_out_rs_mla(
+                attn_output, lse, get_parallel().dcp_group
+            )
             attn_output = attn_output.transpose(0, 1)
         attn_output = attn_output.view(-1, self.num_local_heads, self.kv_lora_rank)
 

python/sglang/srt/models/deepseek_v2.py

@@ -74,7 +74,6 @@ from sglang.srt.layers.communicator_dsa_cp import (
     DSACPLayerCommunicator,
     maybe_prefetch_next_full_attention_kv,
 )
-from sglang.srt.layers.dcp import dcp_enabled, get_attention_dcp_world_size
 from sglang.srt.layers.dcp.planner import (
     prepare_decode_context_parallel_metadata,
 )
@@ -1724,9 +1723,9 @@ class DeepseekV2AttentionMLA(
             prefix=add_prefix("attn_mqa", prefix),
         )
         # use num_local_heads * dcp_world_size because q_nope, q_rope is all gathered from dcp ranks
-        if dcp_enabled():
+        if get_parallel().dcp_enabled:
             self.attn_mqa_for_dcp_decode = RadixAttention(
-                self.num_local_heads * get_attention_dcp_world_size(),
+                self.num_local_heads * get_parallel().attn_dcp_size,
                 self.kv_lora_rank + self.qk_rope_head_dim,
                 self.scaling,
                 num_kv_heads=1,

python/sglang/srt/runtime_context.py

@@ -13,7 +13,7 @@
 # ==============================================================================
 """A single structured accessor for process-static runtime state.
 
-``get_parallel()`` returns a ``ParallelContext`` whose attributes — tp / pp /
+``get_parallel()`` returns a ``ParallelContext`` whose attributes — tp / dcp / pp /
 moe / attn size and rank, plus the process-group handles — each delegate live to
 the canonical getter in ``distributed.parallel_state`` / ``layers.dp_attention``.
 Returned values are exactly what those getters return; this is a read-through
@@ -79,10 +79,13 @@ _PARALLEL_FIELDS = frozenset(
         "attn_tp_rank",
         "attn_cp_size",
         "attn_cp_rank",
-        "attn_dp_size",
-        "attn_dp_rank",
+        "dcp_enabled",
         "dcp_size",
         "dcp_rank",
+        "attn_dcp_size",
+        "attn_dcp_rank",
+        "attn_dp_size",
+        "attn_dp_rank",
         "world_group",
         "tp_group",
         "pp_group",
@@ -194,6 +197,27 @@ class ParallelContext:
     def dcp_rank(self) -> int:
         return self._v("dcp_rank", _ps().get_dcp_rank)
 
+    @property
+    def dcp_enabled(self) -> bool:
+        def getter():
+            if _ps().get_dcp_group_no_assert() is None:
+                return False
+            return self.dcp_size > 1
+
+        return self._v("dcp_enabled", getter)
+
+    @property
+    def attn_dcp_size(self) -> int:
+        return self._v(
+            "attn_dcp_size", lambda: self.dcp_size if self.dcp_enabled else 1
+        )
+
+    @property
+    def attn_dcp_rank(self) -> int:
+        return self._v(
+            "attn_dcp_rank", lambda: self.dcp_rank if self.dcp_enabled else 0
+        )
+
     @property
     def attn_dp_size(self) -> int:
         return self._v("attn_dp_size", _dp().get_attention_dp_size)