Clarify ModelRunner.dp_size into attn_dp_size (#31142)

python/sglang/srt/model_executor/model_runner.py

@@ -370,7 +370,9 @@ class ModelRunner(ModelRunnerKVCacheMixin):
         self.moe_ep_rank = moe_ep_rank
         self.moe_ep_size = moe_ep_size
         self.dp_rank = dp_rank
-        self.dp_size = server_args.dp_size if server_args.enable_dp_attention else 1
+        self.attn_dp_size = (
+            server_args.dp_size if server_args.enable_dp_attention else 1
+        )
         self.pp_rank = pp_rank
         self.pp_size = pp_size
         self.attn_cp_rank = attn_cp_rank
@@ -1280,7 +1282,7 @@ class ModelRunner(ModelRunnerKVCacheMixin):
             )
             initialize_model_parallel(
                 tensor_model_parallel_size=self.tp_size,
-                attention_data_parallel_size=self.dp_size,
+                attention_data_parallel_size=self.attn_dp_size,
                 pipeline_model_parallel_size=self.pp_size,
                 expert_model_parallel_size=self.moe_ep_size,
                 attention_context_model_parallel_size=self.attn_cp_size,
@@ -3012,7 +3014,9 @@ class ModelRunner(ModelRunnerKVCacheMixin):
         # Try msprob debugger
         if self.msprobe_debugger is not None:
             rank_id = (
-                self.gpu_id if self.dp_size is not None and self.dp_size > 1 else None
+                self.gpu_id
+                if self.attn_dp_size is not None and self.attn_dp_size > 1
+                else None
             )
             self.msprobe_debugger.start(model=self.model, rank_id=rank_id)
 

python/sglang/srt/model_executor/model_runner_kv_cache_mixin.py

@@ -168,7 +168,7 @@ class ModelRunnerKVCacheMixin:
                 ratio = self._calculate_mamba_ratio()
                 capped_reqs = min(
                     server_args.max_running_requests
-                    // (self.dp_size if server_args.enable_dp_attention else 1),
+                    // (self.attn_dp_size if server_args.enable_dp_attention else 1),
                     server_args.max_mamba_cache_size // ratio,
                 )
                 intermediate_size = (
@@ -226,7 +226,7 @@ class ModelRunnerKVCacheMixin:
                 # so the return value only has main_state subtracted from total
                 capped_reqs = min(
                     server_args.max_running_requests
-                    // (self.dp_size if server_args.enable_dp_attention else 1),
+                    // (self.attn_dp_size if server_args.enable_dp_attention else 1),
                     server_args.max_mamba_cache_size // ratio,
                 )
                 intermediate_size = per_req * capped_reqs * D
@@ -1353,7 +1353,7 @@ class ModelRunnerKVCacheMixin:
 
         max_num_reqs = self.server_args.max_running_requests
         if max_num_reqs is not None:
-            requested_per_worker = max_num_reqs // self.dp_size
+            requested_per_worker = max_num_reqs // self.attn_dp_size
             max_num_reqs = min(requested_per_worker, token_capacity // 2)
         else:
             requested_per_worker = None

python/sglang/srt/speculative/eagle_draft_cuda_graph_runner.py

@@ -107,7 +107,7 @@ class EAGLEDraftCudaGraphRunner(DecodeCudaGraphRunner):
         self.device = model_runner.device
         self.device_module = torch.get_device_module(self.device)
         self.tp_size = model_runner.tp_size
-        self.dp_size = model_runner.dp_size
+        self.attn_dp_size = model_runner.attn_dp_size
         self.pp_size = model_runner.server_args.pp_size
         self.enable_torch_compile = get_flags().capture.enable_torch_compile
         self.disable_padding = model_runner.server_args.disable_cuda_graph_padding
@@ -210,10 +210,10 @@ class EAGLEDraftCudaGraphRunner(DecodeCudaGraphRunner):
             if self.require_gathered_buffer:
                 if self.require_mlp_tp_gather:
                     global_num_tokens_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                     global_num_tokens_for_logprob_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                 else:
                     assert self.require_attn_tp_gather
@@ -350,7 +350,7 @@ class EAGLEDraftCudaGraphRunner(DecodeCudaGraphRunner):
         )
 
         if self.require_mlp_tp_gather:
-            global_num_tokens_cpu = [num_tokens] * self.dp_size
+            global_num_tokens_cpu = [num_tokens] * self.attn_dp_size
         elif self.require_attn_tp_gather:
             global_num_tokens_cpu = [num_tokens]
         else:

python/sglang/srt/speculative/eagle_draft_extend_cuda_graph_runner.py

@@ -96,7 +96,7 @@ class EAGLEDraftExtendCudaGraphRunner(DecodeCudaGraphRunner):
         self.device = model_runner.device
         self.device_module = torch.get_device_module(self.device)
         self.tp_size = model_runner.tp_size
-        self.dp_size = model_runner.dp_size
+        self.attn_dp_size = model_runner.attn_dp_size
         self.pp_size = model_runner.server_args.pp_size
         self.enable_torch_compile = get_flags().capture.enable_torch_compile
         self.disable_padding = model_runner.server_args.disable_cuda_graph_padding
@@ -193,10 +193,10 @@ class EAGLEDraftExtendCudaGraphRunner(DecodeCudaGraphRunner):
             if self.require_gathered_buffer:
                 if self.require_mlp_tp_gather:
                     global_num_tokens_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                     global_num_tokens_for_logprob_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                 else:
                     assert self.require_attn_tp_gather
@@ -339,7 +339,7 @@ class EAGLEDraftExtendCudaGraphRunner(DecodeCudaGraphRunner):
         num_tokens_for_logprob = num_tokens
 
         if self.require_mlp_tp_gather:
-            global_num_tokens_cpu = [num_tokens] * self.dp_size
+            global_num_tokens_cpu = [num_tokens] * self.attn_dp_size
         elif self.require_attn_tp_gather:
             global_num_tokens_cpu = [num_tokens]
         else:

python/sglang/srt/speculative/frozen_kv_mtp_cuda_graph_runner.py

@@ -92,7 +92,7 @@ class FrozenKVMTPCudaGraphRunner(DecodeCudaGraphRunner):
         self.require_mlp_sync = require_mlp_sync(model_runner.server_args)
         self.require_attn_tp_gather = require_attn_tp_gather(model_runner.server_args)
         self.tp_size = self.model_runner.tp_size
-        self.dp_size = self.model_runner.dp_size
+        self.attn_dp_size = self.model_runner.attn_dp_size
         self.pp_size = model_runner.server_args.pp_size
         self.speculative_num_steps = model_runner.server_args.speculative_num_steps
         self.topk = model_runner.server_args.speculative_eagle_topk
@@ -149,10 +149,10 @@ class FrozenKVMTPCudaGraphRunner(DecodeCudaGraphRunner):
             if self.require_gathered_buffer:
                 if self.require_mlp_tp_gather:
                     global_num_tokens_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                     global_num_tokens_for_logprob_gpu = torch.zeros(
-                        (self.dp_size,), dtype=torch.int32
+                        (self.attn_dp_size,), dtype=torch.int32
                     )
                 else:
                     assert self.require_attn_tp_gather
@@ -240,7 +240,7 @@ class FrozenKVMTPCudaGraphRunner(DecodeCudaGraphRunner):
         bonus_tokens = buffers.bonus_tokens[:request_bs]
 
         if self.require_mlp_tp_gather:
-            global_num_tokens_cpu = [expanded_bs] * self.dp_size
+            global_num_tokens_cpu = [expanded_bs] * self.attn_dp_size
         elif self.require_attn_tp_gather:
             global_num_tokens_cpu = [expanded_bs]
         else: