Created by: tangbozhang

执行官方例程 【AI Studio 官方课程】第九节：深度学习进阶（计算机视觉）实践-目标检测，aistudio上运行正常，在本地运行时报错如下： 本地运行环境：win10 64位，cuda10，paddle 1.6.1 ，运行其他例程正常。

EnforceNotMet Traceback (most recent call last) in 20 21 #构造训练用的program ---> 22 train_reader, img, loss, locs, confs, box, box_var = build_train_program_with_async_reader(train_program, start_program) 23 24 print('model success!')

in build_train_program_with_async_reader(main_prog, startup_prog) 9 data_reader = fluid.layers.create_py_reader_by_data(capacity=64, #缓冲区容量 10 feed_list=[img, gt_box, gt_label, difficult], #传输数据列表 ---> 11 name='train') #reader名称 12 #多进程reader，使用python多进程从reader中读取数据 13 multi_reader = multi_process_custom_reader(train_parameters['file_list'],

D:\softwareinstall\deeplearn\anaconda3\envs\paddle\lib\site-packages\paddle\fluid\layers\io.py in create_py_reader_by_data(capacity, feed_list, name, use_double_buffer) 777 name=name, 778 use_double_buffer=use_double_buffer, --> 779 feed_list=feed_list) 780 781

D:\softwareinstall\deeplearn\anaconda3\envs\paddle\lib\site-packages\paddle\fluid\layers\io.py in _py_reader(capacity, shapes, dtypes, lod_levels, name, use_double_buffer, feed_list) 415 416 var = global_scope().var(queue_name) --> 417 feed_queue = core.init_lod_tensor_blocking_queue(var, capacity) 418 419 startup_blk = default_startup_program().current_block()

EnforceNotMet:

C++ Call Stacks (More useful to developers):

Windows not support stack backtrace yet.

Error Message Summary:

PaddleCheckError: LoDTensorBlockingQueueHolder::InitOnce() can only be called once at [D:\1.6.1\paddle\paddle/fluid/operators/reader/lod_tensor_blocking_queue.h:77]

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Thank you for contributing to PaddlePaddle. Before submitting the issue, you could search issue in the github in case that there was a similar issue submitted or resolved before. If there is no solution,please make sure that this is a training issue including the following details: System information -PaddlePaddle version （eg.1.1）or CommitID -CPU: including CPUMKL/OpenBlas/MKLDNN version -GPU: including CUDA/CUDNN version -OS Platform (eg.Mac OS 10.14) -Other imformation: Distriuted training/informantion of operator/ Graphics card storage To Reproduce Steps to reproduce the behavior Describe your current behavior Code to reproduce the issue Other info / logs