paddlex.deploy.Predictor multithreading execute unet will cause RuntimeError: could not execute a primitive #34492
Description
import os
import numpy as np
from PIL import Image
from multiprocessing.dummy import Pool as ThreadPool
import paddlex as pdx
model = pdx.deploy.Predictor("path/to/model", use_gpu=False)
def handler(img):
print("#")
image = Image.open(img)
image_data = np.asarray(image)
# RGB -> BGR
image_data = image_data[..., ::-1]
model.predict(img, topk=5)
img_dirs = "/path/to/imgs"
files = []
for r, ds, fs in os.walk(img_dirs):
for f in fs:
if f.endswith(".JPG"):
files.append(os.path.join(r, f))
p = ThreadPool()
p.map(handler, files)
p.close()
p.join()as above，loading deeplabv3p model does not report error，but loading unet will report error：
File "test_seg.3.py", line 26, in handler
model.predict(img, topk=5)
File "/home/user/miniconda3/envs/tower/lib/python3.8/site-packages/paddlex/deploy.py", line 278, in predict
model_pred = self.raw_predict(preprocessed_input)
File "/home/user/miniconda3/envs/tower/lib/python3.8/site-packages/paddlex/deploy.py", line 257, in raw_predict
self.predictor.zero_copy_run()
RuntimeError: could not execute a primitive