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test(4-gpu-b200): split test_qwen35_models.py + bump partitions 5→6 (#22913)

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This commit is contained in:
Alison Shao
2026-04-16 18:51:59 -07:00
committed by GitHub
parent e353630b57
commit 0052093178
4 changed files with 184 additions and 247 deletions
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.github/workflows/pr-test.yml
+2 -2
View File
@@ -1232,7 +1232,7 @@ jobs:
strategy:
fail-fast: false
matrix:
part: [0, 1, 2, 3, 4]
part: [0, 1, 2, 3, 4, 5]
steps:
- name: Checkout code
@@ -1263,7 +1263,7 @@ jobs:
CONTINUE_ON_ERROR_FLAG: ${{ needs.check-changes.outputs.continue_on_error == 'true' && '--continue-on-error' || '' }}
run: |
cd test
python3 run_suite.py --hw cuda --suite stage-c-test-4-gpu-b200 --auto-partition-id ${{ matrix.part }} --auto-partition-size 5 --timeout-per-file 1800 $CONTINUE_ON_ERROR_FLAG
python3 run_suite.py --hw cuda --suite stage-c-test-4-gpu-b200 --auto-partition-id ${{ matrix.part }} --auto-partition-size 6 --timeout-per-file 1800 $CONTINUE_ON_ERROR_FLAG
- uses: ./.github/actions/upload-cuda-coredumps
if: failure()
test/registered/4-gpu-models/test_qwen35_fp4_mtp_v2.py
+105
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@@ -0,0 +1,105 @@
import unittest
from types import SimpleNamespace
import requests
from sglang.srt.environ import envs
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.kits.reasoning_kit import ReasoningTokenUsageMixin
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=540, suite="stage-c-test-4-gpu-b200")
QWEN35_FP4_MODEL = "nvidia/Qwen3.5-397B-A17B-NVFP4"
ACC_THRESHOLDS = {QWEN35_FP4_MODEL: {"gsm8k": 0.95}}
class TestQwen35FP4MTPV2(ReasoningTokenUsageMixin, CustomTestCase):
reasoning_parser_name = "qwen3"
@classmethod
def setUpClass(cls):
cls.model = QWEN35_FP4_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.init_reasoning_token_verifier()
envs.SGLANG_ENABLE_SPEC_V2.set(True)
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
"--mamba-ssm-dtype",
"bfloat16",
"--max-running-requests",
"128",
"--reasoning-parser",
"qwen3",
"--attention-backend",
"trtllm_mha",
"--quantization",
"modelopt_fp4",
"--speculative-algorithm",
"NEXTN",
"--speculative-num-steps",
"3",
"--speculative-eagle-topk",
"1",
"--speculative-num-draft-tokens",
"4",
"--mem-fraction-static",
"0.8",
"--model-loader-extra-config",
'{"enable_multithread_load": true,"num_threads": 64}',
],
)
@classmethod
def tearDownClass(cls):
envs.SGLANG_ENABLE_SPEC_V2.set(False)
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
model=self.model,
eval_name="gsm8k",
num_shots=5,
num_examples=200,
max_tokens=16000,
num_threads=128,
repeat=1,
temperature=0.6,
top_p=0.95,
top_k=20,
base_url=self.base_url,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreaterEqual(metrics["score"], ACC_THRESHOLDS[self.model]["gsm8k"])
server_info = requests.get(self.base_url + "/server_info")
avg_spec_accept_length = server_info.json()["internal_states"][0][
"avg_spec_accept_length"
]
print(f"{avg_spec_accept_length=}")
self.assertGreater(avg_spec_accept_length, 3.3)
if __name__ == "__main__":
unittest.main()
test/registered/4-gpu-models/test_qwen35_fp4_triton.py
+77
View File
@@ -0,0 +1,77 @@
import unittest
from sglang.test.accuracy_test_runner import AccuracyTestParams
from sglang.test.ci.ci_register import register_cuda_ci
# This eval harness applies the chat_template, which is critical for qwen3.5
# to get good accuracy on gsm8k
from sglang.test.run_combined_tests import run_combined_tests
from sglang.test.test_utils import (
CustomTestCase,
ModelLaunchSettings,
)
register_cuda_ci(est_time=720, suite="stage-c-test-4-gpu-b200")
QWEN35_FP4_MODEL = "nvidia/Qwen3.5-397B-A17B-NVFP4"
ACC_THRESHOLDS = {QWEN35_FP4_MODEL: {"gsm8k": 0.95}}
class TestQwen35FP4(CustomTestCase):
def test_gsm8k(self):
base_args = [
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
"--mamba-ssm-dtype",
"bfloat16",
"--max-running-requests",
"128",
"--reasoning-parser",
"qwen3",
"--attention-backend",
"trtllm_mha",
"--quantization",
"modelopt_fp4",
"--model-loader-extra-config",
'{"enable_multithread_load": true,"num_threads": 64}',
]
variants = [
ModelLaunchSettings(
QWEN35_FP4_MODEL,
extra_args=base_args,
variant="Triton",
),
# TODO: Fix this and re-enable it
# ModelLaunchSettings(
# QWEN35_FP4_MODEL,
# extra_args=base_args + ["--linear-attn-decode-backend", "flashinfer"],
# variant="FlashInfer",
# ),
]
run_combined_tests(
models=variants,
test_name="Qwen3.5-397B-A17B-NVFP4",
accuracy_params=AccuracyTestParams(
dataset="gsm8k",
baseline_accuracy=ACC_THRESHOLDS[QWEN35_FP4_MODEL]["gsm8k"],
num_examples=200,
num_threads=128,
max_tokens=16000,
thinking_mode="qwen3",
temperature=0.6,
top_p=0.95,
top_k=20,
),
)
if __name__ == "__main__":
unittest.main()
test/registered/4-gpu-models/test_qwen35_models.py
-245
View File
@@ -1,245 +0,0 @@
import unittest
from types import SimpleNamespace
import requests
from sglang.srt.environ import envs
from sglang.srt.utils import kill_process_tree
from sglang.test.accuracy_test_runner import AccuracyTestParams
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.kits.reasoning_kit import ReasoningTokenUsageMixin
# This eval harness applies the chat_template, which is critical for qwen3.5
# to get good accuracy on gsm8k
from sglang.test.run_combined_tests import run_combined_tests
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
ModelLaunchSettings,
popen_launch_server,
)
register_cuda_ci(est_time=768, suite="stage-c-test-4-gpu-b200")
QWEN35_FP4_MODEL = "nvidia/Qwen3.5-397B-A17B-NVFP4"
ACC_THRESHOLDS = {QWEN35_FP4_MODEL: {"gsm8k": 0.95}}
class TestQwen35FP4(CustomTestCase):
def test_gsm8k(self):
base_args = [
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
"--mamba-ssm-dtype",
"bfloat16",
"--max-running-requests",
"128",
"--reasoning-parser",
"qwen3",
"--attention-backend",
"trtllm_mha",
"--quantization",
"modelopt_fp4",
"--model-loader-extra-config",
'{"enable_multithread_load": true,"num_threads": 64}',
]
variants = [
ModelLaunchSettings(
QWEN35_FP4_MODEL,
extra_args=base_args,
variant="Triton",
),
# TODO: Fix this and re-enable it
# ModelLaunchSettings(
# QWEN35_FP4_MODEL,
# extra_args=base_args + ["--linear-attn-decode-backend", "flashinfer"],
# variant="FlashInfer",
# ),
]
run_combined_tests(
models=variants,
test_name="Qwen3.5-397B-A17B-NVFP4",
accuracy_params=AccuracyTestParams(
dataset="gsm8k",
baseline_accuracy=ACC_THRESHOLDS[QWEN35_FP4_MODEL]["gsm8k"],
num_examples=200,
num_threads=128,
max_tokens=16000,
thinking_mode="qwen3",
temperature=0.6,
top_p=0.95,
top_k=20,
),
)
class TestQwen35FP4MTP(ReasoningTokenUsageMixin, CustomTestCase):
reasoning_parser_name = "qwen3"
@classmethod
def setUpClass(cls):
cls.model = QWEN35_FP4_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.init_reasoning_token_verifier()
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
"--mamba-ssm-dtype",
"bfloat16",
"--max-running-requests",
"128",
"--reasoning-parser",
"qwen3",
"--attention-backend",
"trtllm_mha",
"--quantization",
"modelopt_fp4",
"--speculative-algorithm",
"NEXTN",
"--speculative-num-steps",
"3",
"--speculative-eagle-topk",
"1",
"--speculative-num-draft-tokens",
"4",
"--mem-fraction-static",
"0.8",
"--model-loader-extra-config",
'{"enable_multithread_load": true,"num_threads": 64}',
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
model=self.model,
eval_name="gsm8k",
num_shots=5,
num_examples=200,
max_tokens=16000,
num_threads=128,
repeat=1,
temperature=0.6,
top_p=0.95,
top_k=20,
base_url=self.base_url,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreaterEqual(metrics["score"], ACC_THRESHOLDS[self.model]["gsm8k"])
server_info = requests.get(self.base_url + "/server_info")
avg_spec_accept_length = server_info.json()["internal_states"][0][
"avg_spec_accept_length"
]
print(f"{avg_spec_accept_length=}")
self.assertGreater(avg_spec_accept_length, 3.3)
class TestQwen35FP4MTPV2(ReasoningTokenUsageMixin, CustomTestCase):
reasoning_parser_name = "qwen3"
@classmethod
def setUpClass(cls):
cls.model = QWEN35_FP4_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.init_reasoning_token_verifier()
envs.SGLANG_ENABLE_SPEC_V2.set(True)
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
"--mamba-ssm-dtype",
"bfloat16",
"--max-running-requests",
"128",
"--reasoning-parser",
"qwen3",
"--attention-backend",
"trtllm_mha",
"--quantization",
"modelopt_fp4",
"--speculative-algorithm",
"NEXTN",
"--speculative-num-steps",
"3",
"--speculative-eagle-topk",
"1",
"--speculative-num-draft-tokens",
"4",
"--mem-fraction-static",
"0.8",
"--model-loader-extra-config",
'{"enable_multithread_load": true,"num_threads": 64}',
],
)
@classmethod
def tearDownClass(cls):
envs.SGLANG_ENABLE_SPEC_V2.set(False)
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
model=self.model,
eval_name="gsm8k",
num_shots=5,
num_examples=200,
max_tokens=16000,
num_threads=128,
repeat=1,
temperature=0.6,
top_p=0.95,
top_k=20,
base_url=self.base_url,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreaterEqual(metrics["score"], ACC_THRESHOLDS[self.model]["gsm8k"])
server_info = requests.get(self.base_url + "/server_info")
avg_spec_accept_length = server_info.json()["internal_states"][0][
"avg_spec_accept_length"
]
print(f"{avg_spec_accept_length=}")
self.assertGreater(avg_spec_accept_length, 3.3)
if __name__ == "__main__":
unittest.main()