encountered "out of memory" when run script_rpn_bf_pedestrian_VGG16_caltech_demo

[TaoZheng]

Hi,
Thank you for your sharing~
When I run script_rpn_bf_pedestrian_VGG16_caltech_demo to see the detection results,I have encountered the following problems.(Remarks: failed to use cudnn,so I modified the Makefile.config to disable the cudnn before compling).
I0108 18:23:22.370462 4073 net.cpp:90] Creating Layer roi_pool4_3_flat
I0108 18:23:22.370471 4073 net.cpp:420] roi_pool4_3_flat <- roi_pool4_3
I0108 18:23:22.370479 4073 net.cpp:378] roi_pool4_3_flat -> roi_pool4_3_flat
I0108 18:23:22.370491 4073 net.cpp:120] Setting up roi_pool4_3_flat
I0108 18:23:22.370501 4073 net.cpp:127] Top shape: 1 25088 (25088)
I0108 18:23:22.370507 4073 layer_factory.hpp:74] Creating layer concat_feat
I0108 18:23:22.370517 4073 net.cpp:90] Creating Layer concat_feat
I0108 18:23:22.370523 4073 net.cpp:420] concat_feat <- roi_pool3_flat
I0108 18:23:22.370532 4073 net.cpp:420] concat_feat <- roi_pool4_3_flat
I0108 18:23:22.370542 4073 net.cpp:378] concat_feat -> concat_feat
I0108 18:23:22.370550 4073 net.cpp:120] Setting up concat_feat
I0108 18:23:22.370561 4073 net.cpp:127] Top shape: 1 50176 (50176)
I0108 18:23:22.370568 4073 net.cpp:194] concat_feat does not need backward computation.
I0108 18:23:22.370576 4073 net.cpp:194] roi_pool4_3_flat does not need backward computation.
I0108 18:23:22.370584 4073 net.cpp:194] roi_pool3_flat does not need backward computation.
I0108 18:23:22.370590 4073 net.cpp:194] roi_pool4_3 does not need backward computation.
I0108 18:23:22.370597 4073 net.cpp:194] roi_pool3 does not need backward computation.
I0108 18:23:22.370605 4073 net.cpp:194] rois_input_2_split does not need backward computation.
I0108 18:23:22.370612 4073 net.cpp:235] This network produces output concat_feat
I0108 18:23:22.370625 4073 net.cpp:492] Collecting Learning Rate and Weight Decay.
I0108 18:23:22.370632 4073 net.cpp:247] Network initialization done.
I0108 18:23:22.370640 4073 net.cpp:248] Memory required for data: 602152
F0108 18:23:27.069090 4073 syncedmem.cpp:51] Check failed: error == cudaSuccess (2 vs. 0) out of memory
*** Check failure stack trace: ***
Killed

Is it caused by the disable cudnn?How should I fix this problem? Any suggestions are very grateful!Thank you very much.

[zhangliliang]

The VGG model needs lots of GPU memory. Thus you might need a titanx or k40 when you disable the cuDNN.