Created by: LeeYongchao

• 版本、环境信息 1）hub.version'1.7.1' 2）paddle.version'1.7.2' 3）ubuntu16.04

4. cuda10 5）paddle.fluid.install_check.run_check() Running Verify Paddle Program ... W0610 10:19:19.803442 8827 device_context.cc:237] Please NOTE: device: 0, CUDA Capability: 75, Driver API Version: 10.1, Runtime API Version: 9.0 W0610 10:19:19.805452 8827 device_context.cc:245] device: 0, cuDNN Version: 7.6. Your Paddle works well on SINGLE GPU or CPU. I0610 10:19:20.703788 8827 parallel_executor.cc:440] The Program will be executed on CUDA using ParallelExecutor, 1 cards are used, so 1 programs are executed in parallel. I0610 10:19:20.704022 8827 build_strategy.cc:365] SeqOnlyAllReduceOps:0, num_trainers:1 I0610 10:19:20.704203 8827 parallel_executor.cc:307] Inplace strategy is enabled, when build_strategy.enable_inplace = True I0610 10:19:20.704339 8827 parallel_executor.cc:375] Garbage collection strategy is enabled, when FLAGS_eager_delete_tensor_gb = 0 Your Paddle works well on MUTIPLE GPU or CPU. Your Paddle is installed successfully! Let's start deep Learning with Paddle now

• 我的显存有6G，如果您的显存很大，请多放图片，会看到 显存一直增长 不回收
• 代码很简单，如下： 首先 export CUDA_VISIBLE_DEVICES=0 import os import paddlehub as hub ocr = hub.Module(name="chinese_ocr_db_crnn_server") img_l=os.listdir('./static/images/') # 本目录有20张带文字的图片，如果您显存大，请多放 for img in img_l: _ = ocr.recognize_text(paths=['./static/images/'+img], use_gpu=True)

报错如下：

Error Message Summary:

ResourceExhaustedError:

Out of memory error on GPU 0. Cannot allocate 29.883057MB memory on GPU 0, available memory is only 22.750000MB.

Please check whether there is any other process using GPU 0.

1. If yes, please stop them, or start PaddlePaddle on another GPU.
2. If no, please decrease the batch size of your model.

at (/paddle/paddle/fluid/memory/allocation/cuda_allocator.cc:69)