Add bench_server_latency.py (#1452)

python/sglang/bench_latency.py

 """
-Benchmark the latency of a given model. It accepts arguments similar to those of launch_server.py.
+Benchmark the latency of running a single static batch.
+This script does not launch a server and uses the low-level APIs.
+It accepts arguments similar to those of launch_server.py.
 
 # Usage (latency test)
 ## with dummy weights:

python/sglang/bench_server_latency.py

+"""
+Benchmark the latency of serving a single batch with a real server.
+This script launches a server and uses the HTTP interface.
+It accepts arguments similar to those of launch_server.py.
+
+Usage:
+
+python3 -m sglang.bench_server_latency --model meta-llama/Meta-Llama-3.1-8B --batch-size 1 16 64 --input-len 1024 --output-len 8
+"""
+
+import argparse
+import dataclasses
+import itertools
+import json
+import multiprocessing
+import os
+import time
+from typing import Tuple
+
+import numpy as np
+import requests
+
+from sglang.srt.server import launch_server
+from sglang.srt.server_args import ServerArgs
+from sglang.srt.utils import kill_child_process
+
+
+@dataclasses.dataclass
+class BenchArgs:
+    run_name: str = "default"
+    batch_size: Tuple[int] = (1,)
+    input_len: Tuple[int] = (1024,)
+    output_len: Tuple[int] = (16,)
+    result_filename: str = "result.jsonl"
+
+    @staticmethod
+    def add_cli_args(parser: argparse.ArgumentParser):
+        parser.add_argument("--run-name", type=str, default=BenchArgs.run_name)
+        parser.add_argument(
+            "--batch-size", type=int, nargs="+", default=BenchArgs.batch_size
+        )
+        parser.add_argument(
+            "--input-len", type=int, nargs="+", default=BenchArgs.input_len
+        )
+        parser.add_argument(
+            "--output-len", type=int, nargs="+", default=BenchArgs.output_len
+        )
+        parser.add_argument(
+            "--result-filename", type=str, default=BenchArgs.result_filename
+        )
+
+    @classmethod
+    def from_cli_args(cls, args: argparse.Namespace):
+        # use the default value's type to case the args into correct types.
+        attrs = [(attr.name, type(attr.default)) for attr in dataclasses.fields(cls)]
+        return cls(
+            **{attr: attr_type(getattr(args, attr)) for attr, attr_type in attrs}
+        )
+
+
+def launch_server_internal(server_args):
+    try:
+        launch_server(server_args)
+    except Exception as e:
+        raise e
+    finally:
+        kill_child_process(os.getpid(), including_parent=False)
+
+
+def launch_server_process(server_args: ServerArgs):
+    proc = multiprocessing.Process(target=launch_server_internal, args=(server_args,))
+    proc.start()
+    base_url = f"http://{server_args.host}:{server_args.port}"
+    timeout = 600
+
+    start_time = time.time()
+    while time.time() - start_time < timeout:
+        try:
+            headers = {
+                "Content-Type": "application/json; charset=utf-8",
+            }
+            response = requests.get(f"{base_url}/v1/models", headers=headers)
+            if response.status_code == 200:
+                return proc, base_url
+        except requests.RequestException:
+            pass
+        time.sleep(10)
+    raise TimeoutError("Server failed to start within the timeout period.")
+
+
+def run_one_case(
+    url: str,
+    batch_size: int,
+    input_len: int,
+    output_len: int,
+    run_name: str,
+    result_filename: str,
+):
+    input_ids = [
+        [int(x) for x in np.random.randint(0, high=16384, size=(input_len,))]
+        for _ in range(batch_size)
+    ]
+
+    tic = time.time()
+    response = requests.post(
+        url + "/generate",
+        json={
+            "input_ids": input_ids,
+            "sampling_params": {
+                "temperature": 0,
+                "max_new_tokens": output_len,
+                "ignore_eos": True,
+            },
+        },
+    )
+    latency = time.time() - tic
+
+    _ = response.json()
+    output_throughput = batch_size * output_len / latency
+    overall_throughput = batch_size * (input_len + output_len) / latency
+
+    print(f"batch size: {batch_size}")
+    print(f"latency: {latency:.2f} s")
+    print(f"output throughput: {output_throughput:.2f} token/s")
+    print(f"(input + output) throughput: {overall_throughput:.2f} token/s")
+
+    if result_filename:
+        with open(result_filename, "a") as fout:
+            res = {
+                "run_name": run_name,
+                "batch_size": batch_size,
+                "input_len": input_len,
+                "output_len": output_len,
+                "latency": round(latency, 4),
+                "output_throughput": round(output_throughput, 2),
+                "overall_throughput": round(overall_throughput, 2),
+            }
+            fout.write(json.dumps(res) + "\n")
+
+
+def run_benchmark(server_args: ServerArgs, bench_args: BenchArgs):
+    proc, base_url = launch_server_process(server_args)
+
+    # warmup
+    run_one_case(
+        base_url,
+        batch_size=16,
+        input_len=1024,
+        output_len=16,
+        run_name="",
+        result_filename="",
+    )
+
+    # benchmark
+    try:
+        for bs, il, ol in itertools.product(
+            bench_args.batch_size, bench_args.input_len, bench_args.output_len
+        ):
+            run_one_case(
+                base_url,
+                bs,
+                il,
+                ol,
+                bench_args.run_name,
+                bench_args.result_filename,
+            )
+    finally:
+        kill_child_process(proc.pid)
+
+    print(f"\nResults are saved to {bench_args.result_filename}")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    ServerArgs.add_cli_args(parser)
+    BenchArgs.add_cli_args(parser)
+    # For this script, model-path is not required
+    assert (
+        parser._actions[1].option_strings[0] == "--model-path"
+    ), "options changed, this code need to be updated"
+    parser._actions[1].required = False
+    args = parser.parse_args()
+
+    server_args = ServerArgs.from_cli_args(args)
+    bench_args = BenchArgs.from_cli_args(args)
+
+    run_benchmark(server_args, bench_args)

python/sglang/bench_serving.py

@@ -2,7 +2,7 @@
 # Adapted from https://github.com/vllm-project/vllm/blob/6366efc67b0aedd2c1721c14385370e50b297fb3/benchmarks/benchmark_serving.py
 
 """
-Benchmark online serving.
+Benchmark online serving with dynamic requests.
 
 Usage:
 python3 -m sglang.bench_serving --backend sglang --num-prompt 10

python/sglang/srt/server_args.py

@@ -26,17 +26,6 @@ from sglang.srt.utils import is_hip
 logger = logging.getLogger(__name__)
 
 
-class LoRAPathAction(argparse.Action):
-    def __call__(self, parser, namespace, values, option_string=None):
-        setattr(namespace, self.dest, {})
-        for lora_path in values:
-            if "=" in lora_path:
-                name, path = lora_path.split("=", 1)
-                getattr(namespace, self.dest)[name] = path
-            else:
-                getattr(namespace, self.dest)[lora_path] = lora_path
-
-
 @dataclasses.dataclass
 class ServerArgs:
     # Model and tokenizer
@@ -619,3 +608,14 @@ class PortArgs:
     controller_port: int
     detokenizer_port: int
     nccl_ports: List[int]
+
+
+class LoRAPathAction(argparse.Action):
+    def __call__(self, parser, namespace, values, option_string=None):
+        setattr(namespace, self.dest, {})
+        for lora_path in values:
+            if "=" in lora_path:
+                name, path = lora_path.split("=", 1)
+                getattr(namespace, self.dest)[name] = path
+            else:
+                getattr(namespace, self.dest)[lora_path] = lora_path

python/sglang/test/few_shot_gsm8k.py

@@ -44,7 +44,7 @@ def get_answer_value(answer_str):
         return INVALID
 
 
-def main(args):
+def run_eval(args):
     # Select backend
     set_default_backend(RuntimeEndpoint(f"{args.host}:{args.port}"))
 
@@ -119,6 +119,12 @@ def main(args):
     # Dump results
     dump_state_text("tmp_output_gsm8k.txt", states)
 
+    return {
+        "accuracy": acc,
+        "latency": latency,
+        "output_throughput": output_throughput,
+    }
+
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
@@ -129,4 +135,4 @@ if __name__ == "__main__":
     parser.add_argument("--host", type=str, default="http://127.0.0.1")
     parser.add_argument("--port", type=int, default=30000)
     args = parser.parse_args()
-    main(args)
+    run_eval(args)