Merge pull request #327 from MissPenguin/develop
add parameter enable_mkldnn
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commit
d671fefd1e
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@ -17,5 +17,13 @@
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说明:
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- 评估耗时阶段为图像输入到结果输出的完整阶段,包括了图像的预处理和后处理。
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- `Intel至强6148`为服务器端CPU型号,目前正在调试使用Intel MKL-DNN 进一步加速CPU预测速度。
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- `Intel至强6148`为服务器端CPU型号,测试中使用Intel MKL-DNN 加速CPU预测速度,使用该操作需要:
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- 更新到飞桨latest版本:https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev ,请根据自己环境的CUDA版本和Python版本选择相应的mkl版wheel包,如,CUDA10、Python3.7环境,应操作:
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```shell
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# 获取安装包
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wget https://paddle-wheel.bj.bcebos.com/0.0.0-gpu-cuda10-cudnn7-mkl/paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl
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# 安装
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pip3.7 install paddlepaddle_gpu-0.0.0-cp37-cp37m-linux_x86_64.whl
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```
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- 预测时使用参数打开加速开关: `--enable_mkldnn True`
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- `骁龙855`为移动端处理平台型号。
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@ -117,12 +117,16 @@ def main(args):
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image_file_list = get_image_file_list(args.image_dir)
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text_sys = TextSystem(args)
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is_visualize = True
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tackle_img_num = 0
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for image_file in image_file_list:
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img = cv2.imread(image_file)
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if img is None:
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logger.info("error in loading image:{}".format(image_file))
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continue
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starttime = time.time()
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tackle_img_num += 1
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if not args.use_gpu and args.enable_mkldnn and tackle_img_num % 30 == 0:
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text_sys = TextSystem(args)
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dt_boxes, rec_res = text_sys(img)
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elapse = time.time() - starttime
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print("Predict time of %s: %.3fs" % (image_file, elapse))
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@ -64,6 +64,7 @@ def parse_args():
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type=str,
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default="./ppocr/utils/ppocr_keys_v1.txt")
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parser.add_argument("--use_space_char", type=bool, default=True)
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parser.add_argument("--enable_mkldnn", type=bool, default=False)
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return parser.parse_args()
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@ -91,8 +92,10 @@ def create_predictor(args, mode):
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config.enable_use_gpu(args.gpu_mem, 0)
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else:
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config.disable_gpu()
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# config.enable_mkldnn()
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config.set_cpu_math_library_num_threads(4)
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config.set_cpu_math_library_num_threads(6)
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if args.enable_mkldnn:
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config.enable_mkldnn()
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#config.enable_memory_optim()
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config.disable_glog_info()
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