1，安装cuda

2，安装cudnn

3，安装libnccl.so

4，测试多gpu分配运行内容

在代码中如何分配资源：通过gpu_id来指定相应的gpu

from paddleocr import PaddleOCR, draw_ocr
import paddle
import paddleocr
import time
from PIL import Image
import numpy as np
import os
# paddleocr.DEFAULT_OCR_MODEL_VERSION = 'PP-OCRv4'
if __name__ == '__main__':
    # paddle.device.set_device("gpu:1")
    # print(paddle.device.get_device())
    #os.environ['CUDA_VISIBLE_DEVICES']='1'
    ocr = PaddleOCR(use_angle_cls=True, lang="ch",ocr_version="PP-OCRv4",gpu_id=1)
    img = Image.open('00000003.tif').convert('RGB')
    for i in range(10000):
        start = time.time()
        # result = ocr.ocr(np.array(img), cls=True)
        result = ocr.ocr(np.array(img))
        end = time.time()
        print('time:', (end-start))

    # for line in result:
    #     print(line)