I got a error when I run "train.sh" in demo/image_classification
I0907 14:35:07.593504 49407 Util.cpp:144] commandline: /home/hadoop/paddle/paddle/build/bin/../opt/paddle/bin/paddle_trainer --config=vgg_16_cifar.py --dot_period=10 --log_period=100 --test_all_data_in_one_period=1 --use_gpu=1 --trainer_count=1 --num_passes=200 --save_dir=./cifar_vgg_model
I0907 14:35:08.002375 49407 Util.cpp:113] Calling runInitFunctions
I0907 14:35:08.002609 49407 Util.cpp:126] Call runInitFunctions done.
[INFO 2016-09-07 14:35:08,043 layers.py:1438] channels=3 size=3072
[INFO 2016-09-07 14:35:08,043 layers.py:1438] output size for conv_0 is 32
[INFO 2016-09-07 14:35:08,044 layers.py:1438] channels=64 size=65536
[INFO 2016-09-07 14:35:08,045 layers.py:1438] output size for conv_1 is 32
[INFO 2016-09-07 14:35:08,046 layers.py:1499] output size for pool_0 is 16_16
[INFO 2016-09-07 14:35:08,046 layers.py:1438] channels=64 size=16384
[INFO 2016-09-07 14:35:08,046 layers.py:1438] output size for conv_2 is 16
[INFO 2016-09-07 14:35:08,047 layers.py:1438] channels=128 size=32768
[INFO 2016-09-07 14:35:08,048 layers.py:1438] output size for conv_3 is 16
[INFO 2016-09-07 14:35:08,049 layers.py:1499] output size for pool_1 is 8_8
[INFO 2016-09-07 14:35:08,049 layers.py:1438] channels=128 size=8192
[INFO 2016-09-07 14:35:08,049 layers.py:1438] output size for conv_4 is 8
[INFO 2016-09-07 14:35:08,051 layers.py:1438] channels=256 size=16384
[INFO 2016-09-07 14:35:08,051 layers.py:1438] output size for conv_5 is 8
[INFO 2016-09-07 14:35:08,052 layers.py:1438] channels=256 size=16384
[INFO 2016-09-07 14:35:08,052 layers.py:1438] output size for conv_6 is 8
[INFO 2016-09-07 14:35:08,053 layers.py:1499] output size for pool_2 is 4_4
[INFO 2016-09-07 14:35:08,054 layers.py:1438] channels=256 size=4096
[INFO 2016-09-07 14:35:08,054 layers.py:1438] output size for conv_7 is 4
[INFO 2016-09-07 14:35:08,055 layers.py:1438] channels=512 size=8192
[INFO 2016-09-07 14:35:08,055 layers.py:1438] output size for conv_8 is 4
[INFO 2016-09-07 14:35:08,056 layers.py:1438] channels=512 size=8192
[INFO 2016-09-07 14:35:08,056 layers.py:1438] output size for conv_9 is 4
[INFO 2016-09-07 14:35:08,058 layers.py:1499] output size for pool_3 is 2_2
[INFO 2016-09-07 14:35:08,058 layers.py:1499] output size for pool_4 is 1_1
[INFO 2016-09-07 14:35:08,060 networks.py:1122] The input order is [image, label]
[INFO 2016-09-07 14:35:08,060 networks.py:1129] The output order is [cost_0]
I0907 14:35:08.067443 49407 Trainer.cpp:169] trainer mode: Normal
I0907 14:35:08.075389 49407 PyDataProvider2.cpp:219] loading dataprovider image_provider::processData
[INFO 2016-09-07 14:35:08,109 image_provider.py:52] Image size: 32
[INFO 2016-09-07 14:35:08,109 image_provider.py:53] Meta path: data/cifar-out/batches/batches.meta
[INFO 2016-09-07 14:35:08,109 image_provider.py:58] DataProvider Initialization finished
I0907 14:35:08.109668 49407 PyDataProvider2.cpp:219] loading dataprovider image_provider::processData
[INFO 2016-09-07 14:35:08,109 image_provider.py:52] Image size: 32
[INFO 2016-09-07 14:35:08,109 image_provider.py:53] Meta path: data/cifar-out/batches/batches.meta
[INFO 2016-09-07 14:35:08,109 image_provider.py:58] DataProvider Initialization finished
I0907 14:35:08.109978 49407 GradientMachine.cpp:134] Initing parameters..
I0907 14:35:08.554066 49407 GradientMachine.cpp:141] Init parameters done.
Current Layer forward/backward stack is
LayerName: batch_norm_10
LayerName: fc_layer_0
LayerName: dropout_0
LayerName: pool_4
LayerName: pool_3
LayerName: batch_norm_9
LayerName: conv_9
LayerName: batch_norm_8
LayerName: conv_8
LayerName: batch_norm_7
LayerName: conv_7
LayerName: pool_2
LayerName: batch_norm_6
LayerName: conv_6
LayerName: batch_norm_5
LayerName: conv_5
LayerName: batch_norm_4
LayerName: conv_4
LayerName: pool_1
LayerName: batch_norm_3
LayerName: conv_3
LayerName: batch_norm_2
LayerName: conv_2
LayerName: pool_0
LayerName: batch_norm_1
LayerName: conv_1
LayerName: batch_norm_0
LayerName: conv_0
LayerName: image
*_* Aborted at 1473230129 (unix time) try "date -d @1473230129" if you are using GNU date ***
Current Layer forward/backward stack is
PC: @ 0x7fb72227a855 (unknown)
Current Layer forward/backward stack is
*** SIGSEGV (@0x130701aa00) received by PID 49407 (TID 0x7fb7386fe800) from PID 117549568; stack trace: ***
Current Layer forward/backward stack is
@ 0x7fb737fdf100 (unknown)
Current Layer forward/backward stack is
@ 0x7fb72227a855 (unknown)
Current Layer forward/backward stack is
@ 0x8b3350 hl_batch_norm_backward()
Current Layer forward/backward stack is
@ 0x5d4684 paddle::CudnnBatchNormLayer::backward()
Current Layer forward/backward stack is
@ 0x620bae paddle::NeuralNetwork::backward()
Current Layer forward/backward stack is
@ 0x69c95d paddle::TrainerInternal::forwardBackwardBatch()
Current Layer forward/backward stack is
@ 0x69cf14 paddle::TrainerInternal::trainOneBatch()
Current Layer forward/backward stack is
@ 0x698350 paddle::Trainer::trainOnePass()
Current Layer forward/backward stack is
@ 0x69ba47 paddle::Trainer::train()
Current Layer forward/backward stack is
@ 0x53aea3 main
Current Layer forward/backward stack is
@ 0x7fb73587bb15 __libc_start_main
Current Layer forward/backward stack is
@ 0x545b15 (unknown)
/home/hadoop/paddle/paddle/build/bin/paddle: line 46: 49407 Segmentation fault (core dumped) ${DEBUGGER} $MYDIR/../opt/paddle/bin/paddle_trainer ${@:2}
No data to plot. Exiting!

Someone know why?