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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

53 行
1.5 KiB
Python

import unittest
from sglang.test.accuracy_test_runner import AccuracyTestParams
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.performance_test_runner import PerformanceTestParams
from sglang.test.run_combined_tests import run_combined_tests
from sglang.test.test_utils import ModelLaunchSettings
# Runs on both H200 and B200 via nightly-8-gpu-common suite
register_cuda_ci(est_time=1800, suite="nightly-8-gpu-common", nightly=True)
GLM_4_6_MODEL_PATH = "zai-org/GLM-4.6"
class TestGLM46(unittest.TestCase):
"""Unified test class for GLM-4.6 performance and accuracy.
Single variant with simple TP=8 configuration.
GLM-4.6 is a 357B MoE model.
Runs BOTH:
- Performance test (using NightlyBenchmarkRunner)
- Accuracy test (using run_eval with mgsm_en)
"""
def test_glm_46(self):
"""Run performance and accuracy for GLM-4.6."""
base_args = [
"--tp=8",
"--trust-remote-code",
]
variants = [
ModelLaunchSettings(
GLM_4_6_MODEL_PATH,
tp_size=8,
extra_args=base_args,
variant="TP8",
),
]
run_combined_tests(
models=variants,
test_name="GLM-4.6",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_4_6",
),
)
if __name__ == "__main__":
unittest.main()