[PD] Add simple unit test for disaggregation feature (#5654)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

.github/workflows/pr-test.yml

@@ -252,6 +252,24 @@ jobs:
           cd test/srt
           python3 test_moe_eval_accuracy_large.py
 
+  unit-test-backend-pd:
+    if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') &&
+        github.event.pull_request.draft == false
+    runs-on: 8-gpu-runner
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install dependencies
+        run: |
+          bash scripts/ci_install_dependency_8_gpu.sh
+
+      - name: Run test
+        timeout-minutes: 10
+        run: |
+          cd test/srt
+          python3 -m unittest test_disaggregation.TestDisaggregationMooncake.test_gsm8k
+
   large-scale-test-8-gpu:
     if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') &&
         github.event.pull_request.draft == false

python/sglang/test/test_utils.py

@@ -478,6 +478,81 @@ def popen_launch_server(
     raise TimeoutError("Server failed to start within the timeout period.")
 
 
+def popen_launch_pd_server(
+    model: str,
+    base_url: str,
+    timeout: float,
+    api_key: Optional[str] = None,
+    other_args: list[str] = (),
+    env: Optional[dict] = None,
+    return_stdout_stderr: Optional[tuple] = None,
+):
+    _, host, port = base_url.split(":")
+    host = host[2:]
+
+    command = "sglang.launch_server"
+
+    command = [
+        "python3",
+        "-m",
+        command,
+        "--model-path",
+        model,
+        *[str(x) for x in other_args],
+    ]
+
+    command.extend(
+        [
+            "--host",
+            host,
+            "--port",
+            port,
+        ]
+    )
+
+    if api_key:
+        command += ["--api-key", api_key]
+
+    print(f"command={' '.join(command)}")
+
+    if return_stdout_stderr:
+        process = subprocess.Popen(
+            command,
+            stdout=return_stdout_stderr[0],
+            stderr=return_stdout_stderr[1],
+            env=env,
+            text=True,
+        )
+    else:
+        process = subprocess.Popen(command, stdout=None, stderr=None, env=env)
+
+    start_time = time.time()
+    with requests.Session() as session:
+        while time.time() - start_time < timeout:
+            try:
+                headers = {
+                    "Content-Type": "application/json; charset=utf-8",
+                    "Authorization": f"Bearer {api_key}",
+                }
+                response = session.get(
+                    f"{base_url}/health",
+                    headers=headers,
+                )
+                if response.status_code == 200:
+                    return process
+            except requests.RequestException:
+                pass
+
+            return_code = process.poll()
+            if return_code is not None:
+                raise Exception(f"Server unexpectedly exits ({return_code=}).")
+
+            time.sleep(10)
+
+    kill_process_tree(process.pid)
+    raise TimeoutError("Server failed to start within the timeout period.")
+
+
 def run_with_timeout(
     func: Callable,
     args: tuple = (),

scripts/ci_install_dependency_8_gpu.sh

@@ -53,6 +53,9 @@ pip install -e lmms-eval/
 # Install FlashMLA for attention backend tests
 pip install git+https://github.com/deepseek-ai/FlashMLA.git
 
+# Install mooncake-transfer-engine
+pip install mooncake-transfer-engine
+
 # Install system dependencies
 # apt-get update && apt-get install -y libibverbs-dev infiniband-diags libmlx5-1 rdma-core openssh-server perftest ibverbs-providers libibumad3 libibverbs1 libnl-3-200 libnl-route-3-200 librdmacm1 rdma-core-dev infiniband-diags-dev libibverbs-dev libibverbs-utils librdmacm-dev librdmacm-utils ibverbs-utils rdma-core-utils
 apt install curl wget git sudo libibverbs-dev -y

test/srt/run_suite.py

@@ -85,6 +85,9 @@ suites = {
         TestFile("test_w8a8_quantization.py", 46),
         TestFile("models/lora/test_lora_cuda_graph.py", 250),
     ],
+    "per-commit-pd": [
+        TestFile("test_disaggregation.py", 90),
+    ],
     "per-commit-2-gpu": [
         TestFile("models/lora/test_lora_tp.py", 116),
         TestFile("test_data_parallelism.py", 73),

test/srt/test_disaggregation.py

+import subprocess
+import threading
+import time
+import unittest
+from types import SimpleNamespace
+
+import requests
+import torch
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.test_utils import (
+    DEFAULT_MODEL_NAME_FOR_TEST,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_pd_server,
+    run_with_timeout,
+)
+
+
+class TestDisaggregationMooncake(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
+        cls.base_host = "127.0.0.1"
+        cls.base_port = int(DEFAULT_URL_FOR_TEST.split(":")[-1])
+        cls.lb_url = DEFAULT_URL_FOR_TEST
+        cls.prefill_url = f"http://{cls.base_host}:{cls.base_port + 100}"
+        cls.decode_url = f"http://{cls.base_host}:{cls.base_port + 200}"
+
+        run_with_timeout(cls.start_prefill, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH)
+        run_with_timeout(cls.start_decode, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH)
+
+        cls.wait_server_ready(cls.prefill_url + "/health")
+        cls.wait_server_ready(cls.decode_url + "/health")
+
+        lb_command = [
+            "python3",
+            "-m",
+            "sglang.srt.disaggregation.mini_lb",
+            "--prefill",
+            cls.prefill_url,
+            "--decode",
+            cls.decode_url,
+            "--host",
+            cls.base_host,
+            "--port",
+            str(cls.base_port),
+        ]
+
+        print("Starting load balancer:", " ".join(lb_command))
+        cls.process_lb = subprocess.Popen(
+            lb_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE
+        )
+        cls.wait_server_ready(cls.lb_url + "/health")
+
+    @classmethod
+    def start_prefill(cls):
+        prefill_args = [
+            "--trust-remote-code",
+            "--disaggregation-mode",
+            "prefill",
+            "--host",
+            cls.base_host,
+            "--port",
+            str(cls.base_port + 100),
+            "--tp",
+            "4",
+        ]
+        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",
+            "--host",
+            cls.base_host,
+            "--port",
+            str(cls.base_port + 200),
+            "--tp",
+            "4",
+            "--base-gpu-id",
+            "4",
+        ]
+        cls.process_decode = popen_launch_pd_server(
+            cls.model,
+            cls.decode_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=decode_args,
+        )
+
+    @classmethod
+    def wait_server_ready(cls, url, timeout=60):
+        start_time = time.time()
+        while True:
+            try:
+                response = requests.get(url)
+                if response.status_code == 200:
+                    print(f"Server {url} is ready")
+                    return
+            except Exception:
+                pass
+
+            if time.time() - start_time > timeout:
+                raise RuntimeError(f"Server {url} failed to start in {timeout}s")
+            time.sleep(1)
+
+    @classmethod
+    def tearDownClass(cls):
+        for process in [cls.process_lb, cls.process_decode, cls.process_prefill]:
+            if process:
+                try:
+                    kill_process_tree(process.pid)
+                except Exception as e:
+                    print(f"Error killing process {process.pid}: {e}")
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host="http://127.0.0.1",
+            port=int(self.lb_url.split(":")[-1]),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(f"Evaluation metrics: {metrics}")
+
+        self.assertGreater(metrics["accuracy"], 0.62)
+
+
+if __name__ == "__main__":
+    unittest.main()