How to do multithreaded infer with onnxruntime

[XiaBing992]

Describe the issue

When I do multithreaded infer via onnxruntime(python), I get an error. My onnx_session are all independent, model files are all read independently, for multithreaded reasoning what should I do?

To reproduce

...
def Infer(self, request, context):
# 推理
log.info('infer...')
model_path = os.path.join(MODEL_DIR, request.model_name)
input = np.array(request.input).astype(np.float32)
......
providers = [
('CUDAExecutionProvider', {
'device_id': 0,
}),
'CPUExecutionProvider',
]
onnx_session = onnxruntime.InferenceSession(model_path, providers = providers)
........

    output = onnx_session.run(output_name, input_feed=input_feed)

    .......

if name == 'main':

thread_num = 50
threads = []
start_time = time.time()
for index in range(thread_num):
    threads.append(threading.Thread(target = Infer, args=......))
    threads[index].start()

for th in threads:
    th.join()

end_time = time.time()

log.info('all time: {}'.format(end_time - start_time))

Urgency

No response

Platform

Linux

OS Version

ubuntu 20.04

ONNX Runtime Installation

Released Package

ONNX Runtime Version or Commit ID

1.18.1

ONNX Runtime API

Python

Architecture

X64

Execution Provider

CUDA

Execution Provider Library Version

12.4

[wejoncy]

Do you want multi-sessions in your senario?
Multiprocessing should work for you.

[github-actions]

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