Files
sglang/test/registered/basic_perf/test_pp_throughput.py
T

71 lines
2.0 KiB
Python

"""Throughput of pipeline parallelism on two GPUs, decode and long prefill."""
import unittest
from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
from sglang.test.kits.perf_bench_kit import at_least, check_perf
from sglang.test.test_utils import (
DEFAULT_MOE_MODEL_NAME_FOR_TEST,
CustomTestCase,
is_in_amd_ci,
run_bench_serving,
)
register_cuda_ci(est_time=490, stage="extra-a", runner_config="2-gpu-large")
register_amd_ci(est_time=1030, suite="stage-b-test-2-gpu-large-amd")
class TestPPThroughput(CustomTestCase):
def test_pp_offline_throughput_default_decode(self):
res = run_bench_serving(
model=DEFAULT_MOE_MODEL_NAME_FOR_TEST,
num_prompts=1000,
request_rate=float("inf"),
random_input_len=1,
random_output_len=1024,
other_server_args=["--pp-size", "2"],
need_warmup=True,
seed=42,
)
check_perf(
self,
at_least(
"output_throughput", res["output_throughput"], 6250, unit="token/s"
),
)
def test_pp_long_context_prefill(self):
res = run_bench_serving(
model="meta-llama/Llama-3.3-70B-Instruct",
num_prompts=4,
request_rate=float("inf"),
random_input_len=128000,
random_output_len=1,
dataset_name="random",
other_server_args=[
"--quantization",
"fp8",
"--pp-size",
"2",
]
+ (["--mem-fraction-static", "0.7"] if is_in_amd_ci() else []),
need_warmup=False,
seed=42,
)
check_perf(
self,
at_least(
"input_throughput",
res["input_throughput"],
4380,
amd=3000,
unit="token/s",
),
)
if __name__ == "__main__":
unittest.main()