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

209 行
6.7 KiB
Python

"""MI35x DeepSeek-V4-Flash FP4 Test (8-GPU)
Combined accuracy + performance test for DeepSeek-V4-Flash FP4 on MI35x ROCm 7.2.
- Accuracy: GSM8K few-shot eval
- Performance: bench_one_batch_server with input_len=8192, output_len=1024 (bs=1)
Both tests share a single launched server.
Registry: nightly-amd-8-gpu-mi35x-deepseek-v4-flash suite
"""
import json
import os
import subprocess
import unittest
from types import SimpleNamespace
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_amd_ci
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
DEFAULT_URL_FOR_TEST,
CustomTestCase,
is_in_ci,
popen_launch_server,
write_github_step_summary,
)
register_amd_ci(
est_time=7200, suite="nightly-amd-8-gpu-mi35x-deepseek-v4-flash", nightly=True
)
DEEPSEEK_V4_FP4_MODEL_PATH = os.environ.get(
"DEEPSEEK_V4_FP4_MODEL_PATH", "deepseek-ai/DeepSeek-V4-Flash"
)
SERVER_LAUNCH_TIMEOUT = 3600
FLASHMLA_BACKEND = os.environ.get("SGLANG_HACK_FLASHMLA_BACKEND", "unified_kv_triton")
COMMON_ENV_VARS = {
"SGLANG_DEFAULT_THINKING": "1",
"SGLANG_DSV4_REASONING_EFFORT": "max",
"SGLANG_USE_ROCM700A": "0",
"SGLANG_DP_USE_GATHERV": "1",
"SGLANG_HACK_FLASHMLA_BACKEND": FLASHMLA_BACKEND,
"AITER_BF16_FP8_MOE_BOUND": "0",
}
# FP4 variant
FP4_ENV_VARS = {
"SGLANG_DSV4_FP4_EXPERTS": "true",
}
class TestDeepseekV4Fp4(CustomTestCase):
@classmethod
def setUpClass(cls):
cls.model = DEEPSEEK_V4_FP4_MODEL_PATH
cls.base_url = DEFAULT_URL_FOR_TEST
env = os.environ.copy()
env.update(COMMON_ENV_VARS)
env.update(FP4_ENV_VARS)
other_args = [
"--trust-remote-code",
"--tp",
"8",
"--disable-radix-cache",
"--attention-backend",
"dsv4",
"--max-running-requests",
"256",
"--page-size",
"256",
"--mem-fraction-static",
"0.90",
"--swa-full-tokens-ratio",
"0.1",
"--chunked-prefill-size",
"8192",
"--disable-shared-experts-fusion",
"--tool-call-parser",
"deepseekv4",
"--reasoning-parser",
"deepseek-v4",
]
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=other_args,
env=env,
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_a_gsm8k(self):
# `a` prefix to run first (alphabetical) and warm up the server.
args = SimpleNamespace(
num_shots=8,
data_path=None,
num_questions=1319,
parallel=1319,
max_new_tokens=512,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval_few_shot_gsm8k(args)
print(f"{metrics=}")
if is_in_ci():
write_github_step_summary(
f"### test_gsm8k (deepseek-v4-flash-fp4, {FLASHMLA_BACKEND})\n"
f'{metrics["accuracy"]=:.3f}\n'
)
self.assertGreater(metrics["accuracy"], 0.91)
@unittest.skipIf(
os.environ.get("SGLANG_DSV4_ACCURACY_ONLY") == "1",
"SGLANG_DSV4_ACCURACY_ONLY=1: accuracy-only run (skipping perf)",
)
def test_b_perf_8k_1k(self):
json_output = "/tmp/deepseek_v4_flash_fp4_perf.json"
if os.path.exists(json_output):
os.remove(json_output)
# First "1" is a warmup; the markdown report below skips it.
batch_sizes = ["1", "1", "2", "4", "8", "16", "32"]
cmd = [
"python3",
"-m",
"sglang.bench_one_batch_server",
"--model",
"None",
"--base-url",
self.base_url,
"--batch-size",
*batch_sizes,
"--input-len",
"8192",
"--output-len",
"1024",
"--show-report",
f"--pydantic-result-filename={json_output}",
"--no-append-to-github-summary",
"--trust-remote-code",
]
print(f"Running benchmark: {' '.join(cmd)}")
result = subprocess.run(cmd, capture_output=True, text=True)
print(result.stdout)
if result.returncode != 0:
print(f"STDERR: {result.stderr}")
self.fail(f"bench_one_batch_server failed (rc={result.returncode})")
self.assertTrue(
os.path.exists(json_output),
f"Benchmark JSON output {json_output} not found",
)
with open(json_output) as f:
results_data = json.load(f)
self.assertTrue(results_data, "No benchmark results returned")
if (
len(results_data) > 1
and results_data[0]["batch_size"] == results_data[1]["batch_size"]
):
report_results = results_data[1:]
else:
report_results = results_data
summary_lines = [
f"### test_perf_8k_1k (deepseek-v4-flash-fp4, {FLASHMLA_BACKEND})",
"input_len=8192 output_len=1024",
"",
"| batch size | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |",
"| ---------- | ----------- | ------------------------ | ------------------------- | -------- |",
]
for r in report_results:
bs = r["batch_size"]
latency = r.get("latency", 0.0)
in_tp = r.get("input_throughput", 0.0)
out_tp = r.get("output_throughput", 0.0)
itl = 1 / (out_tp / bs) * 1000 if out_tp > 0 else float("inf")
summary_lines.append(
f"| {bs} | {latency:.2f} | {in_tp:.2f} | {out_tp:.2f} | {itl:.2f} |"
)
print(
f"bs={bs} latency={latency:.2f}s "
f"in_tp={in_tp:.2f} tok/s out_tp={out_tp:.2f} tok/s ITL={itl:.2f}ms"
)
if is_in_ci():
write_github_step_summary("\n".join(summary_lines) + "\n")
if __name__ == "__main__":
# run_suite.py's run_one_file launches each test file with `python3 <file> -f`,
# which enables unittest fail-fast. For this file, `test_a_gsm8k` (accuracy)
# and `test_b_perf_8k_1k` (performance) are independent measurements that
# share a very expensive server launch in setUpClass; we want perf data even
# if accuracy fails. Strip `-f` locally so subsequent test methods still run.
import sys
sys.argv = [a for a in sys.argv if a not in ("-f", "--failfast")]
unittest.main()