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[CI] Improve github summary & enable fa3 for more models (#5796)

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This commit is contained in:
Lianmin Zheng
2025-04-27 15:29:46 -07:00
committed by GitHub
parent ded04b2e0a
commit daed453e84
6 changed files with 26 additions and 20 deletions
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2
.github/workflows/pr-test.yml vendored
View File

@@ -123,7 +123,7 @@ jobs:
timeout-minutes: 10
run: |
cd test/srt
python3 -m unittest test_bench_one_batch.TestBenchOneBatch.test_bs1
python3 -m unittest test_bench_one_batch.TestBenchOneBatch.test_bs1_default
- name: Benchmark online latency
timeout-minutes: 10

1
python/sglang/srt/utils.py
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@@ -1970,6 +1970,7 @@ def is_fa3_default_architecture(hf_config):
"Llama4ForConditionalGeneration",
"LlamaForCausalLM",
"MistralForCausalLM",
"MixtralForCausalLM",
"Gemma2ForCausalLM",
"Gemma3ForConditionalGeneration",
}

2
test/srt/run_suite.py
View File

@@ -64,7 +64,7 @@ suites = {
TestFile("test_retract_decode.py", 54),
TestFile("test_server_args.py", 1),
TestFile("test_skip_tokenizer_init.py", 117),
TestFile("test_srt_engine.py", 237),
TestFile("test_srt_engine.py", 261),
TestFile("test_srt_endpoint.py", 130),
TestFile("test_torch_compile.py", 76),
TestFile("test_torch_compile_moe.py", 172),

15
test/srt/test_bench_one_batch.py
View File

@@ -4,7 +4,6 @@ from sglang.test.test_utils import (
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_MOE_MODEL_NAME_FOR_TEST,
CustomTestCase,
get_bool_env_var,
is_in_ci,
run_bench_one_batch,
write_github_step_summary,
@@ -12,15 +11,15 @@ from sglang.test.test_utils import (
class TestBenchOneBatch(CustomTestCase):
def test_bs1(self):
def test_bs1_default(self):
output_throughput = run_bench_one_batch(
DEFAULT_MODEL_NAME_FOR_TEST, ["--cuda-graph-max-bs", "2"]
)
if is_in_ci():
write_github_step_summary(
f"### test_bs1\n"
f"output_throughput : {output_throughput:.2f} token/s\n"
f"### test_bs1_default (llama-3.1-8b)\n"
f"output_throughput: {output_throughput:.2f} token/s\n"
)
self.assertGreater(output_throughput, 135)
@@ -32,9 +31,9 @@ class TestBenchOneBatch(CustomTestCase):
if is_in_ci():
write_github_step_summary(
f"### test_moe_tp2_bs1\n"
f"output_throughput : {output_throughput:.2f} token/s\n"
f"output_throughput: {output_throughput:.2f} token/s\n"
)
self.assertGreater(output_throughput, 124)
self.assertGreater(output_throughput, 125)
def test_torch_compile_tp2_bs1(self):
output_throughput = run_bench_one_batch(
@@ -45,9 +44,9 @@ class TestBenchOneBatch(CustomTestCase):
if is_in_ci():
write_github_step_summary(
f"### test_torch_compile_tp2_bs1\n"
f"output_throughput : {output_throughput:.2f} token/s\n"
f"output_throughput: {output_throughput:.2f} token/s\n"
)
self.assertGreater(output_throughput, 225)
self.assertGreater(output_throughput, 220)
if __name__ == "__main__":

10
test/srt/test_bench_serving.py
View File

@@ -98,7 +98,7 @@ class TestBenchServing(CustomTestCase):
f"### test_offline_throughput_with_triton_attention_backend\n"
f'Output throughput: {res["output_throughput"]:.2f} token/s\n'
)
self.assertGreater(res["output_throughput"], 3600)
self.assertGreater(res["output_throughput"], 3700)
def test_offline_throughput_default_fp8(self):
res = run_bench_serving(
@@ -113,7 +113,7 @@ class TestBenchServing(CustomTestCase):
f"### test_offline_throughput_default_fp8\n"
f'Output throughput: {res["output_throughput"]:.2f} token/s\n'
)
self.assertGreater(res["output_throughput"], 4200)
self.assertGreater(res["output_throughput"], 4300)
def test_online_latency_default(self):
res = run_bench_serving(
@@ -126,7 +126,7 @@ class TestBenchServing(CustomTestCase):
if is_in_ci():
write_github_step_summary(
f"### test_online_latency_default\n"
f'median_e2e_latency_ms : {res["median_e2e_latency_ms"]:.2f} ms\n'
f'median_e2e_latency_ms: {res["median_e2e_latency_ms"]:.2f} ms\n'
)
self.assertLess(res["median_e2e_latency_ms"], 11000)
self.assertLess(res["median_ttft_ms"], 86)
@@ -161,8 +161,8 @@ class TestBenchServing(CustomTestCase):
if is_in_ci():
write_github_step_summary(
f"### test_online_latency_eagle\n"
f'median_e2e_latency_ms : {res["median_e2e_latency_ms"]:.2f} ms\n'
f'accept_length : {res["accept_length"]:.2f} \n'
f'median_e2e_latency_ms: {res["median_e2e_latency_ms"]:.2f} ms\n'
f'accept_length: {res["accept_length"]:.2f} \n'
)
self.assertLess(res["median_e2e_latency_ms"], 900)
self.assertGreater(res["accept_length"], 3.0)

16
test/srt/test_full_deepseek_v3.py
View File

@@ -2,7 +2,6 @@ import unittest
from types import SimpleNamespace
import requests
import torch
from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
@@ -49,7 +48,7 @@ class TestDeepseekV3(CustomTestCase):
metrics = run_eval_few_shot_gsm8k(args)
print(f"{metrics=}")
self.assertGreater(metrics["accuracy"], 0.94)
self.assertGreater(metrics["accuracy"], 0.935)
class TestBenchOneBatch(CustomTestCase):
@@ -58,11 +57,11 @@ class TestBenchOneBatch(CustomTestCase):
FULL_DEEPSEEK_V3_MODEL_PATH,
["--trust-remote-code", "--tp", "8", "--cuda-graph-max-bs", "2"],
)
print(f"output_throughput : {output_throughput:.2f} token/s")
print(f"{output_throughput=:.2f} token/s")
if is_in_ci():
write_github_step_summary(
f"### test_bs1\n"
f"output_throughput : {output_throughput:.2f} token/s\n"
f"### test_bs1 (deepseek-v3)\n" f"{output_throughput=:.2f} token/s\n"
)
self.assertGreater(output_throughput, 70)
@@ -121,6 +120,13 @@ class TestDeepseekV3MTP(CustomTestCase):
print(f"{avg_spec_accept_length=}")
self.assertGreater(avg_spec_accept_length, 3.2)
if is_in_ci():
write_github_step_summary(
f"### test_gsm8k (deepseek-v3)\n"
f'{metrics["accuracy"]=:.3f}\n'
f"{avg_spec_accept_length=:.2f}\n"
)
if __name__ == "__main__":
unittest.main()