A few updates to the night tests (#17694)

This commit is contained in:
Kangyan-Zhou
2026-01-25 11:20:17 -08:00
committed by GitHub
parent a883906a24
commit 9123491430
11 changed files with 52 additions and 26 deletions
@@ -60,7 +60,7 @@ class TestDeepseekV31(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="DeepSeek-V3.1 Unified",
test_name="DeepSeek-V3.1",
accuracy_params=AccuracyTestParams(
dataset="gsm8k", baseline_accuracy=0.935
),
@@ -82,7 +82,7 @@ class TestDeepseekV32(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="DeepSeek-V3.2 Unified",
test_name="DeepSeek-V3.2",
accuracy_params=AccuracyTestParams(
dataset="gsm8k", baseline_accuracy=GSM8K_BASELINE
),
@@ -69,7 +69,7 @@ class TestDeepseekV32CPSingleNode(unittest.TestCase):
ModelLaunchSettings(
DEEPSEEK_V32_EXP_MODEL_PATH,
tp_size=8,
extra_args=BASE_ARGS + ["--tp=8"] + MTP_ARGS + CP_ROUND_ROBIN_ARGS,
extra_args=BASE_ARGS + MTP_ARGS + CP_ROUND_ROBIN_ARGS,
variant="CP-round-robin-split",
),
]
+1 -1
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@@ -40,7 +40,7 @@ class TestGLM46(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="GLM-4.6 Unified",
test_name="GLM-4.6",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_4_6",
@@ -51,7 +51,7 @@ class TestGLM46FP8(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="GLM-4.6-FP8 Unified",
test_name="GLM-4.6-FP8",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_glm_4_6_fp8",
+1 -1
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@@ -41,7 +41,7 @@ class TestKimiK2(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="Kimi-K2-Thinking Unified",
test_name="Kimi-K2-Thinking",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.94),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_kimi_k2_thinking",
+1 -1
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@@ -44,7 +44,7 @@ class TestLlama4(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="Llama-4-Scout Unified",
test_name="Llama-4-Scout",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.9),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_llama4",
@@ -43,7 +43,7 @@ class TestMiniMaxM2(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="MiniMax-M2 Unified",
test_name="MiniMax-M2",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_minimax_m2",
@@ -76,7 +76,7 @@ class TestMistralLarge3(unittest.TestCase):
run_combined_tests(
models=variants,
test_name="Mistral-Large-3 Unified",
test_name="Mistral-Large-3",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.90),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_mistral_large3",
+34 -13
View File
@@ -4,46 +4,67 @@ 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, is_blackwell_system
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)
QWEN3_235B_MODEL_PATH = "Qwen/Qwen3-235B-A22B-Instruct-2507"
QWEN3_235B_FP8_MODEL_PATH = "Qwen/Qwen3-235B-A22B-Instruct-2507-FP8"
QWEN3_235B_EAGLE3_MODEL_PATH = (
"lmsys/SGLang-EAGLE3-Qwen3-235B-A22B-Instruct-2507-SpecForge-Meituan"
)
@unittest.skipIf(not is_blackwell_system(), "Requires B200")
class TestQwen3235B(unittest.TestCase):
"""Unified test class for Qwen3-235B performance and accuracy.
class TestQwen3235BFP8(unittest.TestCase):
"""Test class for Qwen3-235B-FP8 performance and accuracy.
Single variant with simple TP=8 configuration.
Runs BOTH:
Two variants:
- basic: TP=8
- eagle3: TP=8 + EP=2 + EAGLE3 speculative decoding
Each variant runs BOTH:
- Performance test (using NightlyBenchmarkRunner)
- Accuracy test (using run_eval with mgsm_en)
- Accuracy test (using run_eval with gsm8k)
"""
def test_qwen3_235b(self):
"""Run performance and accuracy for Qwen3-235B."""
def test_qwen3_235b_fp8_all_variants(self):
"""Run performance and accuracy for Qwen3-235B-FP8."""
base_args = [
"--tp=8",
"--trust-remote-code",
]
eagle3_args = [
"--ep=2",
"--speculative-algorithm=EAGLE3",
f"--speculative-draft-model-path={QWEN3_235B_EAGLE3_MODEL_PATH}",
"--speculative-num-steps=3",
"--speculative-eagle-topk=1",
"--speculative-num-draft-tokens=4",
]
variants = [
# Variant: "basic" - TP=8
ModelLaunchSettings(
QWEN3_235B_MODEL_PATH,
QWEN3_235B_FP8_MODEL_PATH,
tp_size=8,
extra_args=base_args,
variant="TP8",
),
# Variant: "eagle3" - TP=8 + EP=2 + EAGLE3 speculative decoding
ModelLaunchSettings(
QWEN3_235B_FP8_MODEL_PATH,
tp_size=8,
extra_args=base_args + eagle3_args,
variant="TP8+EP2+EAGLE3",
),
]
run_combined_tests(
models=variants,
test_name="Qwen3-235B Unified",
test_name="Qwen3-235B-FP8",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.88),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_qwen3_235b",
profile_dir="performance_profiles_qwen3_235b_fp8",
),
)