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Update CI (#3474)

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* update CI cases

* update CI cases

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* Merge upstream/develop and resolve directory rename conflict

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This commit is contained in:
Zhang Yulong
2025-08-21 16:49:20 +08:00
committed by GitHub
parent c83381d650
commit b7eee3aec1
13 changed files with 150 additions and 392 deletions
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1
.github/workflows/_accuracy_test.yml vendored
View File

@@ -132,6 +132,7 @@ jobs:
-v "${CACHE_DIR}/ConfigDir:/root/.config" \
-e TZ="Asia/Shanghai" \
--gpus '"device='"${DEVICES}"'"' ${docker_image} /bin/bash -xc '
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple

25
.github/workflows/_base_test.yml vendored
View File

@@ -132,6 +132,7 @@ jobs:
-v "${CACHE_DIR}/ConfigDir:/root/.config" \
-e TZ="Asia/Shanghai" \
--gpus '"device='"${DEVICES}"'"' ${docker_image} /bin/bash -xc '
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
@@ -155,7 +156,19 @@ jobs:
-H "Content-Type: application/json" \
-d "{\"--model\": \"/MODELDATA/ERNIE-4.5-0.3B-Paddle\"}"
curl -X POST http://localhost:${FLASK_PORT}/wait_for_infer?timeout=90
check_service() {
local timeout=${1:-90}
local url="http://localhost:${FLASK_PORT}/wait_for_infer?timeout=${timeout}"
local resp
resp=$(curl -s -X POST "$url")
if echo "$resp" | grep -q "服务启动超时"; then
exit 8
fi
}
check_service 90
popd
pushd tests/ce/server
@@ -166,8 +179,16 @@ jobs:
curl -X POST http://0.0.0.0:${FLASK_PORT}/switch \
-H "Content-Type: application/json" \
-d "{\"--model\": \"/MODELDATA/ERNIE-4.5-0.3B-Paddle\", \"--early-stop-config\": \"{\\\"enable_early_stop\\\":true, \\\"window_size\\\":6, \\\"threshold\\\":0.93}\"}"
curl -X POST http://localhost:${FLASK_PORT}/wait_for_infer?timeout=90
check_service 90
python -m pytest -sv test_repetition_early_stop.py || TEST_EXIT_CODE=1
curl -X POST http://0.0.0.0:${FLASK_PORT}/switch \
-H "Content-Type: application/json" \
-d "{\"--model\": \"/MODELDATA/ernie-4_5-21b-a3b-bf16-paddle\", \"--config\": \"21b_mtp.yaml\", \"--enable-logprob\": \"False\"}"
check_service 180
export TEMPLATE=TOKEN_NORMAL
python -m pytest -sv test_seed_usage.py -k "not test_seed_stream" || TEST_EXIT_CODE=1
popd
echo "TEST_EXIT_CODE=${TEST_EXIT_CODE}" >> /workspace/FastDeploy/exit_code.env
'

1
.github/workflows/_build_linux.yml vendored
View File

@@ -148,6 +148,7 @@ jobs:
elif [[ "${PADDLEVERSION}" != "" ]];then
python -m pip install paddlepaddle-gpu==${PADDLEVERSION} -i https://www.paddlepaddle.org.cn/packages/stable/cu126/
else
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
fi

1
.github/workflows/_logprob_test_linux.yml vendored
View File

@@ -122,6 +122,7 @@ jobs:
-v "${CACHE_DIR}/ConfigDir:/root/.config" \
-e TZ="Asia/Shanghai" \
--gpus '"device='"${DEVICES}"'"' ${docker_image} /bin/bash -xc '
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple

1
.github/workflows/_pre_ce_test.yml vendored
View File

@@ -129,6 +129,7 @@ jobs:
--gpus "\"device=${DEVICES}\"" ${docker_image} /bin/bash -c '
git config --global --add safe.directory /workspace/FastDeploy
cd FastDeploy
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install ${fd_wheel_url}
bash scripts/run_pre_ce.sh

1
.github/workflows/_stable_test.yml vendored
View File

@@ -138,6 +138,7 @@ jobs:
-v "${CACHE_DIR}/ConfigDir:/root/.config" \
-e TZ="Asia/Shanghai" \
--gpus '"device='"${DEVICES}"'"' ${docker_image} /bin/bash -xc '
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple

1
.github/workflows/_unit_test_coverage.yml vendored
View File

@@ -144,6 +144,7 @@ jobs:
git config --global --add safe.directory /workspace/FastDeploy
cd FastDeploy
#python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
pip config set global.extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple

1
scripts/run_unittest.sh
View File

@@ -17,6 +17,7 @@ pwd
git config --global --add safe.directory /workspace1/FastDeploy
#python -m pip install --force-reinstall --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install --force-reinstall paddlepaddle-gpu==3.0.0.dev20250818 -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
python -m pip install --upgrade --force-reinstall -r requirements/unittest/requirements.txt
bash tools/build_wheel.sh

8
tests/ce/deploy/21b_mtp.yaml Normal file
View File

@@ -0,0 +1,8 @@
max_model_len: 32768
max_num_seqs: 128
tensor_parallel_size: 1
quantization: wint4
speculative_config:
method: mtp
num_speculative_tokens: 1
model: /MODELDATA/ernie-4_5-21b-a3b-bf16-paddle/mtp/

3
tests/ce/deploy/deploy.py
View File

@@ -79,6 +79,7 @@ def build_command(config):
# 添加配置参数
for key, value in config.items():
if "--enable" in key:
value = bool(value if isinstance(value, bool) else eval(value))
if value:
cmd.append(key)
else:
@@ -189,6 +190,8 @@ def stop_server(signum=None, frame=None):
# 若log目录存在，则重命名为log_timestamp
if os.path.isdir("./log"):
os.rename("./log", "./log_{}".format(time.strftime("%Y%m%d%H%M%S")))
if os.path.exists("gemm_profiles.json"):
os.remove("gemm_profiles.json")
if signum:
sys.exit(0)

10
tests/ce/server/core/request_template.py
View File

@@ -18,8 +18,18 @@ TOKEN_LOGPROB = {
"max_tokens": 10000,
}
TOKEN_NORMAL = {
"model": "default",
"temperature": 0,
"top_p": 0,
"seed": 33,
"stream": True,
"max_tokens": 10000,
}
TEMPLATES = {
"TOKEN_LOGPROB": TOKEN_LOGPROB,
"TOKEN_NORMAL": TOKEN_NORMAL,
# "ANOTHER_TEMPLATE": ANOTHER_TEMPLATE
}

103
tests/ce/server/test_seed_usage.py
View File

@@ -5,6 +5,7 @@
import json
import pytest
from core import TEMPLATE, URL, build_request_payload, get_stream_chunks, send_request
@@ -44,7 +45,7 @@ def test_seed_stream():
assert l1 == l2, f"top_p=0, 固定seed, logprobs[{idx}]不一致"
def test_usage_stream():
def test_chat_usage_stream():
"""测试payload max_tokens参数"""
data = {
"messages": [
@@ -65,9 +66,103 @@ def test_usage_stream():
usage = chunks[-1]["usage"]
total_tokens = usage["completion_tokens"] + usage["prompt_tokens"]
assert data["max_tokens"] >= usage["completion_tokens"], "completion_tokens大于max_tokens"
assert data["metadata"]["min_tokens"] <= usage["completion_tokens"], "completion_tokens小于min_tokens"
assert usage["total_tokens"] == total_tokens, "total_tokens不等于prompt_tokens + completion_tokens"
assert data["max_tokens"] >= usage["completion_tokens"], f"completion_tokens大于max_tokens, usage: {usage}"
assert (
data["metadata"]["min_tokens"] <= usage["completion_tokens"]
), f"completion_tokens小于min_tokens, usage: {usage}"
assert (
usage["total_tokens"] == total_tokens
), f"total_tokens不等于prompt_tokens + completion_tokens, usage: {usage}"
def test_chat_usage_non_stream():
"""测试非流式 usage"""
data = {
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "牛顿的三大运动定律是什么？"},
],
"max_tokens": 50,
"stream": False,
"metadata": {"min_tokens": 10},
}
payload = build_request_payload(TEMPLATE, data)
response = send_request(url=URL, payload=payload).json()
# print(response)
# chunks = get_stream_chunks(response)
# for idx, chunk in enumerate(chunks):
# print(f"\nchunk[{idx}]:\n{json.dumps(chunk, indent=2, ensure_ascii=False)}")
usage = response["usage"]
total_tokens = usage["completion_tokens"] + usage["prompt_tokens"]
assert data["max_tokens"] >= usage["completion_tokens"], f"completion_tokens大于max_tokens, usage: {usage}"
assert (
data["metadata"]["min_tokens"] <= usage["completion_tokens"]
), f"completion_tokens小于min_tokens, usage: {usage}"
assert (
usage["total_tokens"] == total_tokens
), f"total_tokens不等于prompt_tokens + completion_tokens, usage: {usage}"
@pytest.mark.skip(reason="修复后打开")
def test_non_chat_usage_stream():
"""测试completions 流式 usage"""
data = {
"prompt": "牛顿的三大运动定律是什么？",
"max_tokens": 50,
"stream": True,
"stream_options": {"include_usage": True, "continuous_usage_stats": True},
"metadata": {"min_tokens": 10},
}
completion_url = URL.replace("chat/completions", "completions")
payload = build_request_payload(TEMPLATE, data)
response = send_request(url=completion_url, payload=payload, stream=True)
chunks = get_stream_chunks(response)
# for idx, chunk in enumerate(chunks):
# print(f"\nchunk[{idx}]:\n{json.dumps(chunk, indent=2, ensure_ascii=False)}")
usage = chunks[-1]["usage"]
total_tokens = usage["completion_tokens"] + usage["prompt_tokens"]
assert data["max_tokens"] >= usage["completion_tokens"], f"completion_tokens大于max_tokens, usage: {usage}"
assert (
data["metadata"]["min_tokens"] <= usage["completion_tokens"]
), f"completion_tokens小于min_tokens, usage: {usage}"
assert (
usage["total_tokens"] == total_tokens
), f"total_tokens不等于prompt_tokens + completion_tokens, usage: {usage}"
def test_non_chat_usage_non_stream():
"""测试completions 非流式 usage"""
data = {
"prompt": "牛顿的三大运动定律是什么？",
"max_tokens": 50,
"stream": False,
"metadata": {"min_tokens": 10},
}
completion_url = URL.replace("chat/completions", "completions")
payload = build_request_payload(TEMPLATE, data)
response = send_request(url=completion_url, payload=payload).json()
# print(response)
# chunks = get_stream_chunks(response)
# for idx, chunk in enumerate(chunks):
# print(f"\nchunk[{idx}]:\n{json.dumps(chunk, indent=2, ensure_ascii=False)}")
usage = response["usage"]
total_tokens = usage["completion_tokens"] + usage["prompt_tokens"]
assert data["max_tokens"] >= usage["completion_tokens"], f"completion_tokens大于max_tokens, usage: {usage}"
assert (
data["metadata"]["min_tokens"] <= usage["completion_tokens"]
), f"completion_tokens小于min_tokens, usage: {usage}"
assert (
usage["total_tokens"] == total_tokens
), f"total_tokens不等于prompt_tokens + completion_tokens, usage: {usage}"
if __name__ == "__main__":

386
tests/ci_use/EB_Lite_mtp/test_EB_Lite_serving_mtp.py
View File

@@ -1,386 +0,0 @@
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import os
import re
import signal
import socket
import subprocess
import sys
import time
import openai
import pytest
import requests
# Read ports from environment variables; use default values if not set
FD_API_PORT = int(os.getenv("FD_API_PORT", 8188))
FD_ENGINE_QUEUE_PORT = int(os.getenv("FD_ENGINE_QUEUE_PORT", 8133))
FD_METRICS_PORT = int(os.getenv("FD_METRICS_PORT", 8233))
# List of ports to clean before and after tests
PORTS_TO_CLEAN = [FD_API_PORT, FD_ENGINE_QUEUE_PORT, FD_METRICS_PORT]
def is_port_open(host: str, port: int, timeout=1.0):
"""
Check if a TCP port is open on the given host.
Returns True if connection succeeds, False otherwise.
"""
try:
with socket.create_connection((host, port), timeout):
return True
except Exception:
return False
def kill_process_on_port(port: int):
"""
Kill processes that are listening on the given port.
Uses `lsof` to find process ids and sends SIGKILL.
"""
try:
output = subprocess.check_output(f"lsof -i:{port} -t", shell=True).decode().strip()
for pid in output.splitlines():
os.kill(int(pid), signal.SIGKILL)
print(f"Killed process on port {port}, pid={pid}")
except subprocess.CalledProcessError:
pass
def clean_ports():
"""
Kill all processes occupying the ports listed in PORTS_TO_CLEAN.
"""
for port in PORTS_TO_CLEAN:
kill_process_on_port(port)
@pytest.fixture(scope="session", autouse=True)
def setup_and_run_server():
"""
Pytest fixture that runs once per test session:
- Cleans ports before tests
- Starts the API server as a subprocess
- Waits for server port to open (up to 30 seconds)
- Tears down server after all tests finish
"""
print("Pre-test port cleanup...")
clean_ports()
base_path = os.getenv("MODEL_PATH")
if base_path:
model_path = os.path.join(base_path, "ernie-4_5-21b-a3b-bf16-paddle")
else:
model_path = "./ernie-4_5-21b-a3b-bf16-paddle"
mtp_model_path = os.path.join(model_path, "mtp")
mtp_mode_str = json.dumps({"method": "mtp", "num_speculative_tokens": 1, "model": mtp_model_path})
log_path = "server.log"
cmd = [
sys.executable,
"-m",
"fastdeploy.entrypoints.openai.api_server",
"--model",
model_path,
"--port",
str(FD_API_PORT),
"--tensor-parallel-size",
"1",
"--engine-worker-queue-port",
str(FD_ENGINE_QUEUE_PORT),
"--metrics-port",
str(FD_METRICS_PORT),
"--max-model-len",
"32768",
"--max-num-seqs",
"128",
"--quantization",
"wint4",
"--speculative-config",
mtp_mode_str,
]
# Start subprocess in new process group
with open(log_path, "w") as logfile:
process = subprocess.Popen(
cmd,
stdout=logfile,
stderr=subprocess.STDOUT,
start_new_session=True, # Enables killing full group via os.killpg
)
# Wait up to 300 seconds for API server to be ready
for _ in range(300):
if is_port_open("127.0.0.1", FD_API_PORT):
print(f"API server is up on port {FD_API_PORT}")
break
time.sleep(1)
else:
print("[TIMEOUT] API server failed to start in 5 minutes. Cleaning up...")
try:
os.killpg(process.pid, signal.SIGTERM)
except Exception as e:
print(f"Failed to kill process group: {e}")
raise RuntimeError(f"API server did not start on port {FD_API_PORT}")
yield # Run tests
print("\n===== Post-test server cleanup... =====")
try:
os.killpg(process.pid, signal.SIGTERM)
print(f"API server (pid={process.pid}) terminated")
except Exception as e:
print(f"Failed to terminate API server: {e}")
@pytest.fixture(scope="session")
def api_url(request):
"""
Returns the API endpoint URL for chat completions.
"""
return f"http://0.0.0.0:{FD_API_PORT}/v1/chat/completions"
@pytest.fixture(scope="session")
def metrics_url(request):
"""
Returns the metrics endpoint URL.
"""
return f"http://0.0.0.0:{FD_METRICS_PORT}/metrics"
@pytest.fixture
def headers():
"""
Returns common HTTP request headers.
"""
return {"Content-Type": "application/json"}
@pytest.fixture
def consistent_payload():
"""
Returns a fixed payload for consistency testing,
including a fixed random seed and temperature.
"""
return {
"messages": [{"role": "user", "content": "用一句话介绍 PaddlePaddle"}],
"temperature": 0.9,
"top_p": 0, # fix top_p to reduce randomness
"seed": 13, # fixed random seed
}
# ==========================
# Helper function to calculate difference rate between two texts
# ==========================
def calculate_diff_rate(text1, text2):
"""
Calculate the difference rate between two strings
based on the normalized Levenshtein edit distance.
Returns a float in [0,1], where 0 means identical.
"""
if text1 == text2:
return 0.0
len1, len2 = len(text1), len(text2)
dp = [[0] * (len2 + 1) for _ in range(len1 + 1)]
for i in range(len1 + 1):
for j in range(len2 + 1):
if i == 0 or j == 0:
dp[i][j] = i + j
elif text1[i - 1] == text2[j - 1]:
dp[i][j] = dp[i - 1][j - 1]
else:
dp[i][j] = 1 + min(dp[i - 1][j], dp[i][j - 1], dp[i - 1][j - 1])
edit_distance = dp[len1][len2]
max_len = max(len1, len2)
return edit_distance / max_len if max_len > 0 else 0.0
# ==========================
# Consistency test for repeated runs with fixed payload
# ==========================
def test_consistency_between_runs(api_url, headers, consistent_payload):
"""
Test that two runs with the same fixed input produce similar outputs.
"""
# First request
resp1 = requests.post(api_url, headers=headers, json=consistent_payload)
assert resp1.status_code == 200
result1 = resp1.json()
content1 = result1["choices"][0]["message"]["content"]
# Second request
resp2 = requests.post(api_url, headers=headers, json=consistent_payload)
assert resp2.status_code == 200
result2 = resp2.json()
content2 = result2["choices"][0]["message"]["content"]
# Calculate difference rate
diff_rate = calculate_diff_rate(content1, content2)
# Verify that the difference rate is below the threshold
assert diff_rate < 0.05, f"Output difference too large ({diff_rate:.4%})"
# ==========================
# OpenAI Client chat.completions Test
# ==========================
@pytest.fixture
def openai_client():
ip = "0.0.0.0"
service_http_port = str(FD_API_PORT)
client = openai.Client(
base_url=f"http://{ip}:{service_http_port}/v1",
api_key="EMPTY_API_KEY",
)
return client
# Non-streaming test
def test_non_streaming_chat(openai_client):
"""
Test non-streaming chat functionality with the local service
"""
response = openai_client.chat.completions.create(
model="default",
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "List 3 countries and their capitals."},
],
temperature=1,
max_tokens=1024,
stream=False,
)
assert hasattr(response, "choices")
assert len(response.choices) > 0
assert hasattr(response.choices[0], "message")
assert hasattr(response.choices[0].message, "content")
# Streaming test
def test_streaming_chat(openai_client, capsys):
"""
Test streaming chat functionality with the local service
"""
response = openai_client.chat.completions.create(
model="default",
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "List 3 countries and their capitals."},
{
"role": "assistant",
"content": "China(Beijing), France(Paris), Australia(Canberra).",
},
{"role": "user", "content": "OK, tell more."},
],
temperature=1,
max_tokens=1024,
stream=True,
)
output = []
for chunk in response:
if hasattr(chunk.choices[0], "delta") and hasattr(chunk.choices[0].delta, "content"):
output.append(chunk.choices[0].delta.content)
assert len(output) > 2
# ==========================
# OpenAI Client completions Test
# ==========================
def test_non_streaming(openai_client):
"""
Test non-streaming chat functionality with the local service
"""
response = openai_client.completions.create(
model="default",
prompt="Hello, how are you?",
temperature=1,
max_tokens=1024,
stream=False,
)
# Assertions to check the response structure
assert hasattr(response, "choices")
assert len(response.choices) > 0
def test_streaming(openai_client, capsys):
"""
Test streaming functionality with the local service
"""
response = openai_client.completions.create(
model="default",
prompt="Hello, how are you?",
temperature=1,
max_tokens=1024,
stream=True,
)
# Collect streaming output
output = []
for chunk in response:
output.append(chunk.choices[0].text)
assert len(output) > 0
def test_profile_reset_block_num():
"""测试profile reset_block_num功能，与baseline diff不能超过5%"""
log_file = "./log/config.log"
baseline = 30065
if not os.path.exists(log_file):
pytest.fail(f"Log file not found: {log_file}")
with open(log_file, "r") as f:
log_lines = f.readlines()
target_line = None
for line in log_lines:
if "Reset block num" in line:
target_line = line.strip()
break
if target_line is None:
pytest.fail("日志中没有Reset block num信息")
match = re.search(r"total_block_num:(\d+)", target_line)
if not match:
pytest.fail(f"Failed to extract total_block_num from line: {target_line}")
try:
actual_value = int(match.group(1))
except ValueError:
pytest.fail(f"Invalid number format: {match.group(1)}")
lower_bound = baseline * (1 - 0.05)
upper_bound = baseline * (1 + 0.05)
print(f"Reset total_block_num: {actual_value}. baseline: {baseline}")
assert lower_bound <= actual_value <= upper_bound, (
f"Reset total_block_num {actual_value} 与 baseline {baseline} diff需要在5%以内"
f"Allowed range: [{lower_bound:.1f}, {upper_bound:.1f}]"
)