I0517 17:20:57.718914 4852 layer_factory.hpp:77] Creating layer data
I0517 17:20:57.718928 4852 net.cpp:94] Creating Layer data
I0517 17:20:57.718935 4852 net.cpp:409] data -> data
I0517 17:20:57.718951 4852 net.cpp:409] data -> label
I0517 17:20:57.718967 4852 hdf5_data_layer.cpp:79] Loading list of HDF5 filenames from: /mnt/lab-raid2/home/A/train.txt
I0517 17:20:57.720168 4852 hdf5_data_layer.cpp:93] Number of HDF5 files: 1
I0517 17:20:57.722488 4852 hdf5.cpp:32] Datatype class: H5T_FLOAT
I0517 17:20:57.730764 4852 net.cpp:144] Setting up data
I0517 17:20:57.730803 4852 net.cpp:151] Top shape: 22 1 33 33 (23958)
I0517 17:20:57.730808 4852 net.cpp:151] Top shape: 22 1 21 21 (9702)
I0517 17:20:57.730810 4852 net.cpp:159] Memory required for data: 134640
I0517 17:20:57.730818 4852 layer_factory.hpp:77] Creating layer conv1
I0517 17:20:57.730851 4852 net.cpp:94] Creating Layer conv1
I0517 17:20:57.730856 4852 net.cpp:435] conv1 <- data
I0517 17:20:57.730871 4852 net.cpp:409] conv1 -> conv1
I0517 17:20:57.738759 4852 net.cpp:144] Setting up conv1
I0517 17:20:57.738811 4852 net.cpp:151] Top shape: 22 96 29 29 (1776192)
I0517 17:20:57.738821 4852 net.cpp:159] Memory required for data: 7239408
I0517 17:20:57.738858 4852 layer_factory.hpp:77] Creating layer relu1
I0517 17:20:57.738883 4852 net.cpp:94] Creating Layer relu1
I0517 17:20:57.738893 4852 net.cpp:435] relu1 <- conv1
I0517 17:20:57.738907 4852 net.cpp:396] relu1 -> conv1 (in-place)
I0517 17:20:57.738943 4852 net.cpp:144] Setting up relu1
I0517 17:20:57.738957 4852 net.cpp:151] Top shape: 22 96 29 29 (1776192)
I0517 17:20:57.738966 4852 net.cpp:159] Memory required for data: 14344176
I0517 17:20:57.738976 4852 layer_factory.hpp:77] Creating layer conv2
I0517 17:20:57.739048 4852 net.cpp:94] Creating Layer conv2
I0517 17:20:57.739058 4852 net.cpp:435] conv2 <- conv1
I0517 17:20:57.739074 4852 net.cpp:409] conv2 -> conv2
I0517 17:20:57.742362 4852 net.cpp:144] Setting up conv2
I0517 17:20:57.742391 4852 net.cpp:151] Top shape: 22 24 29 29 (444048)
I0517 17:20:57.742401 4852 net.cpp:159] Memory required for data: 16120368
I0517 17:20:57.742421 4852 layer_factory.hpp:77] Creating layer relu2
I0517 17:20:57.742439 4852 net.cpp:94] Creating Layer relu2
I0517 17:20:57.742449 4852 net.cpp:435] relu2 <- conv2
I0517 17:20:57.742465 4852 net.cpp:396] relu2 -> conv2 (in-place)
I0517 17:20:57.742483 4852 net.cpp:144] Setting up relu2
I0517 17:20:57.742494 4852 net.cpp:151] Top shape: 22 24 29 29 (444048)
I0517 17:20:57.742502 4852 net.cpp:159] Memory required for data: 17896560
I0517 17:20:57.742512 4852 layer_factory.hpp:77] Creating layer conv3
I0517 17:20:57.742532 4852 net.cpp:94] Creating Layer conv3
I0517 17:20:57.742540 4852 net.cpp:435] conv3 <- conv2
I0517 17:20:57.742554 4852 net.cpp:409] conv3 -> conv3
I0517 17:20:57.747347 4852 net.cpp:144] Setting up conv3
I0517 17:20:57.747378 4852 net.cpp:151] Top shape: 22 1 29 29 (18502)
I0517 17:20:57.747387 4852 net.cpp:159] Memory required for data: 17970568
I0517 17:20:57.747408 4852 layer_factory.hpp:77] Creating layer loss
I0517 17:20:57.747427 4852 net.cpp:94] Creating Layer loss
I0517 17:20:57.747437 4852 net.cpp:435] loss <- conv3
I0517 17:20:57.747448 4852 net.cpp:435] loss <- label
I0517 17:20:57.747462 4852 net.cpp:409] loss -> loss
F0517 17:20:57.747512 4852 euclidean_loss_layer.cpp:12] Check failed: bottom[0]->count(1) == bottom[1]->count(1) (841 vs. 441) Inputs must have the same dimension.
*** Check failure stack trace: ***
@ 0x2af492d685cd google::LogMessage::Fail()
@ 0x2af492d6a433 google::LogMessage::SendToLog()
@ 0x2af492d6815b google::LogMessage::Flush()
@ 0x2af492d6ae1e google::LogMessageFatal::~LogMessageFatal()
@ 0x2af49213fe52 caffe::EuclideanLossLayer<>::Reshape()
@ 0x2af4922618f6 caffe::Net<>::Init()
@ 0x2af4922631c6 caffe::Net<>::Net()
@ 0x2af492243cca caffe::Solver<>::InitTrainNet()
@ 0x2af4922450d7 caffe::Solver<>::Init()
@ 0x2af492245493 caffe::Solver<>::Solver()
@ 0x2af4922ce4b5 caffe::Creator_SGDSolver<>()
@ 0x40b9a5 train()
@ 0x408668 main
@ 0x2af4941a7830 __libc_start_main
@ 0x408dd9 _start
@ (nil) (unknown)
How do I solve this problem?How do I fixed the same dimension?Here I add the network.I use HDF5D in matlab.