Files
sglang/test/registered/backends/test_flashinfer_trtllm_gen_moe_backend.py
T

353 lines
9.7 KiB
Python

import os
import unittest
from types import SimpleNamespace
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
register_cuda_ci(est_time=800, suite="nightly-4-gpu-b200", nightly=True)
class FlashinferTrtllmGenMoeBackendFP8Base:
backend = None
@classmethod
def setUpClass(cls):
cls.model = "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
env={**os.environ, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
other_args=[
"--attention-backend",
"triton",
"--moe-runner-backend",
cls.backend,
"--tp-size",
"4",
"--ep-size",
"4",
"--mem-fraction-static",
"0.7",
"--mamba-ssm-dtype",
"bfloat16",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.89)
class FlashinferTrtllmGenMoeBackendBF16Base:
backend = None
@classmethod
def setUpClass(cls):
cls.model = "Qwen/Qwen3-Next-80B-A3B-Instruct"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--attention-backend",
"triton",
"--moe-runner-backend",
cls.backend,
"--cuda-graph-max-bs-decode",
"512",
"--tp-size",
"4",
"--ep-size",
"4",
"--mem-fraction-static",
"0.7",
"--mamba-ssm-dtype",
"bfloat16",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.93)
class FlashinferTrtllmGenMoeBackendMXFP8Base:
backend = None
@classmethod
def setUpClass(cls):
cls.model = "zianglih/Qwen3-30B-A3B-Instruct-2507-MXFP8"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
env={**os.environ, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
other_args=[
"--fp8-gemm-backend",
"flashinfer_cutlass",
"--moe-runner-backend",
cls.backend,
"--tp-size",
"4",
"--ep-size",
"4",
"--mem-fraction-static",
"0.7",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.93)
class FlashinferTrtllmGenMoeBackendMXFP8MixedBF16Base:
backend = None
@classmethod
def setUpClass(cls):
cls.model = "zianglih/JoyAI-LLM-Flash-MXFP8-last-6-BF16"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
env={**os.environ, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
other_args=[
"--kv-cache-dtype",
"bf16",
"--fp8-gemm-backend",
"flashinfer_trtllm",
"--moe-runner-backend",
cls.backend,
"--tp-size",
"4",
"--trust-remote-code",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.92)
class FlashinferTrtllmGenMoeBackendNVFP4Base:
backend = None
extra_env = {}
@classmethod
def setUpClass(cls):
cls.model = "nvidia/Qwen3-30B-A3B-NVFP4"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
env={**os.environ, **cls.extra_env, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
other_args=[
"--moe-runner-backend",
cls.backend,
"--tp-size",
"4",
"--ep-size",
"4",
"--mem-fraction-static",
"0.7",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.89)
class FlashinferTrtllmGenMoeBackendNvFp4OnlineBase:
backend = None
extra_env = {}
@classmethod
def setUpClass(cls):
cls.model = "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
env={**os.environ, **cls.extra_env, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
other_args=[
"--attention-backend",
"triton",
"--moe-runner-backend",
cls.backend,
"--cuda-graph-max-bs-decode",
"128",
"--tp-size",
"4",
"--ep-size",
"2",
"--quantization",
"nvfp4_online",
"--mem-fraction-static",
"0.7",
"--mamba-ssm-dtype",
"bfloat16",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["score"], 0.90)
class TestFlashinferTrtllmGenMoeBackendFP8(
FlashinferTrtllmGenMoeBackendFP8Base, CustomTestCase
):
backend = "flashinfer_trtllm"
class TestFlashinferTrtllmGenMoeBackendNVFP4(
FlashinferTrtllmGenMoeBackendNVFP4Base, CustomTestCase
):
backend = "flashinfer_trtllm"
class TestFlashinferTrtllmGenMoeBackendMXFP8Routed(
FlashinferTrtllmGenMoeBackendMXFP8Base, CustomTestCase
):
backend = "flashinfer_trtllm_routed"
class TestFlashinferTrtllmRoutedMxfp8MixedBF16(
FlashinferTrtllmGenMoeBackendMXFP8MixedBF16Base, CustomTestCase
):
backend = "flashinfer_trtllm_routed"
class TestFlashinferTrtllmGenMoeBackendBF16Routed(
FlashinferTrtllmGenMoeBackendBF16Base, CustomTestCase
):
backend = "flashinfer_trtllm_routed"
class TestFlashinferTrtllmGenMoeBackendNvFp4PerTokenActivationRouted(
FlashinferTrtllmGenMoeBackendNVFP4Base, CustomTestCase
):
extra_env = {"SGLANG_FLASHINFER_NVFP4_PER_TOKEN_ACTIVATION": "1"}
backend = "flashinfer_trtllm_routed"
class TestFlashinferTrtllmGenMoeBackendNvFp4Online(
FlashinferTrtllmGenMoeBackendNvFp4OnlineBase, CustomTestCase
):
extra_env = {
"FLASHINFER_NVFP4_4OVER6": "1",
"FLASHINFER_NVFP4_4OVER6_ERR_MODE": "MSE",
"FLASHINFER_NVFP4_4OVER6_ERR_USE_FAST_MATH": "1",
"FLASHINFER_NVFP4_4OVER6_E4M3_USE_256": "1",
"SGLANG_FP4_IGNORED_LAYERS": ",".join(
["shared_expert"]
+ [f"model.layers.{layer_id}" for layer_id in range(40, 48)]
),
}
backend = "flashinfer_trtllm"
if __name__ == "__main__":
unittest.main()