[CI] Add test for paddleocr_vl (#4627)

This commit is contained in:
Haonan Luo
2025-10-30 13:40:04 +08:00
committed by GitHub
parent cd3b7cc392
commit d7d0112bbf
2 changed files with 281 additions and 0 deletions

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@@ -147,6 +147,7 @@ class DataProcessor:
"num_input_video_tokens": 0,
"fps": [],
"mm_positions": [],
"mm_hashes": [],
"vit_seqlen": [],
"vit_position_ids": [],
}

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@@ -0,0 +1,280 @@
# 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 shutil
import signal
import socket
import subprocess
import sys
import time
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))
FD_CACHE_QUEUE_PORT = int(os.getenv("FD_CACHE_QUEUE_PORT", 8333))
# List of ports to clean before and after tests
PORTS_TO_CLEAN = [FD_API_PORT, FD_ENGINE_QUEUE_PORT, FD_METRICS_PORT, FD_CACHE_QUEUE_PORT]
os.environ["FD_USE_MACHETE"] = "0"
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()
current_pid = os.getpid()
parent_pid = os.getppid()
for pid in output.splitlines():
pid = int(pid)
if pid in (current_pid, parent_pid):
print(f"Skip killing current process (pid={pid}) on port {port}")
continue
os.kill(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)
time.sleep(2)
@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()
print("log dir clean ")
if os.path.exists("log") and os.path.isdir("log"):
shutil.rmtree("log")
base_path = os.getenv("MODEL_PATH")
if base_path:
model_path = os.path.join(base_path, "PaddleOCR-VL-0.9B")
else:
model_path = "./PaddleOCR-VL-0.9B"
log_path = "server.log"
limit_mm_str = json.dumps({"image": 100, "video": 100})
cmd = [
sys.executable,
"-m",
"fastdeploy.entrypoints.openai.api_server",
"--model",
model_path,
"--port",
str(FD_API_PORT),
"--tensor-parallel-size",
"2",
"--engine-worker-queue-port",
str(FD_ENGINE_QUEUE_PORT),
"--metrics-port",
str(FD_METRICS_PORT),
"--cache-queue-port",
str(FD_CACHE_QUEUE_PORT),
"--enable-mm",
"--max-model-len",
"32768",
"--max-num-batched-tokens",
"384",
"--max-num-seqs",
"128",
"--limit-mm-per-prompt",
limit_mm_str,
"--enable-chunked-prefill",
"--kv-cache-ratio",
"0.71",
"--quantization",
"wint4",
"--graph-optimization-config",
'{"graph_opt_level":0, "use_cudagraph":true}',
]
# 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 10 minutes for API server to be ready
for _ in range(10 * 60):
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")
clean_ports()
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": [
{
"type": "image_url",
"image_url": {
"url": "https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/dataset/ocr_v5_eval/handwrite_ch_rec_val/中文手写古籍_000054_crop_32.jpg",
},
},
{"type": "text", "text": "OCR:"},
],
}
],
"temperature": 0.8,
"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"]
print(content1)
# 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"]
print(content2)
# 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%})"
assert content1 == "生甘草"