[PD] Add PD support for hybrid model (Qwen3-Next, DeepSeek V3.2 Exp) (#10912)

Signed-off-by: Shangming Cai <csmthu@gmail.com>
Co-authored-by: hzh0425 <hzh0425@apache.org>
Co-authored-by: ZeldaHuang <hzm414167@alibaba-inc.com>

test/srt/run_suite.py

@@ -163,6 +163,7 @@ suites = {
         TestFile("test_deepseek_v3_basic.py", 275),
         TestFile("test_deepseek_v3_mtp.py", 275),
         TestFile("test_disaggregation_different_tp.py", 600),
+        TestFile("test_disaggregation_hybrid_attention.py", 200),
         TestFile("test_disaggregation_pp.py", 140),
     ],
     "per-commit-4-gpu-b200": [

test/srt/test_disaggregation_hybrid_attention.py

@@ -0,0 +1,83 @@
+import os
+import unittest
+from types import SimpleNamespace
+
+from sglang.srt.environ import envs
+from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.test_disaggregation_utils import TestDisaggregationBase
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    popen_launch_pd_server,
+)
+
+
+class TestDisaggregationHybridAttentionMamba(TestDisaggregationBase):
+    @classmethod
+    def setUpClass(cls):
+        super().setUpClass()
+        cls.model = "Qwen/Qwen3-Next-80B-A3B-Instruct"
+
+        # Non blocking start servers
+        cls.start_prefill()
+        cls.start_decode()
+
+        # Block until both
+        cls.wait_server_ready(cls.prefill_url + "/health")
+        cls.wait_server_ready(cls.decode_url + "/health")
+
+        cls.launch_lb()
+
+    @classmethod
+    def start_prefill(cls):
+        prefill_args = [
+            "--trust-remote-code",
+            "--disaggregation-mode",
+            "prefill",
+            "--tp",
+            "4",
+        ]
+        prefill_args += cls.transfer_backend + cls.rdma_devices
+        cls.process_prefill = popen_launch_pd_server(
+            cls.model,
+            cls.prefill_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=prefill_args,
+        )
+
+    @classmethod
+    def start_decode(cls):
+        decode_args = [
+            "--trust-remote-code",
+            "--disaggregation-mode",
+            "decode",
+            "--tp",
+            "4",
+            "--base-gpu-id",
+            "4",
+        ]
+        decode_args += cls.transfer_backend + cls.rdma_devices
+        cls.process_decode = popen_launch_pd_server(
+            cls.model,
+            cls.decode_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=decode_args,
+        )
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host=f"http://{self.base_host}",
+            port=int(self.lb_port),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(f"Evaluation metrics: {metrics}")
+
+        self.assertGreater(metrics["accuracy"], 0.93)
+
+
+if __name__ == "__main__":
+    unittest.main()

test/srt/test_mamba_unittest.py

@@ -42,6 +42,7 @@ class TestMamba(unittest.TestCase):
             full_attention_layer_ids=full_attention_layer_ids,
             enable_kvcache_transpose=False,
             device=device,
+            mamba_pool=None,
         )
         assert pool._transfer_full_attention_id(global_interval - 1) == 0
         assert pool._transfer_full_attention_id(2 * global_interval - 1) == 1
@@ -173,6 +174,7 @@ class TestMamba(unittest.TestCase):
             full_attention_layer_ids=full_attention_layer_ids,
             enable_kvcache_transpose=False,
             device=device,
+            mamba_pool=req_to_token_pool.mamba_pool,
         )
 
         # setup token to kv pool allocator