DIGITS-CNN/cars/lr-investigations/fixed/1e-4/caffe_output.log

I0405 12:47:16.936889 18799 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210405-110229-8c6c/solver.prototxt
I0405 12:47:16.937041 18799 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string).
W0405 12:47:16.937045 18799 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type.
I0405 12:47:16.937100 18799 caffe.cpp:218] Using GPUs 0
I0405 12:47:16.959851 18799 caffe.cpp:223] GPU 0: GeForce GTX TITAN X
I0405 12:47:17.186710 18799 solver.cpp:44] Initializing solver from parameters:
test_iter: 51
test_interval: 102
base_lr: 0.0001
display: 12
max_iter: 20400
lr_policy: "fixed"
momentum: 0.9
weight_decay: 1e-06
snapshot: 102
snapshot_prefix: "snapshot"
solver_mode: GPU
device_id: 0
net: "train_val.prototxt"
train_state {
level: 0
stage: ""
}
type: "SGD"
I0405 12:47:17.187651 18799 solver.cpp:87] Creating training net from net file: train_val.prototxt
I0405 12:47:17.188313 18799 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data
I0405 12:47:17.188326 18799 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy
I0405 12:47:17.188446 18799 net.cpp:51] Initializing net from parameters:
state {
phase: TRAIN
level: 0
stage: ""
}
layer {
name: "train-data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_file: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto"
}
data_param {
source: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/train_db"
batch_size: 128
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "norm1"
type: "LRN"
bottom: "conv1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "norm1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "norm2"
type: "LRN"
bottom: "conv2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "norm2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "fc7"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 196
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8"
bottom: "label"
top: "loss"
}
I0405 12:47:17.188529 18799 layer_factory.hpp:77] Creating layer train-data
I0405 12:47:17.203459 18799 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/train_db
I0405 12:47:17.203706 18799 net.cpp:84] Creating Layer train-data
I0405 12:47:17.203722 18799 net.cpp:380] train-data -> data
I0405 12:47:17.203742 18799 net.cpp:380] train-data -> label
I0405 12:47:17.203752 18799 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0405 12:47:17.208353 18799 data_layer.cpp:45] output data size: 128,3,227,227
I0405 12:47:17.344980 18799 net.cpp:122] Setting up train-data
I0405 12:47:17.345002 18799 net.cpp:129] Top shape: 128 3 227 227 (19787136)
I0405 12:47:17.345006 18799 net.cpp:129] Top shape: 128 (128)
I0405 12:47:17.345008 18799 net.cpp:137] Memory required for data: 79149056
I0405 12:47:17.345016 18799 layer_factory.hpp:77] Creating layer conv1
I0405 12:47:17.345036 18799 net.cpp:84] Creating Layer conv1
I0405 12:47:17.345041 18799 net.cpp:406] conv1 <- data
I0405 12:47:17.345052 18799 net.cpp:380] conv1 -> conv1
I0405 12:47:17.767601 18799 net.cpp:122] Setting up conv1
I0405 12:47:17.767621 18799 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 12:47:17.767623 18799 net.cpp:137] Memory required for data: 227833856
I0405 12:47:17.767642 18799 layer_factory.hpp:77] Creating layer relu1
I0405 12:47:17.767652 18799 net.cpp:84] Creating Layer relu1
I0405 12:47:17.767654 18799 net.cpp:406] relu1 <- conv1
I0405 12:47:17.767659 18799 net.cpp:367] relu1 -> conv1 (in-place)
I0405 12:47:17.767916 18799 net.cpp:122] Setting up relu1
I0405 12:47:17.767925 18799 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 12:47:17.767926 18799 net.cpp:137] Memory required for data: 376518656
I0405 12:47:17.767930 18799 layer_factory.hpp:77] Creating layer norm1
I0405 12:47:17.767937 18799 net.cpp:84] Creating Layer norm1
I0405 12:47:17.767940 18799 net.cpp:406] norm1 <- conv1
I0405 12:47:17.767966 18799 net.cpp:380] norm1 -> norm1
I0405 12:47:17.768399 18799 net.cpp:122] Setting up norm1
I0405 12:47:17.768409 18799 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 12:47:17.768410 18799 net.cpp:137] Memory required for data: 525203456
I0405 12:47:17.768414 18799 layer_factory.hpp:77] Creating layer pool1
I0405 12:47:17.768419 18799 net.cpp:84] Creating Layer pool1
I0405 12:47:17.768422 18799 net.cpp:406] pool1 <- norm1
I0405 12:47:17.768426 18799 net.cpp:380] pool1 -> pool1
I0405 12:47:17.768457 18799 net.cpp:122] Setting up pool1
I0405 12:47:17.768462 18799 net.cpp:129] Top shape: 128 96 27 27 (8957952)
I0405 12:47:17.768465 18799 net.cpp:137] Memory required for data: 561035264
I0405 12:47:17.768466 18799 layer_factory.hpp:77] Creating layer conv2
I0405 12:47:17.768476 18799 net.cpp:84] Creating Layer conv2
I0405 12:47:17.768477 18799 net.cpp:406] conv2 <- pool1
I0405 12:47:17.768481 18799 net.cpp:380] conv2 -> conv2
I0405 12:47:17.773975 18799 net.cpp:122] Setting up conv2
I0405 12:47:17.773990 18799 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 12:47:17.773993 18799 net.cpp:137] Memory required for data: 656586752
I0405 12:47:17.774003 18799 layer_factory.hpp:77] Creating layer relu2
I0405 12:47:17.774008 18799 net.cpp:84] Creating Layer relu2
I0405 12:47:17.774011 18799 net.cpp:406] relu2 <- conv2
I0405 12:47:17.774015 18799 net.cpp:367] relu2 -> conv2 (in-place)
I0405 12:47:17.774475 18799 net.cpp:122] Setting up relu2
I0405 12:47:17.774484 18799 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 12:47:17.774487 18799 net.cpp:137] Memory required for data: 752138240
I0405 12:47:17.774488 18799 layer_factory.hpp:77] Creating layer norm2
I0405 12:47:17.774494 18799 net.cpp:84] Creating Layer norm2
I0405 12:47:17.774497 18799 net.cpp:406] norm2 <- conv2
I0405 12:47:17.774502 18799 net.cpp:380] norm2 -> norm2
I0405 12:47:17.774757 18799 net.cpp:122] Setting up norm2
I0405 12:47:17.774765 18799 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 12:47:17.774767 18799 net.cpp:137] Memory required for data: 847689728
I0405 12:47:17.774770 18799 layer_factory.hpp:77] Creating layer pool2
I0405 12:47:17.774776 18799 net.cpp:84] Creating Layer pool2
I0405 12:47:17.774778 18799 net.cpp:406] pool2 <- norm2
I0405 12:47:17.774782 18799 net.cpp:380] pool2 -> pool2
I0405 12:47:17.774806 18799 net.cpp:122] Setting up pool2
I0405 12:47:17.774809 18799 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 12:47:17.774811 18799 net.cpp:137] Memory required for data: 869840896
I0405 12:47:17.774814 18799 layer_factory.hpp:77] Creating layer conv3
I0405 12:47:17.774821 18799 net.cpp:84] Creating Layer conv3
I0405 12:47:17.774823 18799 net.cpp:406] conv3 <- pool2
I0405 12:47:17.774827 18799 net.cpp:380] conv3 -> conv3
I0405 12:47:17.784315 18799 net.cpp:122] Setting up conv3
I0405 12:47:17.784327 18799 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 12:47:17.784329 18799 net.cpp:137] Memory required for data: 903067648
I0405 12:47:17.784337 18799 layer_factory.hpp:77] Creating layer relu3
I0405 12:47:17.784343 18799 net.cpp:84] Creating Layer relu3
I0405 12:47:17.784344 18799 net.cpp:406] relu3 <- conv3
I0405 12:47:17.784348 18799 net.cpp:367] relu3 -> conv3 (in-place)
I0405 12:47:17.784761 18799 net.cpp:122] Setting up relu3
I0405 12:47:17.784770 18799 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 12:47:17.784772 18799 net.cpp:137] Memory required for data: 936294400
I0405 12:47:17.784775 18799 layer_factory.hpp:77] Creating layer conv4
I0405 12:47:17.784782 18799 net.cpp:84] Creating Layer conv4
I0405 12:47:17.784785 18799 net.cpp:406] conv4 <- conv3
I0405 12:47:17.784790 18799 net.cpp:380] conv4 -> conv4
I0405 12:47:17.793893 18799 net.cpp:122] Setting up conv4
I0405 12:47:17.793910 18799 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 12:47:17.793911 18799 net.cpp:137] Memory required for data: 969521152
I0405 12:47:17.793918 18799 layer_factory.hpp:77] Creating layer relu4
I0405 12:47:17.793926 18799 net.cpp:84] Creating Layer relu4
I0405 12:47:17.793948 18799 net.cpp:406] relu4 <- conv4
I0405 12:47:17.793952 18799 net.cpp:367] relu4 -> conv4 (in-place)
I0405 12:47:17.794260 18799 net.cpp:122] Setting up relu4
I0405 12:47:17.794268 18799 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 12:47:17.794270 18799 net.cpp:137] Memory required for data: 1002747904
I0405 12:47:17.794273 18799 layer_factory.hpp:77] Creating layer conv5
I0405 12:47:17.794282 18799 net.cpp:84] Creating Layer conv5
I0405 12:47:17.794286 18799 net.cpp:406] conv5 <- conv4
I0405 12:47:17.794289 18799 net.cpp:380] conv5 -> conv5
I0405 12:47:17.802953 18799 net.cpp:122] Setting up conv5
I0405 12:47:17.802970 18799 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 12:47:17.802973 18799 net.cpp:137] Memory required for data: 1024899072
I0405 12:47:17.802984 18799 layer_factory.hpp:77] Creating layer relu5
I0405 12:47:17.802994 18799 net.cpp:84] Creating Layer relu5
I0405 12:47:17.802997 18799 net.cpp:406] relu5 <- conv5
I0405 12:47:17.803001 18799 net.cpp:367] relu5 -> conv5 (in-place)
I0405 12:47:17.803483 18799 net.cpp:122] Setting up relu5
I0405 12:47:17.803490 18799 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 12:47:17.803493 18799 net.cpp:137] Memory required for data: 1047050240
I0405 12:47:17.803495 18799 layer_factory.hpp:77] Creating layer pool5
I0405 12:47:17.803501 18799 net.cpp:84] Creating Layer pool5
I0405 12:47:17.803504 18799 net.cpp:406] pool5 <- conv5
I0405 12:47:17.803509 18799 net.cpp:380] pool5 -> pool5
I0405 12:47:17.803542 18799 net.cpp:122] Setting up pool5
I0405 12:47:17.803546 18799 net.cpp:129] Top shape: 128 256 6 6 (1179648)
I0405 12:47:17.803548 18799 net.cpp:137] Memory required for data: 1051768832
I0405 12:47:17.803550 18799 layer_factory.hpp:77] Creating layer fc6
I0405 12:47:17.803560 18799 net.cpp:84] Creating Layer fc6
I0405 12:47:17.803562 18799 net.cpp:406] fc6 <- pool5
I0405 12:47:17.803566 18799 net.cpp:380] fc6 -> fc6
I0405 12:47:18.133078 18799 net.cpp:122] Setting up fc6
I0405 12:47:18.133100 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.133101 18799 net.cpp:137] Memory required for data: 1053865984
I0405 12:47:18.133111 18799 layer_factory.hpp:77] Creating layer relu6
I0405 12:47:18.133123 18799 net.cpp:84] Creating Layer relu6
I0405 12:47:18.133127 18799 net.cpp:406] relu6 <- fc6
I0405 12:47:18.133132 18799 net.cpp:367] relu6 -> fc6 (in-place)
I0405 12:47:18.133752 18799 net.cpp:122] Setting up relu6
I0405 12:47:18.133760 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.133762 18799 net.cpp:137] Memory required for data: 1055963136
I0405 12:47:18.133765 18799 layer_factory.hpp:77] Creating layer drop6
I0405 12:47:18.133770 18799 net.cpp:84] Creating Layer drop6
I0405 12:47:18.133774 18799 net.cpp:406] drop6 <- fc6
I0405 12:47:18.133778 18799 net.cpp:367] drop6 -> fc6 (in-place)
I0405 12:47:18.133801 18799 net.cpp:122] Setting up drop6
I0405 12:47:18.133805 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.133807 18799 net.cpp:137] Memory required for data: 1058060288
I0405 12:47:18.133810 18799 layer_factory.hpp:77] Creating layer fc7
I0405 12:47:18.133817 18799 net.cpp:84] Creating Layer fc7
I0405 12:47:18.133819 18799 net.cpp:406] fc7 <- fc6
I0405 12:47:18.133824 18799 net.cpp:380] fc7 -> fc7
I0405 12:47:18.281322 18799 net.cpp:122] Setting up fc7
I0405 12:47:18.281342 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.281344 18799 net.cpp:137] Memory required for data: 1060157440
I0405 12:47:18.281352 18799 layer_factory.hpp:77] Creating layer relu7
I0405 12:47:18.281361 18799 net.cpp:84] Creating Layer relu7
I0405 12:47:18.281365 18799 net.cpp:406] relu7 <- fc7
I0405 12:47:18.281370 18799 net.cpp:367] relu7 -> fc7 (in-place)
I0405 12:47:18.281733 18799 net.cpp:122] Setting up relu7
I0405 12:47:18.281741 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.281744 18799 net.cpp:137] Memory required for data: 1062254592
I0405 12:47:18.281746 18799 layer_factory.hpp:77] Creating layer drop7
I0405 12:47:18.281751 18799 net.cpp:84] Creating Layer drop7
I0405 12:47:18.281754 18799 net.cpp:406] drop7 <- fc7
I0405 12:47:18.281774 18799 net.cpp:367] drop7 -> fc7 (in-place)
I0405 12:47:18.281796 18799 net.cpp:122] Setting up drop7
I0405 12:47:18.281800 18799 net.cpp:129] Top shape: 128 4096 (524288)
I0405 12:47:18.281802 18799 net.cpp:137] Memory required for data: 1064351744
I0405 12:47:18.281805 18799 layer_factory.hpp:77] Creating layer fc8
I0405 12:47:18.281811 18799 net.cpp:84] Creating Layer fc8
I0405 12:47:18.281813 18799 net.cpp:406] fc8 <- fc7
I0405 12:47:18.281817 18799 net.cpp:380] fc8 -> fc8
I0405 12:47:18.288913 18799 net.cpp:122] Setting up fc8
I0405 12:47:18.288928 18799 net.cpp:129] Top shape: 128 196 (25088)
I0405 12:47:18.288930 18799 net.cpp:137] Memory required for data: 1064452096
I0405 12:47:18.288936 18799 layer_factory.hpp:77] Creating layer loss
I0405 12:47:18.288942 18799 net.cpp:84] Creating Layer loss
I0405 12:47:18.288945 18799 net.cpp:406] loss <- fc8
I0405 12:47:18.288949 18799 net.cpp:406] loss <- label
I0405 12:47:18.288955 18799 net.cpp:380] loss -> loss
I0405 12:47:18.288964 18799 layer_factory.hpp:77] Creating layer loss
I0405 12:47:18.292783 18799 net.cpp:122] Setting up loss
I0405 12:47:18.292790 18799 net.cpp:129] Top shape: (1)
I0405 12:47:18.292793 18799 net.cpp:132]     with loss weight 1
I0405 12:47:18.292809 18799 net.cpp:137] Memory required for data: 1064452100
I0405 12:47:18.292811 18799 net.cpp:198] loss needs backward computation.
I0405 12:47:18.292817 18799 net.cpp:198] fc8 needs backward computation.
I0405 12:47:18.292819 18799 net.cpp:198] drop7 needs backward computation.
I0405 12:47:18.292821 18799 net.cpp:198] relu7 needs backward computation.
I0405 12:47:18.292824 18799 net.cpp:198] fc7 needs backward computation.
I0405 12:47:18.292825 18799 net.cpp:198] drop6 needs backward computation.
I0405 12:47:18.292829 18799 net.cpp:198] relu6 needs backward computation.
I0405 12:47:18.292830 18799 net.cpp:198] fc6 needs backward computation.
I0405 12:47:18.292834 18799 net.cpp:198] pool5 needs backward computation.
I0405 12:47:18.292835 18799 net.cpp:198] relu5 needs backward computation.
I0405 12:47:18.292838 18799 net.cpp:198] conv5 needs backward computation.
I0405 12:47:18.292840 18799 net.cpp:198] relu4 needs backward computation.
I0405 12:47:18.292842 18799 net.cpp:198] conv4 needs backward computation.
I0405 12:47:18.292845 18799 net.cpp:198] relu3 needs backward computation.
I0405 12:47:18.292847 18799 net.cpp:198] conv3 needs backward computation.
I0405 12:47:18.292850 18799 net.cpp:198] pool2 needs backward computation.
I0405 12:47:18.292852 18799 net.cpp:198] norm2 needs backward computation.
I0405 12:47:18.292855 18799 net.cpp:198] relu2 needs backward computation.
I0405 12:47:18.292856 18799 net.cpp:198] conv2 needs backward computation.
I0405 12:47:18.292858 18799 net.cpp:198] pool1 needs backward computation.
I0405 12:47:18.292861 18799 net.cpp:198] norm1 needs backward computation.
I0405 12:47:18.292863 18799 net.cpp:198] relu1 needs backward computation.
I0405 12:47:18.292867 18799 net.cpp:198] conv1 needs backward computation.
I0405 12:47:18.292870 18799 net.cpp:200] train-data does not need backward computation.
I0405 12:47:18.292872 18799 net.cpp:242] This network produces output loss
I0405 12:47:18.292888 18799 net.cpp:255] Network initialization done.
I0405 12:47:18.293437 18799 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt
I0405 12:47:18.293467 18799 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data
I0405 12:47:18.293601 18799 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
}
layer {
name: "val-data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
crop_size: 227
mean_file: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto"
}
data_param {
source: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/val_db"
batch_size: 32
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "norm1"
type: "LRN"
bottom: "conv1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "norm1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "norm2"
type: "LRN"
bottom: "conv2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "norm2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "fc7"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 196
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fc8"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8"
bottom: "label"
top: "loss"
}
I0405 12:47:18.293694 18799 layer_factory.hpp:77] Creating layer val-data
I0405 12:47:18.375998 18799 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/val_db
I0405 12:47:18.376224 18799 net.cpp:84] Creating Layer val-data
I0405 12:47:18.376240 18799 net.cpp:380] val-data -> data
I0405 12:47:18.376251 18799 net.cpp:380] val-data -> label
I0405 12:47:18.376258 18799 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0405 12:47:18.381676 18799 data_layer.cpp:45] output data size: 32,3,227,227
I0405 12:47:18.423166 18799 net.cpp:122] Setting up val-data
I0405 12:47:18.423187 18799 net.cpp:129] Top shape: 32 3 227 227 (4946784)
I0405 12:47:18.423192 18799 net.cpp:129] Top shape: 32 (32)
I0405 12:47:18.423193 18799 net.cpp:137] Memory required for data: 19787264
I0405 12:47:18.423199 18799 layer_factory.hpp:77] Creating layer label_val-data_1_split
I0405 12:47:18.423211 18799 net.cpp:84] Creating Layer label_val-data_1_split
I0405 12:47:18.423215 18799 net.cpp:406] label_val-data_1_split <- label
I0405 12:47:18.423221 18799 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0
I0405 12:47:18.423230 18799 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1
I0405 12:47:18.423359 18799 net.cpp:122] Setting up label_val-data_1_split
I0405 12:47:18.423367 18799 net.cpp:129] Top shape: 32 (32)
I0405 12:47:18.423370 18799 net.cpp:129] Top shape: 32 (32)
I0405 12:47:18.423372 18799 net.cpp:137] Memory required for data: 19787520
I0405 12:47:18.423375 18799 layer_factory.hpp:77] Creating layer conv1
I0405 12:47:18.423388 18799 net.cpp:84] Creating Layer conv1
I0405 12:47:18.423391 18799 net.cpp:406] conv1 <- data
I0405 12:47:18.423398 18799 net.cpp:380] conv1 -> conv1
I0405 12:47:18.426327 18799 net.cpp:122] Setting up conv1
I0405 12:47:18.426340 18799 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 12:47:18.426343 18799 net.cpp:137] Memory required for data: 56958720
I0405 12:47:18.426353 18799 layer_factory.hpp:77] Creating layer relu1
I0405 12:47:18.426360 18799 net.cpp:84] Creating Layer relu1
I0405 12:47:18.426363 18799 net.cpp:406] relu1 <- conv1
I0405 12:47:18.426367 18799 net.cpp:367] relu1 -> conv1 (in-place)
I0405 12:47:18.426676 18799 net.cpp:122] Setting up relu1
I0405 12:47:18.426685 18799 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 12:47:18.426687 18799 net.cpp:137] Memory required for data: 94129920
I0405 12:47:18.426690 18799 layer_factory.hpp:77] Creating layer norm1
I0405 12:47:18.426698 18799 net.cpp:84] Creating Layer norm1
I0405 12:47:18.426702 18799 net.cpp:406] norm1 <- conv1
I0405 12:47:18.426707 18799 net.cpp:380] norm1 -> norm1
I0405 12:47:18.427224 18799 net.cpp:122] Setting up norm1
I0405 12:47:18.427234 18799 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 12:47:18.427237 18799 net.cpp:137] Memory required for data: 131301120
I0405 12:47:18.427240 18799 layer_factory.hpp:77] Creating layer pool1
I0405 12:47:18.427246 18799 net.cpp:84] Creating Layer pool1
I0405 12:47:18.427249 18799 net.cpp:406] pool1 <- norm1
I0405 12:47:18.427253 18799 net.cpp:380] pool1 -> pool1
I0405 12:47:18.427291 18799 net.cpp:122] Setting up pool1
I0405 12:47:18.427296 18799 net.cpp:129] Top shape: 32 96 27 27 (2239488)
I0405 12:47:18.427299 18799 net.cpp:137] Memory required for data: 140259072
I0405 12:47:18.427301 18799 layer_factory.hpp:77] Creating layer conv2
I0405 12:47:18.427309 18799 net.cpp:84] Creating Layer conv2
I0405 12:47:18.427312 18799 net.cpp:406] conv2 <- pool1
I0405 12:47:18.427340 18799 net.cpp:380] conv2 -> conv2
I0405 12:47:18.436203 18799 net.cpp:122] Setting up conv2
I0405 12:47:18.436223 18799 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 12:47:18.436226 18799 net.cpp:137] Memory required for data: 164146944
I0405 12:47:18.436237 18799 layer_factory.hpp:77] Creating layer relu2
I0405 12:47:18.436245 18799 net.cpp:84] Creating Layer relu2
I0405 12:47:18.436249 18799 net.cpp:406] relu2 <- conv2
I0405 12:47:18.436254 18799 net.cpp:367] relu2 -> conv2 (in-place)
I0405 12:47:18.436842 18799 net.cpp:122] Setting up relu2
I0405 12:47:18.436853 18799 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 12:47:18.436856 18799 net.cpp:137] Memory required for data: 188034816
I0405 12:47:18.436859 18799 layer_factory.hpp:77] Creating layer norm2
I0405 12:47:18.436870 18799 net.cpp:84] Creating Layer norm2
I0405 12:47:18.436873 18799 net.cpp:406] norm2 <- conv2
I0405 12:47:18.436878 18799 net.cpp:380] norm2 -> norm2
I0405 12:47:18.437492 18799 net.cpp:122] Setting up norm2
I0405 12:47:18.437502 18799 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 12:47:18.437505 18799 net.cpp:137] Memory required for data: 211922688
I0405 12:47:18.437507 18799 layer_factory.hpp:77] Creating layer pool2
I0405 12:47:18.437515 18799 net.cpp:84] Creating Layer pool2
I0405 12:47:18.437516 18799 net.cpp:406] pool2 <- norm2
I0405 12:47:18.437522 18799 net.cpp:380] pool2 -> pool2
I0405 12:47:18.437552 18799 net.cpp:122] Setting up pool2
I0405 12:47:18.437557 18799 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 12:47:18.437559 18799 net.cpp:137] Memory required for data: 217460480
I0405 12:47:18.437562 18799 layer_factory.hpp:77] Creating layer conv3
I0405 12:47:18.437573 18799 net.cpp:84] Creating Layer conv3
I0405 12:47:18.437577 18799 net.cpp:406] conv3 <- pool2
I0405 12:47:18.437580 18799 net.cpp:380] conv3 -> conv3
I0405 12:47:18.449404 18799 net.cpp:122] Setting up conv3
I0405 12:47:18.449427 18799 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 12:47:18.449430 18799 net.cpp:137] Memory required for data: 225767168
I0405 12:47:18.449442 18799 layer_factory.hpp:77] Creating layer relu3
I0405 12:47:18.449450 18799 net.cpp:84] Creating Layer relu3
I0405 12:47:18.449455 18799 net.cpp:406] relu3 <- conv3
I0405 12:47:18.449461 18799 net.cpp:367] relu3 -> conv3 (in-place)
I0405 12:47:18.450016 18799 net.cpp:122] Setting up relu3
I0405 12:47:18.450026 18799 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 12:47:18.450029 18799 net.cpp:137] Memory required for data: 234073856
I0405 12:47:18.450032 18799 layer_factory.hpp:77] Creating layer conv4
I0405 12:47:18.450042 18799 net.cpp:84] Creating Layer conv4
I0405 12:47:18.450045 18799 net.cpp:406] conv4 <- conv3
I0405 12:47:18.450050 18799 net.cpp:380] conv4 -> conv4
I0405 12:47:18.460336 18799 net.cpp:122] Setting up conv4
I0405 12:47:18.460353 18799 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 12:47:18.460356 18799 net.cpp:137] Memory required for data: 242380544
I0405 12:47:18.460363 18799 layer_factory.hpp:77] Creating layer relu4
I0405 12:47:18.460371 18799 net.cpp:84] Creating Layer relu4
I0405 12:47:18.460374 18799 net.cpp:406] relu4 <- conv4
I0405 12:47:18.460381 18799 net.cpp:367] relu4 -> conv4 (in-place)
I0405 12:47:18.460736 18799 net.cpp:122] Setting up relu4
I0405 12:47:18.460745 18799 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 12:47:18.460748 18799 net.cpp:137] Memory required for data: 250687232
I0405 12:47:18.460752 18799 layer_factory.hpp:77] Creating layer conv5
I0405 12:47:18.460762 18799 net.cpp:84] Creating Layer conv5
I0405 12:47:18.460764 18799 net.cpp:406] conv5 <- conv4
I0405 12:47:18.460769 18799 net.cpp:380] conv5 -> conv5
I0405 12:47:18.469486 18799 net.cpp:122] Setting up conv5
I0405 12:47:18.469504 18799 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 12:47:18.469507 18799 net.cpp:137] Memory required for data: 256225024
I0405 12:47:18.469521 18799 layer_factory.hpp:77] Creating layer relu5
I0405 12:47:18.469527 18799 net.cpp:84] Creating Layer relu5
I0405 12:47:18.469530 18799 net.cpp:406] relu5 <- conv5
I0405 12:47:18.469556 18799 net.cpp:367] relu5 -> conv5 (in-place)
I0405 12:47:18.470098 18799 net.cpp:122] Setting up relu5
I0405 12:47:18.470108 18799 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 12:47:18.470109 18799 net.cpp:137] Memory required for data: 261762816
I0405 12:47:18.470113 18799 layer_factory.hpp:77] Creating layer pool5
I0405 12:47:18.470121 18799 net.cpp:84] Creating Layer pool5
I0405 12:47:18.470124 18799 net.cpp:406] pool5 <- conv5
I0405 12:47:18.470129 18799 net.cpp:380] pool5 -> pool5
I0405 12:47:18.470165 18799 net.cpp:122] Setting up pool5
I0405 12:47:18.470170 18799 net.cpp:129] Top shape: 32 256 6 6 (294912)
I0405 12:47:18.470172 18799 net.cpp:137] Memory required for data: 262942464
I0405 12:47:18.470175 18799 layer_factory.hpp:77] Creating layer fc6
I0405 12:47:18.470181 18799 net.cpp:84] Creating Layer fc6
I0405 12:47:18.470185 18799 net.cpp:406] fc6 <- pool5
I0405 12:47:18.470188 18799 net.cpp:380] fc6 -> fc6
I0405 12:47:18.848244 18799 net.cpp:122] Setting up fc6
I0405 12:47:18.848268 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.848269 18799 net.cpp:137] Memory required for data: 263466752
I0405 12:47:18.848278 18799 layer_factory.hpp:77] Creating layer relu6
I0405 12:47:18.848287 18799 net.cpp:84] Creating Layer relu6
I0405 12:47:18.848290 18799 net.cpp:406] relu6 <- fc6
I0405 12:47:18.848295 18799 net.cpp:367] relu6 -> fc6 (in-place)
I0405 12:47:18.848971 18799 net.cpp:122] Setting up relu6
I0405 12:47:18.848979 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.848982 18799 net.cpp:137] Memory required for data: 263991040
I0405 12:47:18.848985 18799 layer_factory.hpp:77] Creating layer drop6
I0405 12:47:18.848991 18799 net.cpp:84] Creating Layer drop6
I0405 12:47:18.848994 18799 net.cpp:406] drop6 <- fc6
I0405 12:47:18.848999 18799 net.cpp:367] drop6 -> fc6 (in-place)
I0405 12:47:18.849020 18799 net.cpp:122] Setting up drop6
I0405 12:47:18.849025 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.849026 18799 net.cpp:137] Memory required for data: 264515328
I0405 12:47:18.849028 18799 layer_factory.hpp:77] Creating layer fc7
I0405 12:47:18.849035 18799 net.cpp:84] Creating Layer fc7
I0405 12:47:18.849036 18799 net.cpp:406] fc7 <- fc6
I0405 12:47:18.849041 18799 net.cpp:380] fc7 -> fc7
I0405 12:47:18.994992 18799 net.cpp:122] Setting up fc7
I0405 12:47:18.995012 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.995015 18799 net.cpp:137] Memory required for data: 265039616
I0405 12:47:18.995023 18799 layer_factory.hpp:77] Creating layer relu7
I0405 12:47:18.995031 18799 net.cpp:84] Creating Layer relu7
I0405 12:47:18.995034 18799 net.cpp:406] relu7 <- fc7
I0405 12:47:18.995040 18799 net.cpp:367] relu7 -> fc7 (in-place)
I0405 12:47:18.995427 18799 net.cpp:122] Setting up relu7
I0405 12:47:18.995435 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.995437 18799 net.cpp:137] Memory required for data: 265563904
I0405 12:47:18.995440 18799 layer_factory.hpp:77] Creating layer drop7
I0405 12:47:18.995446 18799 net.cpp:84] Creating Layer drop7
I0405 12:47:18.995448 18799 net.cpp:406] drop7 <- fc7
I0405 12:47:18.995452 18799 net.cpp:367] drop7 -> fc7 (in-place)
I0405 12:47:18.995473 18799 net.cpp:122] Setting up drop7
I0405 12:47:18.995477 18799 net.cpp:129] Top shape: 32 4096 (131072)
I0405 12:47:18.995479 18799 net.cpp:137] Memory required for data: 266088192
I0405 12:47:18.995481 18799 layer_factory.hpp:77] Creating layer fc8
I0405 12:47:18.995488 18799 net.cpp:84] Creating Layer fc8
I0405 12:47:18.995491 18799 net.cpp:406] fc8 <- fc7
I0405 12:47:18.995494 18799 net.cpp:380] fc8 -> fc8
I0405 12:47:19.002842 18799 net.cpp:122] Setting up fc8
I0405 12:47:19.002864 18799 net.cpp:129] Top shape: 32 196 (6272)
I0405 12:47:19.002867 18799 net.cpp:137] Memory required for data: 266113280
I0405 12:47:19.002874 18799 layer_factory.hpp:77] Creating layer fc8_fc8_0_split
I0405 12:47:19.002882 18799 net.cpp:84] Creating Layer fc8_fc8_0_split
I0405 12:47:19.002885 18799 net.cpp:406] fc8_fc8_0_split <- fc8
I0405 12:47:19.002915 18799 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0
I0405 12:47:19.002923 18799 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1
I0405 12:47:19.002959 18799 net.cpp:122] Setting up fc8_fc8_0_split
I0405 12:47:19.002962 18799 net.cpp:129] Top shape: 32 196 (6272)
I0405 12:47:19.002965 18799 net.cpp:129] Top shape: 32 196 (6272)
I0405 12:47:19.002967 18799 net.cpp:137] Memory required for data: 266163456
I0405 12:47:19.002969 18799 layer_factory.hpp:77] Creating layer accuracy
I0405 12:47:19.002976 18799 net.cpp:84] Creating Layer accuracy
I0405 12:47:19.002979 18799 net.cpp:406] accuracy <- fc8_fc8_0_split_0
I0405 12:47:19.002982 18799 net.cpp:406] accuracy <- label_val-data_1_split_0
I0405 12:47:19.002985 18799 net.cpp:380] accuracy -> accuracy
I0405 12:47:19.002991 18799 net.cpp:122] Setting up accuracy
I0405 12:47:19.002995 18799 net.cpp:129] Top shape: (1)
I0405 12:47:19.002996 18799 net.cpp:137] Memory required for data: 266163460
I0405 12:47:19.002997 18799 layer_factory.hpp:77] Creating layer loss
I0405 12:47:19.003002 18799 net.cpp:84] Creating Layer loss
I0405 12:47:19.003005 18799 net.cpp:406] loss <- fc8_fc8_0_split_1
I0405 12:47:19.003006 18799 net.cpp:406] loss <- label_val-data_1_split_1
I0405 12:47:19.003010 18799 net.cpp:380] loss -> loss
I0405 12:47:19.003015 18799 layer_factory.hpp:77] Creating layer loss
I0405 12:47:19.003710 18799 net.cpp:122] Setting up loss
I0405 12:47:19.003717 18799 net.cpp:129] Top shape: (1)
I0405 12:47:19.003720 18799 net.cpp:132]     with loss weight 1
I0405 12:47:19.003728 18799 net.cpp:137] Memory required for data: 266163464
I0405 12:47:19.003731 18799 net.cpp:198] loss needs backward computation.
I0405 12:47:19.003734 18799 net.cpp:200] accuracy does not need backward computation.
I0405 12:47:19.003737 18799 net.cpp:198] fc8_fc8_0_split needs backward computation.
I0405 12:47:19.003739 18799 net.cpp:198] fc8 needs backward computation.
I0405 12:47:19.003741 18799 net.cpp:198] drop7 needs backward computation.
I0405 12:47:19.003743 18799 net.cpp:198] relu7 needs backward computation.
I0405 12:47:19.003746 18799 net.cpp:198] fc7 needs backward computation.
I0405 12:47:19.003747 18799 net.cpp:198] drop6 needs backward computation.
I0405 12:47:19.003751 18799 net.cpp:198] relu6 needs backward computation.
I0405 12:47:19.003752 18799 net.cpp:198] fc6 needs backward computation.
I0405 12:47:19.003754 18799 net.cpp:198] pool5 needs backward computation.
I0405 12:47:19.003757 18799 net.cpp:198] relu5 needs backward computation.
I0405 12:47:19.003759 18799 net.cpp:198] conv5 needs backward computation.
I0405 12:47:19.003762 18799 net.cpp:198] relu4 needs backward computation.
I0405 12:47:19.003765 18799 net.cpp:198] conv4 needs backward computation.
I0405 12:47:19.003767 18799 net.cpp:198] relu3 needs backward computation.
I0405 12:47:19.003769 18799 net.cpp:198] conv3 needs backward computation.
I0405 12:47:19.003772 18799 net.cpp:198] pool2 needs backward computation.
I0405 12:47:19.003774 18799 net.cpp:198] norm2 needs backward computation.
I0405 12:47:19.003777 18799 net.cpp:198] relu2 needs backward computation.
I0405 12:47:19.003778 18799 net.cpp:198] conv2 needs backward computation.
I0405 12:47:19.003780 18799 net.cpp:198] pool1 needs backward computation.
I0405 12:47:19.003783 18799 net.cpp:198] norm1 needs backward computation.
I0405 12:47:19.003785 18799 net.cpp:198] relu1 needs backward computation.
I0405 12:47:19.003787 18799 net.cpp:198] conv1 needs backward computation.
I0405 12:47:19.003789 18799 net.cpp:200] label_val-data_1_split does not need backward computation.
I0405 12:47:19.003793 18799 net.cpp:200] val-data does not need backward computation.
I0405 12:47:19.003794 18799 net.cpp:242] This network produces output accuracy
I0405 12:47:19.003798 18799 net.cpp:242] This network produces output loss
I0405 12:47:19.003811 18799 net.cpp:255] Network initialization done.
I0405 12:47:19.003890 18799 solver.cpp:56] Solver scaffolding done.
I0405 12:47:19.004287 18799 caffe.cpp:248] Starting Optimization
I0405 12:47:19.004294 18799 solver.cpp:272] Solving
I0405 12:47:19.004307 18799 solver.cpp:273] Learning Rate Policy: fixed
I0405 12:47:19.006047 18799 solver.cpp:330] Iteration 0, Testing net (#0)
I0405 12:47:19.006055 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:47:19.115793 18799 blocking_queue.cpp:49] Waiting for data
I0405 12:47:23.370206 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:47:23.418478 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 12:47:23.418515 18799 solver.cpp:397]     Test net output #1: loss = 5.27913 (* 1 = 5.27913 loss)
I0405 12:47:23.562127 18799 solver.cpp:218] Iteration 0 (1.75013e+36 iter/s, 4.55774s/12 iters), loss = 5.28183
I0405 12:47:23.563690 18799 solver.cpp:237]     Train net output #0: loss = 5.28183 (* 1 = 5.28183 loss)
I0405 12:47:23.563705 18799 sgd_solver.cpp:105] Iteration 0, lr = 0.0001
I0405 12:47:27.848948 18799 solver.cpp:218] Iteration 12 (2.80032 iter/s, 4.28522s/12 iters), loss = 5.2946
I0405 12:47:27.848991 18799 solver.cpp:237]     Train net output #0: loss = 5.2946 (* 1 = 5.2946 loss)
I0405 12:47:27.848997 18799 sgd_solver.cpp:105] Iteration 12, lr = 0.0001
I0405 12:47:33.247238 18799 solver.cpp:218] Iteration 24 (2.22297 iter/s, 5.39819s/12 iters), loss = 5.27203
I0405 12:47:33.247292 18799 solver.cpp:237]     Train net output #0: loss = 5.27203 (* 1 = 5.27203 loss)
I0405 12:47:33.247299 18799 sgd_solver.cpp:105] Iteration 24, lr = 0.0001
I0405 12:47:38.656977 18799 solver.cpp:218] Iteration 36 (2.21826 iter/s, 5.40964s/12 iters), loss = 5.27007
I0405 12:47:38.657017 18799 solver.cpp:237]     Train net output #0: loss = 5.27007 (* 1 = 5.27007 loss)
I0405 12:47:38.657022 18799 sgd_solver.cpp:105] Iteration 36, lr = 0.0001
I0405 12:47:44.044644 18799 solver.cpp:218] Iteration 48 (2.22735 iter/s, 5.38757s/12 iters), loss = 5.2849
I0405 12:47:44.044701 18799 solver.cpp:237]     Train net output #0: loss = 5.2849 (* 1 = 5.2849 loss)
I0405 12:47:44.044709 18799 sgd_solver.cpp:105] Iteration 48, lr = 0.0001
I0405 12:47:49.306013 18799 solver.cpp:218] Iteration 60 (2.28082 iter/s, 5.26127s/12 iters), loss = 5.28793
I0405 12:47:49.306097 18799 solver.cpp:237]     Train net output #0: loss = 5.28793 (* 1 = 5.28793 loss)
I0405 12:47:49.306102 18799 sgd_solver.cpp:105] Iteration 60, lr = 0.0001
I0405 12:47:54.496613 18799 solver.cpp:218] Iteration 72 (2.31193 iter/s, 5.19047s/12 iters), loss = 5.30173
I0405 12:47:54.496666 18799 solver.cpp:237]     Train net output #0: loss = 5.30173 (* 1 = 5.30173 loss)
I0405 12:47:54.496675 18799 sgd_solver.cpp:105] Iteration 72, lr = 0.0001
I0405 12:47:59.781945 18799 solver.cpp:218] Iteration 84 (2.27048 iter/s, 5.28523s/12 iters), loss = 5.27376
I0405 12:47:59.782004 18799 solver.cpp:237]     Train net output #0: loss = 5.27376 (* 1 = 5.27376 loss)
I0405 12:47:59.782013 18799 sgd_solver.cpp:105] Iteration 84, lr = 0.0001
I0405 12:48:05.168462 18799 solver.cpp:218] Iteration 96 (2.22783 iter/s, 5.38641s/12 iters), loss = 5.28904
I0405 12:48:05.168514 18799 solver.cpp:237]     Train net output #0: loss = 5.28904 (* 1 = 5.28904 loss)
I0405 12:48:05.168521 18799 sgd_solver.cpp:105] Iteration 96, lr = 0.0001
I0405 12:48:07.012156 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:48:07.327509 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel
I0405 12:48:10.454233 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate
I0405 12:48:12.781220 18799 solver.cpp:330] Iteration 102, Testing net (#0)
I0405 12:48:12.781240 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:48:17.227718 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:48:17.309387 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 12:48:17.309430 18799 solver.cpp:397]     Test net output #1: loss = 5.27848 (* 1 = 5.27848 loss)
I0405 12:48:19.289862 18799 solver.cpp:218] Iteration 108 (0.849783 iter/s, 14.1213s/12 iters), loss = 5.27384
I0405 12:48:19.289916 18799 solver.cpp:237]     Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss)
I0405 12:48:19.289924 18799 sgd_solver.cpp:105] Iteration 108, lr = 0.0001
I0405 12:48:24.810643 18799 solver.cpp:218] Iteration 120 (2.17365 iter/s, 5.52067s/12 iters), loss = 5.2647
I0405 12:48:24.810811 18799 solver.cpp:237]     Train net output #0: loss = 5.2647 (* 1 = 5.2647 loss)
I0405 12:48:24.810820 18799 sgd_solver.cpp:105] Iteration 120, lr = 0.0001
I0405 12:48:30.316298 18799 solver.cpp:218] Iteration 132 (2.17966 iter/s, 5.50544s/12 iters), loss = 5.27421
I0405 12:48:30.316365 18799 solver.cpp:237]     Train net output #0: loss = 5.27421 (* 1 = 5.27421 loss)
I0405 12:48:30.316373 18799 sgd_solver.cpp:105] Iteration 132, lr = 0.0001
I0405 12:48:35.583912 18799 solver.cpp:218] Iteration 144 (2.27812 iter/s, 5.2675s/12 iters), loss = 5.29073
I0405 12:48:35.583962 18799 solver.cpp:237]     Train net output #0: loss = 5.29073 (* 1 = 5.29073 loss)
I0405 12:48:35.583971 18799 sgd_solver.cpp:105] Iteration 144, lr = 0.0001
I0405 12:48:41.329524 18799 solver.cpp:218] Iteration 156 (2.08859 iter/s, 5.74551s/12 iters), loss = 5.26935
I0405 12:48:41.329576 18799 solver.cpp:237]     Train net output #0: loss = 5.26935 (* 1 = 5.26935 loss)
I0405 12:48:41.329583 18799 sgd_solver.cpp:105] Iteration 156, lr = 0.0001
I0405 12:48:46.771993 18799 solver.cpp:218] Iteration 168 (2.20492 iter/s, 5.44236s/12 iters), loss = 5.28392
I0405 12:48:46.772049 18799 solver.cpp:237]     Train net output #0: loss = 5.28392 (* 1 = 5.28392 loss)
I0405 12:48:46.772058 18799 sgd_solver.cpp:105] Iteration 168, lr = 0.0001
I0405 12:48:52.299800 18799 solver.cpp:218] Iteration 180 (2.17088 iter/s, 5.5277s/12 iters), loss = 5.30372
I0405 12:48:52.299855 18799 solver.cpp:237]     Train net output #0: loss = 5.30372 (* 1 = 5.30372 loss)
I0405 12:48:52.299863 18799 sgd_solver.cpp:105] Iteration 180, lr = 0.0001
I0405 12:48:57.679543 18799 solver.cpp:218] Iteration 192 (2.23063 iter/s, 5.37964s/12 iters), loss = 5.28002
I0405 12:48:57.679673 18799 solver.cpp:237]     Train net output #0: loss = 5.28002 (* 1 = 5.28002 loss)
I0405 12:48:57.679683 18799 sgd_solver.cpp:105] Iteration 192, lr = 0.0001
I0405 12:49:01.987040 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:49:02.703454 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel
I0405 12:49:05.826470 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate
I0405 12:49:08.137745 18799 solver.cpp:330] Iteration 204, Testing net (#0)
I0405 12:49:08.137768 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:49:12.900832 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:49:13.041018 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 12:49:13.041050 18799 solver.cpp:397]     Test net output #1: loss = 5.27862 (* 1 = 5.27862 loss)
I0405 12:49:13.183008 18799 solver.cpp:218] Iteration 204 (0.774032 iter/s, 15.5032s/12 iters), loss = 5.2786
I0405 12:49:13.183053 18799 solver.cpp:237]     Train net output #0: loss = 5.2786 (* 1 = 5.2786 loss)
I0405 12:49:13.183059 18799 sgd_solver.cpp:105] Iteration 204, lr = 0.0001
I0405 12:49:17.827324 18799 solver.cpp:218] Iteration 216 (2.58385 iter/s, 4.64423s/12 iters), loss = 5.28758
I0405 12:49:17.827374 18799 solver.cpp:237]     Train net output #0: loss = 5.28758 (* 1 = 5.28758 loss)
I0405 12:49:17.827383 18799 sgd_solver.cpp:105] Iteration 216, lr = 0.0001
I0405 12:49:23.202613 18799 solver.cpp:218] Iteration 228 (2.23248 iter/s, 5.3752s/12 iters), loss = 5.294
I0405 12:49:23.202651 18799 solver.cpp:237]     Train net output #0: loss = 5.294 (* 1 = 5.294 loss)
I0405 12:49:23.202657 18799 sgd_solver.cpp:105] Iteration 228, lr = 0.0001
I0405 12:49:28.793670 18799 solver.cpp:218] Iteration 240 (2.14632 iter/s, 5.59097s/12 iters), loss = 5.2667
I0405 12:49:28.793784 18799 solver.cpp:237]     Train net output #0: loss = 5.2667 (* 1 = 5.2667 loss)
I0405 12:49:28.793790 18799 sgd_solver.cpp:105] Iteration 240, lr = 0.0001
I0405 12:49:34.428592 18799 solver.cpp:218] Iteration 252 (2.12964 iter/s, 5.63476s/12 iters), loss = 5.28776
I0405 12:49:34.428632 18799 solver.cpp:237]     Train net output #0: loss = 5.28776 (* 1 = 5.28776 loss)
I0405 12:49:34.428637 18799 sgd_solver.cpp:105] Iteration 252, lr = 0.0001
I0405 12:49:39.888615 18799 solver.cpp:218] Iteration 264 (2.19783 iter/s, 5.45993s/12 iters), loss = 5.29353
I0405 12:49:39.888670 18799 solver.cpp:237]     Train net output #0: loss = 5.29353 (* 1 = 5.29353 loss)
I0405 12:49:39.888679 18799 sgd_solver.cpp:105] Iteration 264, lr = 0.0001
I0405 12:49:45.202764 18799 solver.cpp:218] Iteration 276 (2.25817 iter/s, 5.31405s/12 iters), loss = 5.298
I0405 12:49:45.202803 18799 solver.cpp:237]     Train net output #0: loss = 5.298 (* 1 = 5.298 loss)
I0405 12:49:45.202809 18799 sgd_solver.cpp:105] Iteration 276, lr = 0.0001
I0405 12:49:50.637555 18799 solver.cpp:218] Iteration 288 (2.20803 iter/s, 5.43471s/12 iters), loss = 5.27911
I0405 12:49:50.637606 18799 solver.cpp:237]     Train net output #0: loss = 5.27911 (* 1 = 5.27911 loss)
I0405 12:49:50.637614 18799 sgd_solver.cpp:105] Iteration 288, lr = 0.0001
I0405 12:49:56.217298 18799 solver.cpp:218] Iteration 300 (2.15068 iter/s, 5.57964s/12 iters), loss = 5.28328
I0405 12:49:56.217350 18799 solver.cpp:237]     Train net output #0: loss = 5.28328 (* 1 = 5.28328 loss)
I0405 12:49:56.217357 18799 sgd_solver.cpp:105] Iteration 300, lr = 0.0001
I0405 12:49:57.177549 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:49:58.275807 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel
I0405 12:50:01.261557 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate
I0405 12:50:04.343999 18799 solver.cpp:330] Iteration 306, Testing net (#0)
I0405 12:50:04.344024 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:50:08.881938 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:50:09.038769 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 12:50:09.038803 18799 solver.cpp:397]     Test net output #1: loss = 5.27853 (* 1 = 5.27853 loss)
I0405 12:50:10.959084 18799 solver.cpp:218] Iteration 312 (0.814021 iter/s, 14.7416s/12 iters), loss = 5.27776
I0405 12:50:10.959142 18799 solver.cpp:237]     Train net output #0: loss = 5.27776 (* 1 = 5.27776 loss)
I0405 12:50:10.959151 18799 sgd_solver.cpp:105] Iteration 312, lr = 0.0001
I0405 12:50:16.326716 18799 solver.cpp:218] Iteration 324 (2.23567 iter/s, 5.36753s/12 iters), loss = 5.29092
I0405 12:50:16.326757 18799 solver.cpp:237]     Train net output #0: loss = 5.29092 (* 1 = 5.29092 loss)
I0405 12:50:16.326762 18799 sgd_solver.cpp:105] Iteration 324, lr = 0.0001
I0405 12:50:21.802433 18799 solver.cpp:218] Iteration 336 (2.19153 iter/s, 5.47562s/12 iters), loss = 5.27322
I0405 12:50:21.802482 18799 solver.cpp:237]     Train net output #0: loss = 5.27322 (* 1 = 5.27322 loss)
I0405 12:50:21.802489 18799 sgd_solver.cpp:105] Iteration 336, lr = 0.0001
I0405 12:50:27.198784 18799 solver.cpp:218] Iteration 348 (2.22377 iter/s, 5.39625s/12 iters), loss = 5.29889
I0405 12:50:27.198832 18799 solver.cpp:237]     Train net output #0: loss = 5.29889 (* 1 = 5.29889 loss)
I0405 12:50:27.198837 18799 sgd_solver.cpp:105] Iteration 348, lr = 0.0001
I0405 12:50:32.849195 18799 solver.cpp:218] Iteration 360 (2.12378 iter/s, 5.65031s/12 iters), loss = 5.30697
I0405 12:50:32.849318 18799 solver.cpp:237]     Train net output #0: loss = 5.30697 (* 1 = 5.30697 loss)
I0405 12:50:32.849328 18799 sgd_solver.cpp:105] Iteration 360, lr = 0.0001
I0405 12:50:38.236224 18799 solver.cpp:218] Iteration 372 (2.22764 iter/s, 5.38686s/12 iters), loss = 5.26583
I0405 12:50:38.236279 18799 solver.cpp:237]     Train net output #0: loss = 5.26583 (* 1 = 5.26583 loss)
I0405 12:50:38.236289 18799 sgd_solver.cpp:105] Iteration 372, lr = 0.0001
I0405 12:50:43.686779 18799 solver.cpp:218] Iteration 384 (2.20165 iter/s, 5.45045s/12 iters), loss = 5.27626
I0405 12:50:43.686830 18799 solver.cpp:237]     Train net output #0: loss = 5.27626 (* 1 = 5.27626 loss)
I0405 12:50:43.686837 18799 sgd_solver.cpp:105] Iteration 384, lr = 0.0001
I0405 12:50:49.200158 18799 solver.cpp:218] Iteration 396 (2.17656 iter/s, 5.51328s/12 iters), loss = 5.30405
I0405 12:50:49.200217 18799 solver.cpp:237]     Train net output #0: loss = 5.30405 (* 1 = 5.30405 loss)
I0405 12:50:49.200225 18799 sgd_solver.cpp:105] Iteration 396, lr = 0.0001
I0405 12:50:52.585223 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:50:54.134511 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel
I0405 12:50:57.102501 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate
I0405 12:50:59.407727 18799 solver.cpp:330] Iteration 408, Testing net (#0)
I0405 12:50:59.407752 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:51:03.765816 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:51:03.993577 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00857843
I0405 12:51:03.993618 18799 solver.cpp:397]     Test net output #1: loss = 5.27846 (* 1 = 5.27846 loss)
I0405 12:51:04.135576 18799 solver.cpp:218] Iteration 408 (0.803468 iter/s, 14.9353s/12 iters), loss = 5.26292
I0405 12:51:04.135645 18799 solver.cpp:237]     Train net output #0: loss = 5.26292 (* 1 = 5.26292 loss)
I0405 12:51:04.135654 18799 sgd_solver.cpp:105] Iteration 408, lr = 0.0001
I0405 12:51:08.666934 18799 solver.cpp:218] Iteration 420 (2.64828 iter/s, 4.53124s/12 iters), loss = 5.28759
I0405 12:51:08.666976 18799 solver.cpp:237]     Train net output #0: loss = 5.28759 (* 1 = 5.28759 loss)
I0405 12:51:08.666982 18799 sgd_solver.cpp:105] Iteration 420, lr = 0.0001
I0405 12:51:14.194380 18799 solver.cpp:218] Iteration 432 (2.17102 iter/s, 5.52735s/12 iters), loss = 5.27029
I0405 12:51:14.194422 18799 solver.cpp:237]     Train net output #0: loss = 5.27029 (* 1 = 5.27029 loss)
I0405 12:51:14.194428 18799 sgd_solver.cpp:105] Iteration 432, lr = 0.0001
I0405 12:51:19.560340 18799 solver.cpp:218] Iteration 444 (2.23636 iter/s, 5.36587s/12 iters), loss = 5.28524
I0405 12:51:19.560395 18799 solver.cpp:237]     Train net output #0: loss = 5.28524 (* 1 = 5.28524 loss)
I0405 12:51:19.560403 18799 sgd_solver.cpp:105] Iteration 444, lr = 0.0001
I0405 12:51:25.066663 18799 solver.cpp:218] Iteration 456 (2.17935 iter/s, 5.50622s/12 iters), loss = 5.28837
I0405 12:51:25.066732 18799 solver.cpp:237]     Train net output #0: loss = 5.28837 (* 1 = 5.28837 loss)
I0405 12:51:25.066741 18799 sgd_solver.cpp:105] Iteration 456, lr = 0.0001
I0405 12:51:30.420750 18799 solver.cpp:218] Iteration 468 (2.24133 iter/s, 5.35397s/12 iters), loss = 5.28966
I0405 12:51:30.420806 18799 solver.cpp:237]     Train net output #0: loss = 5.28966 (* 1 = 5.28966 loss)
I0405 12:51:30.420815 18799 sgd_solver.cpp:105] Iteration 468, lr = 0.0001
I0405 12:51:35.891769 18799 solver.cpp:218] Iteration 480 (2.19342 iter/s, 5.47091s/12 iters), loss = 5.28244
I0405 12:51:35.891906 18799 solver.cpp:237]     Train net output #0: loss = 5.28244 (* 1 = 5.28244 loss)
I0405 12:51:35.891916 18799 sgd_solver.cpp:105] Iteration 480, lr = 0.0001
I0405 12:51:41.393043 18799 solver.cpp:218] Iteration 492 (2.18139 iter/s, 5.50109s/12 iters), loss = 5.2952
I0405 12:51:41.393090 18799 solver.cpp:237]     Train net output #0: loss = 5.2952 (* 1 = 5.2952 loss)
I0405 12:51:41.393096 18799 sgd_solver.cpp:105] Iteration 492, lr = 0.0001
I0405 12:51:47.002439 18799 solver.cpp:218] Iteration 504 (2.13931 iter/s, 5.6093s/12 iters), loss = 5.27904
I0405 12:51:47.002497 18799 solver.cpp:237]     Train net output #0: loss = 5.27904 (* 1 = 5.27904 loss)
I0405 12:51:47.002506 18799 sgd_solver.cpp:105] Iteration 504, lr = 0.0001
I0405 12:51:47.245774 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:51:49.182379 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel
I0405 12:51:52.204056 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate
I0405 12:51:54.539362 18799 solver.cpp:330] Iteration 510, Testing net (#0)
I0405 12:51:54.539382 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:51:59.011338 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:51:59.276778 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:51:59.276819 18799 solver.cpp:397]     Test net output #1: loss = 5.27885 (* 1 = 5.27885 loss)
I0405 12:52:01.221927 18799 solver.cpp:218] Iteration 516 (0.843921 iter/s, 14.2193s/12 iters), loss = 5.26871
I0405 12:52:01.221978 18799 solver.cpp:237]     Train net output #0: loss = 5.26871 (* 1 = 5.26871 loss)
I0405 12:52:01.221983 18799 sgd_solver.cpp:105] Iteration 516, lr = 0.0001
I0405 12:52:06.584113 18799 solver.cpp:218] Iteration 528 (2.23793 iter/s, 5.36209s/12 iters), loss = 5.28322
I0405 12:52:06.584270 18799 solver.cpp:237]     Train net output #0: loss = 5.28322 (* 1 = 5.28322 loss)
I0405 12:52:06.584280 18799 sgd_solver.cpp:105] Iteration 528, lr = 0.0001
I0405 12:52:12.047695 18799 solver.cpp:218] Iteration 540 (2.19644 iter/s, 5.46338s/12 iters), loss = 5.28091
I0405 12:52:12.047739 18799 solver.cpp:237]     Train net output #0: loss = 5.28091 (* 1 = 5.28091 loss)
I0405 12:52:12.047745 18799 sgd_solver.cpp:105] Iteration 540, lr = 0.0001
I0405 12:52:17.521914 18799 solver.cpp:218] Iteration 552 (2.19213 iter/s, 5.47412s/12 iters), loss = 5.28785
I0405 12:52:17.521970 18799 solver.cpp:237]     Train net output #0: loss = 5.28785 (* 1 = 5.28785 loss)
I0405 12:52:17.521977 18799 sgd_solver.cpp:105] Iteration 552, lr = 0.0001
I0405 12:52:23.002338 18799 solver.cpp:218] Iteration 564 (2.18965 iter/s, 5.48032s/12 iters), loss = 5.2805
I0405 12:52:23.002393 18799 solver.cpp:237]     Train net output #0: loss = 5.2805 (* 1 = 5.2805 loss)
I0405 12:52:23.002401 18799 sgd_solver.cpp:105] Iteration 564, lr = 0.0001
I0405 12:52:28.423096 18799 solver.cpp:218] Iteration 576 (2.21375 iter/s, 5.42066s/12 iters), loss = 5.28601
I0405 12:52:28.423141 18799 solver.cpp:237]     Train net output #0: loss = 5.28601 (* 1 = 5.28601 loss)
I0405 12:52:28.423147 18799 sgd_solver.cpp:105] Iteration 576, lr = 0.0001
I0405 12:52:33.725841 18799 solver.cpp:218] Iteration 588 (2.26302 iter/s, 5.30265s/12 iters), loss = 5.29215
I0405 12:52:33.725879 18799 solver.cpp:237]     Train net output #0: loss = 5.29215 (* 1 = 5.29215 loss)
I0405 12:52:33.725884 18799 sgd_solver.cpp:105] Iteration 588, lr = 0.0001
I0405 12:52:39.055557 18799 solver.cpp:218] Iteration 600 (2.25156 iter/s, 5.32963s/12 iters), loss = 5.27214
I0405 12:52:39.055717 18799 solver.cpp:237]     Train net output #0: loss = 5.27214 (* 1 = 5.27214 loss)
I0405 12:52:39.055724 18799 sgd_solver.cpp:105] Iteration 600, lr = 0.0001
I0405 12:52:41.440435 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:52:43.780201 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel
I0405 12:52:46.929322 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate
I0405 12:52:49.236346 18799 solver.cpp:330] Iteration 612, Testing net (#0)
I0405 12:52:49.236367 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:52:53.488981 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:52:53.772848 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:52:53.772898 18799 solver.cpp:397]     Test net output #1: loss = 5.27873 (* 1 = 5.27873 loss)
I0405 12:52:53.912056 18799 solver.cpp:218] Iteration 612 (0.807741 iter/s, 14.8562s/12 iters), loss = 5.28739
I0405 12:52:53.913664 18799 solver.cpp:237]     Train net output #0: loss = 5.28739 (* 1 = 5.28739 loss)
I0405 12:52:53.913678 18799 sgd_solver.cpp:105] Iteration 612, lr = 0.0001
I0405 12:52:58.381754 18799 solver.cpp:218] Iteration 624 (2.68573 iter/s, 4.46805s/12 iters), loss = 5.2675
I0405 12:52:58.381811 18799 solver.cpp:237]     Train net output #0: loss = 5.2675 (* 1 = 5.2675 loss)
I0405 12:52:58.381819 18799 sgd_solver.cpp:105] Iteration 624, lr = 0.0001
I0405 12:53:03.816128 18799 solver.cpp:218] Iteration 636 (2.20821 iter/s, 5.43427s/12 iters), loss = 5.28487
I0405 12:53:03.816187 18799 solver.cpp:237]     Train net output #0: loss = 5.28487 (* 1 = 5.28487 loss)
I0405 12:53:03.816195 18799 sgd_solver.cpp:105] Iteration 636, lr = 0.0001
I0405 12:53:09.150717 18799 solver.cpp:218] Iteration 648 (2.24952 iter/s, 5.33448s/12 iters), loss = 5.27025
I0405 12:53:09.150858 18799 solver.cpp:237]     Train net output #0: loss = 5.27025 (* 1 = 5.27025 loss)
I0405 12:53:09.150866 18799 sgd_solver.cpp:105] Iteration 648, lr = 0.0001
I0405 12:53:14.334486 18799 solver.cpp:218] Iteration 660 (2.315 iter/s, 5.18358s/12 iters), loss = 5.27803
I0405 12:53:14.334525 18799 solver.cpp:237]     Train net output #0: loss = 5.27803 (* 1 = 5.27803 loss)
I0405 12:53:14.334532 18799 sgd_solver.cpp:105] Iteration 660, lr = 0.0001
I0405 12:53:19.655437 18799 solver.cpp:218] Iteration 672 (2.25527 iter/s, 5.32087s/12 iters), loss = 5.27232
I0405 12:53:19.655490 18799 solver.cpp:237]     Train net output #0: loss = 5.27232 (* 1 = 5.27232 loss)
I0405 12:53:19.655498 18799 sgd_solver.cpp:105] Iteration 672, lr = 0.0001
I0405 12:53:24.939779 18799 solver.cpp:218] Iteration 684 (2.27091 iter/s, 5.28424s/12 iters), loss = 5.28868
I0405 12:53:24.939829 18799 solver.cpp:237]     Train net output #0: loss = 5.28868 (* 1 = 5.28868 loss)
I0405 12:53:24.939841 18799 sgd_solver.cpp:105] Iteration 684, lr = 0.0001
I0405 12:53:25.747859 18799 blocking_queue.cpp:49] Waiting for data
I0405 12:53:30.279793 18799 solver.cpp:218] Iteration 696 (2.24722 iter/s, 5.33992s/12 iters), loss = 5.28364
I0405 12:53:30.279839 18799 solver.cpp:237]     Train net output #0: loss = 5.28364 (* 1 = 5.28364 loss)
I0405 12:53:30.279844 18799 sgd_solver.cpp:105] Iteration 696, lr = 0.0001
I0405 12:53:35.095299 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:53:35.508512 18799 solver.cpp:218] Iteration 708 (2.29506 iter/s, 5.22863s/12 iters), loss = 5.28836
I0405 12:53:35.508551 18799 solver.cpp:237]     Train net output #0: loss = 5.28836 (* 1 = 5.28836 loss)
I0405 12:53:35.508558 18799 sgd_solver.cpp:105] Iteration 708, lr = 0.0001
I0405 12:53:37.719682 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel
I0405 12:53:40.752068 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate
I0405 12:53:43.053315 18799 solver.cpp:330] Iteration 714, Testing net (#0)
I0405 12:53:43.053335 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:53:47.167016 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:53:47.482630 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:53:47.482666 18799 solver.cpp:397]     Test net output #1: loss = 5.27866 (* 1 = 5.27866 loss)
I0405 12:53:49.480566 18799 solver.cpp:218] Iteration 720 (0.858866 iter/s, 13.9719s/12 iters), loss = 5.27659
I0405 12:53:49.480609 18799 solver.cpp:237]     Train net output #0: loss = 5.27659 (* 1 = 5.27659 loss)
I0405 12:53:49.480615 18799 sgd_solver.cpp:105] Iteration 720, lr = 0.0001
I0405 12:53:55.008401 18799 solver.cpp:218] Iteration 732 (2.17087 iter/s, 5.52774s/12 iters), loss = 5.27236
I0405 12:53:55.008460 18799 solver.cpp:237]     Train net output #0: loss = 5.27236 (* 1 = 5.27236 loss)
I0405 12:53:55.008468 18799 sgd_solver.cpp:105] Iteration 732, lr = 0.0001
I0405 12:54:00.399564 18799 solver.cpp:218] Iteration 744 (2.22591 iter/s, 5.39106s/12 iters), loss = 5.27511
I0405 12:54:00.399605 18799 solver.cpp:237]     Train net output #0: loss = 5.27511 (* 1 = 5.27511 loss)
I0405 12:54:00.399611 18799 sgd_solver.cpp:105] Iteration 744, lr = 0.0001
I0405 12:54:05.709286 18799 solver.cpp:218] Iteration 756 (2.26004 iter/s, 5.30963s/12 iters), loss = 5.29114
I0405 12:54:05.709329 18799 solver.cpp:237]     Train net output #0: loss = 5.29114 (* 1 = 5.29114 loss)
I0405 12:54:05.709336 18799 sgd_solver.cpp:105] Iteration 756, lr = 0.0001
I0405 12:54:11.060045 18799 solver.cpp:218] Iteration 768 (2.24271 iter/s, 5.35067s/12 iters), loss = 5.2863
I0405 12:54:11.060214 18799 solver.cpp:237]     Train net output #0: loss = 5.2863 (* 1 = 5.2863 loss)
I0405 12:54:11.060223 18799 sgd_solver.cpp:105] Iteration 768, lr = 0.0001
I0405 12:54:16.406826 18799 solver.cpp:218] Iteration 780 (2.24443 iter/s, 5.34656s/12 iters), loss = 5.28894
I0405 12:54:16.406883 18799 solver.cpp:237]     Train net output #0: loss = 5.28894 (* 1 = 5.28894 loss)
I0405 12:54:16.406889 18799 sgd_solver.cpp:105] Iteration 780, lr = 0.0001
I0405 12:54:21.931612 18799 solver.cpp:218] Iteration 792 (2.17207 iter/s, 5.52468s/12 iters), loss = 5.27449
I0405 12:54:21.931663 18799 solver.cpp:237]     Train net output #0: loss = 5.27449 (* 1 = 5.27449 loss)
I0405 12:54:21.931670 18799 sgd_solver.cpp:105] Iteration 792, lr = 0.0001
I0405 12:54:27.355553 18799 solver.cpp:218] Iteration 804 (2.21245 iter/s, 5.42385s/12 iters), loss = 5.29026
I0405 12:54:27.355593 18799 solver.cpp:237]     Train net output #0: loss = 5.29026 (* 1 = 5.29026 loss)
I0405 12:54:27.355599 18799 sgd_solver.cpp:105] Iteration 804, lr = 0.0001
I0405 12:54:29.183979 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:54:32.072636 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel
I0405 12:54:35.070063 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate
I0405 12:54:38.144762 18799 solver.cpp:330] Iteration 816, Testing net (#0)
I0405 12:54:38.144783 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:54:42.268708 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:54:42.623370 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:54:42.623410 18799 solver.cpp:397]     Test net output #1: loss = 5.27896 (* 1 = 5.27896 loss)
I0405 12:54:42.762904 18799 solver.cpp:218] Iteration 816 (0.778856 iter/s, 15.4072s/12 iters), loss = 5.29418
I0405 12:54:42.762969 18799 solver.cpp:237]     Train net output #0: loss = 5.29418 (* 1 = 5.29418 loss)
I0405 12:54:42.762977 18799 sgd_solver.cpp:105] Iteration 816, lr = 0.0001
I0405 12:54:47.096233 18799 solver.cpp:218] Iteration 828 (2.7693 iter/s, 4.33322s/12 iters), loss = 5.26427
I0405 12:54:47.096273 18799 solver.cpp:237]     Train net output #0: loss = 5.26427 (* 1 = 5.26427 loss)
I0405 12:54:47.096278 18799 sgd_solver.cpp:105] Iteration 828, lr = 0.0001
I0405 12:54:52.390753 18799 solver.cpp:218] Iteration 840 (2.26653 iter/s, 5.29443s/12 iters), loss = 5.27755
I0405 12:54:52.390801 18799 solver.cpp:237]     Train net output #0: loss = 5.27755 (* 1 = 5.27755 loss)
I0405 12:54:52.390810 18799 sgd_solver.cpp:105] Iteration 840, lr = 0.0001
I0405 12:54:57.758085 18799 solver.cpp:218] Iteration 852 (2.23579 iter/s, 5.36723s/12 iters), loss = 5.27005
I0405 12:54:57.758138 18799 solver.cpp:237]     Train net output #0: loss = 5.27005 (* 1 = 5.27005 loss)
I0405 12:54:57.758148 18799 sgd_solver.cpp:105] Iteration 852, lr = 0.0001
I0405 12:55:02.984901 18799 solver.cpp:218] Iteration 864 (2.2959 iter/s, 5.22671s/12 iters), loss = 5.27231
I0405 12:55:02.984961 18799 solver.cpp:237]     Train net output #0: loss = 5.27231 (* 1 = 5.27231 loss)
I0405 12:55:02.984969 18799 sgd_solver.cpp:105] Iteration 864, lr = 0.0001
I0405 12:55:08.170784 18799 solver.cpp:218] Iteration 876 (2.31402 iter/s, 5.18578s/12 iters), loss = 5.26638
I0405 12:55:08.170825 18799 solver.cpp:237]     Train net output #0: loss = 5.26638 (* 1 = 5.26638 loss)
I0405 12:55:08.170830 18799 sgd_solver.cpp:105] Iteration 876, lr = 0.0001
I0405 12:55:13.681682 18799 solver.cpp:218] Iteration 888 (2.17754 iter/s, 5.51081s/12 iters), loss = 5.28988
I0405 12:55:13.681777 18799 solver.cpp:237]     Train net output #0: loss = 5.28988 (* 1 = 5.28988 loss)
I0405 12:55:13.681784 18799 sgd_solver.cpp:105] Iteration 888, lr = 0.0001
I0405 12:55:18.793874 18799 solver.cpp:218] Iteration 900 (2.3474 iter/s, 5.11205s/12 iters), loss = 5.26136
I0405 12:55:18.793938 18799 solver.cpp:237]     Train net output #0: loss = 5.26136 (* 1 = 5.26136 loss)
I0405 12:55:18.793946 18799 sgd_solver.cpp:105] Iteration 900, lr = 0.0001
I0405 12:55:22.977797 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:55:24.206346 18799 solver.cpp:218] Iteration 912 (2.21715 iter/s, 5.41235s/12 iters), loss = 5.28718
I0405 12:55:24.206403 18799 solver.cpp:237]     Train net output #0: loss = 5.28718 (* 1 = 5.28718 loss)
I0405 12:55:24.206409 18799 sgd_solver.cpp:105] Iteration 912, lr = 0.0001
I0405 12:55:26.162132 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel
I0405 12:55:29.221357 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate
I0405 12:55:31.542186 18799 solver.cpp:330] Iteration 918, Testing net (#0)
I0405 12:55:31.542208 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:55:35.563766 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:55:35.964453 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:55:35.964491 18799 solver.cpp:397]     Test net output #1: loss = 5.27918 (* 1 = 5.27918 loss)
I0405 12:55:38.031910 18799 solver.cpp:218] Iteration 924 (0.867967 iter/s, 13.8254s/12 iters), loss = 5.26749
I0405 12:55:38.031952 18799 solver.cpp:237]     Train net output #0: loss = 5.26749 (* 1 = 5.26749 loss)
I0405 12:55:38.031958 18799 sgd_solver.cpp:105] Iteration 924, lr = 0.0001
I0405 12:55:43.180267 18799 solver.cpp:218] Iteration 936 (2.33088 iter/s, 5.14827s/12 iters), loss = 5.29034
I0405 12:55:43.180311 18799 solver.cpp:237]     Train net output #0: loss = 5.29034 (* 1 = 5.29034 loss)
I0405 12:55:43.180318 18799 sgd_solver.cpp:105] Iteration 936, lr = 0.0001
I0405 12:55:48.238343 18799 solver.cpp:218] Iteration 948 (2.37249 iter/s, 5.05798s/12 iters), loss = 5.26792
I0405 12:55:48.238467 18799 solver.cpp:237]     Train net output #0: loss = 5.26792 (* 1 = 5.26792 loss)
I0405 12:55:48.238474 18799 sgd_solver.cpp:105] Iteration 948, lr = 0.0001
I0405 12:55:53.487284 18799 solver.cpp:218] Iteration 960 (2.28625 iter/s, 5.24876s/12 iters), loss = 5.27754
I0405 12:55:53.487341 18799 solver.cpp:237]     Train net output #0: loss = 5.27754 (* 1 = 5.27754 loss)
I0405 12:55:53.487349 18799 sgd_solver.cpp:105] Iteration 960, lr = 0.0001
I0405 12:55:58.724465 18799 solver.cpp:218] Iteration 972 (2.29135 iter/s, 5.23708s/12 iters), loss = 5.28207
I0405 12:55:58.724504 18799 solver.cpp:237]     Train net output #0: loss = 5.28207 (* 1 = 5.28207 loss)
I0405 12:55:58.724510 18799 sgd_solver.cpp:105] Iteration 972, lr = 0.0001
I0405 12:56:04.135929 18799 solver.cpp:218] Iteration 984 (2.21755 iter/s, 5.41138s/12 iters), loss = 5.28877
I0405 12:56:04.135967 18799 solver.cpp:237]     Train net output #0: loss = 5.28877 (* 1 = 5.28877 loss)
I0405 12:56:04.135973 18799 sgd_solver.cpp:105] Iteration 984, lr = 0.0001
I0405 12:56:09.423400 18799 solver.cpp:218] Iteration 996 (2.26955 iter/s, 5.28738s/12 iters), loss = 5.27241
I0405 12:56:09.423439 18799 solver.cpp:237]     Train net output #0: loss = 5.27241 (* 1 = 5.27241 loss)
I0405 12:56:09.423444 18799 sgd_solver.cpp:105] Iteration 996, lr = 0.0001
I0405 12:56:14.716086 18799 solver.cpp:218] Iteration 1008 (2.26732 iter/s, 5.2926s/12 iters), loss = 5.28971
I0405 12:56:14.716126 18799 solver.cpp:237]     Train net output #0: loss = 5.28971 (* 1 = 5.28971 loss)
I0405 12:56:14.716131 18799 sgd_solver.cpp:105] Iteration 1008, lr = 0.0001
I0405 12:56:15.796226 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:56:19.636819 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel
I0405 12:56:22.739758 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate
I0405 12:56:25.030330 18799 solver.cpp:330] Iteration 1020, Testing net (#0)
I0405 12:56:25.030350 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:56:29.010615 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:56:29.439561 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:56:29.439590 18799 solver.cpp:397]     Test net output #1: loss = 5.27954 (* 1 = 5.27954 loss)
I0405 12:56:29.581630 18799 solver.cpp:218] Iteration 1020 (0.807244 iter/s, 14.8654s/12 iters), loss = 5.27794
I0405 12:56:29.581679 18799 solver.cpp:237]     Train net output #0: loss = 5.27794 (* 1 = 5.27794 loss)
I0405 12:56:29.581686 18799 sgd_solver.cpp:105] Iteration 1020, lr = 0.0001
I0405 12:56:34.105661 18799 solver.cpp:218] Iteration 1032 (2.65255 iter/s, 4.52395s/12 iters), loss = 5.28332
I0405 12:56:34.105702 18799 solver.cpp:237]     Train net output #0: loss = 5.28332 (* 1 = 5.28332 loss)
I0405 12:56:34.105710 18799 sgd_solver.cpp:105] Iteration 1032, lr = 0.0001
I0405 12:56:39.664376 18799 solver.cpp:218] Iteration 1044 (2.15881 iter/s, 5.55862s/12 iters), loss = 5.28286
I0405 12:56:39.664418 18799 solver.cpp:237]     Train net output #0: loss = 5.28286 (* 1 = 5.28286 loss)
I0405 12:56:39.664424 18799 sgd_solver.cpp:105] Iteration 1044, lr = 0.0001
I0405 12:56:45.000386 18799 solver.cpp:218] Iteration 1056 (2.24891 iter/s, 5.33592s/12 iters), loss = 5.27629
I0405 12:56:45.000427 18799 solver.cpp:237]     Train net output #0: loss = 5.27629 (* 1 = 5.27629 loss)
I0405 12:56:45.000432 18799 sgd_solver.cpp:105] Iteration 1056, lr = 0.0001
I0405 12:56:50.276078 18799 solver.cpp:218] Iteration 1068 (2.27462 iter/s, 5.2756s/12 iters), loss = 5.2923
I0405 12:56:50.276209 18799 solver.cpp:237]     Train net output #0: loss = 5.2923 (* 1 = 5.2923 loss)
I0405 12:56:50.276216 18799 sgd_solver.cpp:105] Iteration 1068, lr = 0.0001
I0405 12:56:55.606760 18799 solver.cpp:218] Iteration 1080 (2.25119 iter/s, 5.33051s/12 iters), loss = 5.25755
I0405 12:56:55.606801 18799 solver.cpp:237]     Train net output #0: loss = 5.25755 (* 1 = 5.25755 loss)
I0405 12:56:55.606806 18799 sgd_solver.cpp:105] Iteration 1080, lr = 0.0001
I0405 12:57:00.967819 18799 solver.cpp:218] Iteration 1092 (2.2384 iter/s, 5.36097s/12 iters), loss = 5.27449
I0405 12:57:00.967862 18799 solver.cpp:237]     Train net output #0: loss = 5.27449 (* 1 = 5.27449 loss)
I0405 12:57:00.967867 18799 sgd_solver.cpp:105] Iteration 1092, lr = 0.0001
I0405 12:57:06.219669 18799 solver.cpp:218] Iteration 1104 (2.28495 iter/s, 5.25176s/12 iters), loss = 5.29125
I0405 12:57:06.219707 18799 solver.cpp:237]     Train net output #0: loss = 5.29125 (* 1 = 5.29125 loss)
I0405 12:57:06.219712 18799 sgd_solver.cpp:105] Iteration 1104, lr = 0.0001
I0405 12:57:09.537122 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:57:11.485092 18799 solver.cpp:218] Iteration 1116 (2.27906 iter/s, 5.26534s/12 iters), loss = 5.24766
I0405 12:57:11.485134 18799 solver.cpp:237]     Train net output #0: loss = 5.24766 (* 1 = 5.24766 loss)
I0405 12:57:11.485141 18799 sgd_solver.cpp:105] Iteration 1116, lr = 0.0001
I0405 12:57:13.707861 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel
I0405 12:57:16.680284 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate
I0405 12:57:18.990686 18799 solver.cpp:330] Iteration 1122, Testing net (#0)
I0405 12:57:18.990710 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:57:22.885056 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:57:23.370772 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:57:23.370810 18799 solver.cpp:397]     Test net output #1: loss = 5.27933 (* 1 = 5.27933 loss)
I0405 12:57:25.350731 18799 solver.cpp:218] Iteration 1128 (0.865457 iter/s, 13.8655s/12 iters), loss = 5.27903
I0405 12:57:25.350772 18799 solver.cpp:237]     Train net output #0: loss = 5.27903 (* 1 = 5.27903 loss)
I0405 12:57:25.350777 18799 sgd_solver.cpp:105] Iteration 1128, lr = 0.0001
I0405 12:57:30.421190 18799 solver.cpp:218] Iteration 1140 (2.36669 iter/s, 5.07037s/12 iters), loss = 5.26806
I0405 12:57:30.421231 18799 solver.cpp:237]     Train net output #0: loss = 5.26806 (* 1 = 5.26806 loss)
I0405 12:57:30.421237 18799 sgd_solver.cpp:105] Iteration 1140, lr = 0.0001
I0405 12:57:35.798223 18799 solver.cpp:218] Iteration 1152 (2.23175 iter/s, 5.37694s/12 iters), loss = 5.28451
I0405 12:57:35.798264 18799 solver.cpp:237]     Train net output #0: loss = 5.28451 (* 1 = 5.28451 loss)
I0405 12:57:35.798271 18799 sgd_solver.cpp:105] Iteration 1152, lr = 0.0001
I0405 12:57:41.268131 18799 solver.cpp:218] Iteration 1164 (2.19386 iter/s, 5.46981s/12 iters), loss = 5.27176
I0405 12:57:41.268174 18799 solver.cpp:237]     Train net output #0: loss = 5.27176 (* 1 = 5.27176 loss)
I0405 12:57:41.268180 18799 sgd_solver.cpp:105] Iteration 1164, lr = 0.0001
I0405 12:57:46.597287 18799 solver.cpp:218] Iteration 1176 (2.2518 iter/s, 5.32906s/12 iters), loss = 5.28141
I0405 12:57:46.597334 18799 solver.cpp:237]     Train net output #0: loss = 5.28141 (* 1 = 5.28141 loss)
I0405 12:57:46.597340 18799 sgd_solver.cpp:105] Iteration 1176, lr = 0.0001
I0405 12:57:51.944012 18799 solver.cpp:218] Iteration 1188 (2.2444 iter/s, 5.34663s/12 iters), loss = 5.26354
I0405 12:57:51.944068 18799 solver.cpp:237]     Train net output #0: loss = 5.26354 (* 1 = 5.26354 loss)
I0405 12:57:51.944077 18799 sgd_solver.cpp:105] Iteration 1188, lr = 0.0001
I0405 12:57:57.350545 18799 solver.cpp:218] Iteration 1200 (2.21958 iter/s, 5.40643s/12 iters), loss = 5.29425
I0405 12:57:57.350674 18799 solver.cpp:237]     Train net output #0: loss = 5.29425 (* 1 = 5.29425 loss)
I0405 12:57:57.350682 18799 sgd_solver.cpp:105] Iteration 1200, lr = 0.0001
I0405 12:58:02.624908 18799 solver.cpp:218] Iteration 1212 (2.27523 iter/s, 5.27418s/12 iters), loss = 5.27604
I0405 12:58:02.624953 18799 solver.cpp:237]     Train net output #0: loss = 5.27604 (* 1 = 5.27604 loss)
I0405 12:58:02.624958 18799 sgd_solver.cpp:105] Iteration 1212, lr = 0.0001
I0405 12:58:02.883018 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:58:07.571254 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel
I0405 12:58:10.572837 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate
I0405 12:58:12.912323 18799 solver.cpp:330] Iteration 1224, Testing net (#0)
I0405 12:58:12.912343 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:58:16.709934 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:58:17.212266 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:58:17.212299 18799 solver.cpp:397]     Test net output #1: loss = 5.2793 (* 1 = 5.2793 loss)
I0405 12:58:17.352526 18799 solver.cpp:218] Iteration 1224 (0.814804 iter/s, 14.7275s/12 iters), loss = 5.27021
I0405 12:58:17.352581 18799 solver.cpp:237]     Train net output #0: loss = 5.27021 (* 1 = 5.27021 loss)
I0405 12:58:17.352588 18799 sgd_solver.cpp:105] Iteration 1224, lr = 0.0001
I0405 12:58:21.743077 18799 solver.cpp:218] Iteration 1236 (2.7332 iter/s, 4.39046s/12 iters), loss = 5.29284
I0405 12:58:21.743117 18799 solver.cpp:237]     Train net output #0: loss = 5.29284 (* 1 = 5.29284 loss)
I0405 12:58:21.743122 18799 sgd_solver.cpp:105] Iteration 1236, lr = 0.0001
I0405 12:58:27.006479 18799 solver.cpp:218] Iteration 1248 (2.27993 iter/s, 5.26331s/12 iters), loss = 5.27355
I0405 12:58:27.006531 18799 solver.cpp:237]     Train net output #0: loss = 5.27355 (* 1 = 5.27355 loss)
I0405 12:58:27.006541 18799 sgd_solver.cpp:105] Iteration 1248, lr = 0.0001
I0405 12:58:32.396781 18799 solver.cpp:218] Iteration 1260 (2.22626 iter/s, 5.3902s/12 iters), loss = 5.27568
I0405 12:58:32.396905 18799 solver.cpp:237]     Train net output #0: loss = 5.27568 (* 1 = 5.27568 loss)
I0405 12:58:32.396915 18799 sgd_solver.cpp:105] Iteration 1260, lr = 0.0001
I0405 12:58:37.782155 18799 solver.cpp:218] Iteration 1272 (2.22833 iter/s, 5.38521s/12 iters), loss = 5.27959
I0405 12:58:37.782193 18799 solver.cpp:237]     Train net output #0: loss = 5.27959 (* 1 = 5.27959 loss)
I0405 12:58:37.782199 18799 sgd_solver.cpp:105] Iteration 1272, lr = 0.0001
I0405 12:58:43.134948 18799 solver.cpp:218] Iteration 1284 (2.24186 iter/s, 5.3527s/12 iters), loss = 5.26736
I0405 12:58:43.134991 18799 solver.cpp:237]     Train net output #0: loss = 5.26736 (* 1 = 5.26736 loss)
I0405 12:58:43.134997 18799 sgd_solver.cpp:105] Iteration 1284, lr = 0.0001
I0405 12:58:48.368557 18799 solver.cpp:218] Iteration 1296 (2.29291 iter/s, 5.23352s/12 iters), loss = 5.28855
I0405 12:58:48.368607 18799 solver.cpp:237]     Train net output #0: loss = 5.28855 (* 1 = 5.28855 loss)
I0405 12:58:48.368613 18799 sgd_solver.cpp:105] Iteration 1296, lr = 0.0001
I0405 12:58:53.810091 18799 solver.cpp:218] Iteration 1308 (2.2053 iter/s, 5.44143s/12 iters), loss = 5.27685
I0405 12:58:53.810142 18799 solver.cpp:237]     Train net output #0: loss = 5.27685 (* 1 = 5.27685 loss)
I0405 12:58:53.810148 18799 sgd_solver.cpp:105] Iteration 1308, lr = 0.0001
I0405 12:58:56.237488 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:58:58.855283 18799 solver.cpp:218] Iteration 1320 (2.37855 iter/s, 5.0451s/12 iters), loss = 5.29122
I0405 12:58:58.855327 18799 solver.cpp:237]     Train net output #0: loss = 5.29122 (* 1 = 5.29122 loss)
I0405 12:58:58.855335 18799 sgd_solver.cpp:105] Iteration 1320, lr = 0.0001
I0405 12:59:01.071359 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel
I0405 12:59:04.086544 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate
I0405 12:59:06.731937 18799 solver.cpp:330] Iteration 1326, Testing net (#0)
I0405 12:59:06.731961 18799 net.cpp:676] Ignoring source layer train-data
I0405 12:59:10.526922 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:59:11.144523 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 12:59:11.144559 18799 solver.cpp:397]     Test net output #1: loss = 5.27956 (* 1 = 5.27956 loss)
I0405 12:59:13.169512 18799 solver.cpp:218] Iteration 1332 (0.838335 iter/s, 14.3141s/12 iters), loss = 5.29397
I0405 12:59:13.169553 18799 solver.cpp:237]     Train net output #0: loss = 5.29397 (* 1 = 5.29397 loss)
I0405 12:59:13.169559 18799 sgd_solver.cpp:105] Iteration 1332, lr = 0.0001
I0405 12:59:18.487751 18799 solver.cpp:218] Iteration 1344 (2.25642 iter/s, 5.31815s/12 iters), loss = 5.28744
I0405 12:59:18.487785 18799 solver.cpp:237]     Train net output #0: loss = 5.28744 (* 1 = 5.28744 loss)
I0405 12:59:18.487790 18799 sgd_solver.cpp:105] Iteration 1344, lr = 0.0001
I0405 12:59:23.707897 18799 solver.cpp:218] Iteration 1356 (2.29882 iter/s, 5.22006s/12 iters), loss = 5.27499
I0405 12:59:23.707952 18799 solver.cpp:237]     Train net output #0: loss = 5.27499 (* 1 = 5.27499 loss)
I0405 12:59:23.707959 18799 sgd_solver.cpp:105] Iteration 1356, lr = 0.0001
I0405 12:59:28.975590 18799 solver.cpp:218] Iteration 1368 (2.27808 iter/s, 5.2676s/12 iters), loss = 5.2747
I0405 12:59:28.975631 18799 solver.cpp:237]     Train net output #0: loss = 5.2747 (* 1 = 5.2747 loss)
I0405 12:59:28.975637 18799 sgd_solver.cpp:105] Iteration 1368, lr = 0.0001
I0405 12:59:30.254719 18799 blocking_queue.cpp:49] Waiting for data
I0405 12:59:34.239274 18799 solver.cpp:218] Iteration 1380 (2.27981 iter/s, 5.26359s/12 iters), loss = 5.27513
I0405 12:59:34.239396 18799 solver.cpp:237]     Train net output #0: loss = 5.27513 (* 1 = 5.27513 loss)
I0405 12:59:34.239403 18799 sgd_solver.cpp:105] Iteration 1380, lr = 0.0001
I0405 12:59:39.268446 18799 solver.cpp:218] Iteration 1392 (2.38615 iter/s, 5.02901s/12 iters), loss = 5.29558
I0405 12:59:39.268481 18799 solver.cpp:237]     Train net output #0: loss = 5.29558 (* 1 = 5.29558 loss)
I0405 12:59:39.268486 18799 sgd_solver.cpp:105] Iteration 1392, lr = 0.0001
I0405 12:59:44.347242 18799 solver.cpp:218] Iteration 1404 (2.3628 iter/s, 5.07871s/12 iters), loss = 5.28424
I0405 12:59:44.347286 18799 solver.cpp:237]     Train net output #0: loss = 5.28424 (* 1 = 5.28424 loss)
I0405 12:59:44.347292 18799 sgd_solver.cpp:105] Iteration 1404, lr = 0.0001
I0405 12:59:49.093425 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 12:59:49.480063 18799 solver.cpp:218] Iteration 1416 (2.33794 iter/s, 5.13273s/12 iters), loss = 5.28765
I0405 12:59:49.480104 18799 solver.cpp:237]     Train net output #0: loss = 5.28765 (* 1 = 5.28765 loss)
I0405 12:59:49.480109 18799 sgd_solver.cpp:105] Iteration 1416, lr = 0.0001
I0405 12:59:54.074458 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel
I0405 12:59:57.034801 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate
I0405 12:59:59.338551 18799 solver.cpp:330] Iteration 1428, Testing net (#0)
I0405 12:59:59.338579 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:00:03.106876 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:00:03.741063 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:00:03.741101 18799 solver.cpp:397]     Test net output #1: loss = 5.27967 (* 1 = 5.27967 loss)
I0405 13:00:03.883915 18799 solver.cpp:218] Iteration 1428 (0.833119 iter/s, 14.4037s/12 iters), loss = 5.2499
I0405 13:00:03.885515 18799 solver.cpp:237]     Train net output #0: loss = 5.2499 (* 1 = 5.2499 loss)
I0405 13:00:03.885526 18799 sgd_solver.cpp:105] Iteration 1428, lr = 0.0001
I0405 13:00:08.289132 18799 solver.cpp:218] Iteration 1440 (2.72506 iter/s, 4.40358s/12 iters), loss = 5.27383
I0405 13:00:08.289275 18799 solver.cpp:237]     Train net output #0: loss = 5.27383 (* 1 = 5.27383 loss)
I0405 13:00:08.289284 18799 sgd_solver.cpp:105] Iteration 1440, lr = 0.0001
I0405 13:00:13.330756 18799 solver.cpp:218] Iteration 1452 (2.38027 iter/s, 5.04144s/12 iters), loss = 5.27316
I0405 13:00:13.330801 18799 solver.cpp:237]     Train net output #0: loss = 5.27316 (* 1 = 5.27316 loss)
I0405 13:00:13.330807 18799 sgd_solver.cpp:105] Iteration 1452, lr = 0.0001
I0405 13:00:18.729684 18799 solver.cpp:218] Iteration 1464 (2.2227 iter/s, 5.39883s/12 iters), loss = 5.27546
I0405 13:00:18.729725 18799 solver.cpp:237]     Train net output #0: loss = 5.27546 (* 1 = 5.27546 loss)
I0405 13:00:18.729732 18799 sgd_solver.cpp:105] Iteration 1464, lr = 0.0001
I0405 13:00:23.705371 18799 solver.cpp:218] Iteration 1476 (2.41177 iter/s, 4.97559s/12 iters), loss = 5.27841
I0405 13:00:23.705422 18799 solver.cpp:237]     Train net output #0: loss = 5.27841 (* 1 = 5.27841 loss)
I0405 13:00:23.705430 18799 sgd_solver.cpp:105] Iteration 1476, lr = 0.0001
I0405 13:00:28.942229 18799 solver.cpp:218] Iteration 1488 (2.29149 iter/s, 5.23676s/12 iters), loss = 5.27895
I0405 13:00:28.942270 18799 solver.cpp:237]     Train net output #0: loss = 5.27895 (* 1 = 5.27895 loss)
I0405 13:00:28.942276 18799 sgd_solver.cpp:105] Iteration 1488, lr = 0.0001
I0405 13:00:34.217869 18799 solver.cpp:218] Iteration 1500 (2.27464 iter/s, 5.27555s/12 iters), loss = 5.27701
I0405 13:00:34.217913 18799 solver.cpp:237]     Train net output #0: loss = 5.27701 (* 1 = 5.27701 loss)
I0405 13:00:34.217919 18799 sgd_solver.cpp:105] Iteration 1500, lr = 0.0001
I0405 13:00:39.457847 18799 solver.cpp:218] Iteration 1512 (2.29013 iter/s, 5.23988s/12 iters), loss = 5.27327
I0405 13:00:39.457962 18799 solver.cpp:237]     Train net output #0: loss = 5.27327 (* 1 = 5.27327 loss)
I0405 13:00:39.457969 18799 sgd_solver.cpp:105] Iteration 1512, lr = 0.0001
I0405 13:00:41.358832 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:00:44.762574 18799 solver.cpp:218] Iteration 1524 (2.2622 iter/s, 5.30457s/12 iters), loss = 5.30143
I0405 13:00:44.762615 18799 solver.cpp:237]     Train net output #0: loss = 5.30143 (* 1 = 5.30143 loss)
I0405 13:00:44.762620 18799 sgd_solver.cpp:105] Iteration 1524, lr = 0.0001
I0405 13:00:46.916340 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel
I0405 13:00:49.974962 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate
I0405 13:00:52.269333 18799 solver.cpp:330] Iteration 1530, Testing net (#0)
I0405 13:00:52.269356 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:00:56.016182 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:00:56.691114 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:00:56.691150 18799 solver.cpp:397]     Test net output #1: loss = 5.27963 (* 1 = 5.27963 loss)
I0405 13:00:58.673255 18799 solver.cpp:218] Iteration 1536 (0.862655 iter/s, 13.9105s/12 iters), loss = 5.26658
I0405 13:00:58.673296 18799 solver.cpp:237]     Train net output #0: loss = 5.26658 (* 1 = 5.26658 loss)
I0405 13:00:58.673301 18799 sgd_solver.cpp:105] Iteration 1536, lr = 0.0001
I0405 13:01:03.830961 18799 solver.cpp:218] Iteration 1548 (2.32666 iter/s, 5.15761s/12 iters), loss = 5.26952
I0405 13:01:03.831022 18799 solver.cpp:237]     Train net output #0: loss = 5.26952 (* 1 = 5.26952 loss)
I0405 13:01:03.831032 18799 sgd_solver.cpp:105] Iteration 1548, lr = 0.0001
I0405 13:01:09.167371 18799 solver.cpp:218] Iteration 1560 (2.24875 iter/s, 5.3363s/12 iters), loss = 5.27281
I0405 13:01:09.167409 18799 solver.cpp:237]     Train net output #0: loss = 5.27281 (* 1 = 5.27281 loss)
I0405 13:01:09.167415 18799 sgd_solver.cpp:105] Iteration 1560, lr = 0.0001
I0405 13:01:14.501835 18799 solver.cpp:218] Iteration 1572 (2.24956 iter/s, 5.33438s/12 iters), loss = 5.26827
I0405 13:01:14.501971 18799 solver.cpp:237]     Train net output #0: loss = 5.26827 (* 1 = 5.26827 loss)
I0405 13:01:14.501977 18799 sgd_solver.cpp:105] Iteration 1572, lr = 0.0001
I0405 13:01:19.870734 18799 solver.cpp:218] Iteration 1584 (2.23517 iter/s, 5.36872s/12 iters), loss = 5.26266
I0405 13:01:19.870787 18799 solver.cpp:237]     Train net output #0: loss = 5.26266 (* 1 = 5.26266 loss)
I0405 13:01:19.870795 18799 sgd_solver.cpp:105] Iteration 1584, lr = 0.0001
I0405 13:01:25.102048 18799 solver.cpp:218] Iteration 1596 (2.29392 iter/s, 5.23121s/12 iters), loss = 5.27252
I0405 13:01:25.102095 18799 solver.cpp:237]     Train net output #0: loss = 5.27252 (* 1 = 5.27252 loss)
I0405 13:01:25.102102 18799 sgd_solver.cpp:105] Iteration 1596, lr = 0.0001
I0405 13:01:30.417698 18799 solver.cpp:218] Iteration 1608 (2.25753 iter/s, 5.31555s/12 iters), loss = 5.25719
I0405 13:01:30.417737 18799 solver.cpp:237]     Train net output #0: loss = 5.25719 (* 1 = 5.25719 loss)
I0405 13:01:30.417742 18799 sgd_solver.cpp:105] Iteration 1608, lr = 0.0001
I0405 13:01:34.470273 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:01:35.671865 18799 solver.cpp:218] Iteration 1620 (2.28394 iter/s, 5.25408s/12 iters), loss = 5.26272
I0405 13:01:35.671916 18799 solver.cpp:237]     Train net output #0: loss = 5.26272 (* 1 = 5.26272 loss)
I0405 13:01:35.671923 18799 sgd_solver.cpp:105] Iteration 1620, lr = 0.0001
I0405 13:01:40.490020 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel
I0405 13:01:43.436538 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate
I0405 13:01:45.727085 18799 solver.cpp:330] Iteration 1632, Testing net (#0)
I0405 13:01:45.727161 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:01:49.472785 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:01:50.145339 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:01:50.145365 18799 solver.cpp:397]     Test net output #1: loss = 5.27995 (* 1 = 5.27995 loss)
I0405 13:01:50.286397 18799 solver.cpp:218] Iteration 1632 (0.821109 iter/s, 14.6144s/12 iters), loss = 5.2675
I0405 13:01:50.286438 18799 solver.cpp:237]     Train net output #0: loss = 5.2675 (* 1 = 5.2675 loss)
I0405 13:01:50.286444 18799 sgd_solver.cpp:105] Iteration 1632, lr = 0.0001
I0405 13:01:54.582777 18799 solver.cpp:218] Iteration 1644 (2.7931 iter/s, 4.2963s/12 iters), loss = 5.28979
I0405 13:01:54.582820 18799 solver.cpp:237]     Train net output #0: loss = 5.28979 (* 1 = 5.28979 loss)
I0405 13:01:54.582826 18799 sgd_solver.cpp:105] Iteration 1644, lr = 0.0001
I0405 13:01:59.955963 18799 solver.cpp:218] Iteration 1656 (2.23335 iter/s, 5.37309s/12 iters), loss = 5.28533
I0405 13:01:59.956022 18799 solver.cpp:237]     Train net output #0: loss = 5.28533 (* 1 = 5.28533 loss)
I0405 13:01:59.956032 18799 sgd_solver.cpp:105] Iteration 1656, lr = 0.0001
I0405 13:02:05.081032 18799 solver.cpp:218] Iteration 1668 (2.34148 iter/s, 5.12496s/12 iters), loss = 5.28336
I0405 13:02:05.081070 18799 solver.cpp:237]     Train net output #0: loss = 5.28336 (* 1 = 5.28336 loss)
I0405 13:02:05.081075 18799 sgd_solver.cpp:105] Iteration 1668, lr = 0.0001
I0405 13:02:10.341049 18799 solver.cpp:218] Iteration 1680 (2.2814 iter/s, 5.25993s/12 iters), loss = 5.2777
I0405 13:02:10.341100 18799 solver.cpp:237]     Train net output #0: loss = 5.2777 (* 1 = 5.2777 loss)
I0405 13:02:10.341109 18799 sgd_solver.cpp:105] Iteration 1680, lr = 0.0001
I0405 13:02:15.730401 18799 solver.cpp:218] Iteration 1692 (2.22665 iter/s, 5.38926s/12 iters), loss = 5.27732
I0405 13:02:15.730532 18799 solver.cpp:237]     Train net output #0: loss = 5.27732 (* 1 = 5.27732 loss)
I0405 13:02:15.730540 18799 sgd_solver.cpp:105] Iteration 1692, lr = 0.0001
I0405 13:02:20.914904 18799 solver.cpp:218] Iteration 1704 (2.31467 iter/s, 5.18433s/12 iters), loss = 5.26775
I0405 13:02:20.914948 18799 solver.cpp:237]     Train net output #0: loss = 5.26775 (* 1 = 5.26775 loss)
I0405 13:02:20.914954 18799 sgd_solver.cpp:105] Iteration 1704, lr = 0.0001
I0405 13:02:26.268913 18799 solver.cpp:218] Iteration 1716 (2.24135 iter/s, 5.35391s/12 iters), loss = 5.2768
I0405 13:02:26.268961 18799 solver.cpp:237]     Train net output #0: loss = 5.2768 (* 1 = 5.2768 loss)
I0405 13:02:26.268971 18799 sgd_solver.cpp:105] Iteration 1716, lr = 0.0001
I0405 13:02:27.284482 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:02:31.506686 18799 solver.cpp:218] Iteration 1728 (2.29109 iter/s, 5.23768s/12 iters), loss = 5.27005
I0405 13:02:31.506734 18799 solver.cpp:237]     Train net output #0: loss = 5.27005 (* 1 = 5.27005 loss)
I0405 13:02:31.506740 18799 sgd_solver.cpp:105] Iteration 1728, lr = 0.0001
I0405 13:02:33.517014 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel
I0405 13:02:36.592586 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate
I0405 13:02:38.882372 18799 solver.cpp:330] Iteration 1734, Testing net (#0)
I0405 13:02:38.882393 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:02:42.693387 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:02:43.515487 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:02:43.515530 18799 solver.cpp:397]     Test net output #1: loss = 5.2797 (* 1 = 5.2797 loss)
I0405 13:02:45.537703 18799 solver.cpp:218] Iteration 1740 (0.855257 iter/s, 14.0309s/12 iters), loss = 5.2967
I0405 13:02:45.537748 18799 solver.cpp:237]     Train net output #0: loss = 5.2967 (* 1 = 5.2967 loss)
I0405 13:02:45.537753 18799 sgd_solver.cpp:105] Iteration 1740, lr = 0.0001
I0405 13:02:50.711573 18799 solver.cpp:218] Iteration 1752 (2.31939 iter/s, 5.17378s/12 iters), loss = 5.27462
I0405 13:02:50.711694 18799 solver.cpp:237]     Train net output #0: loss = 5.27462 (* 1 = 5.27462 loss)
I0405 13:02:50.711701 18799 sgd_solver.cpp:105] Iteration 1752, lr = 0.0001
I0405 13:02:55.758159 18799 solver.cpp:218] Iteration 1764 (2.37792 iter/s, 5.04642s/12 iters), loss = 5.28069
I0405 13:02:55.758208 18799 solver.cpp:237]     Train net output #0: loss = 5.28069 (* 1 = 5.28069 loss)
I0405 13:02:55.758213 18799 sgd_solver.cpp:105] Iteration 1764, lr = 0.0001
I0405 13:03:01.097174 18799 solver.cpp:218] Iteration 1776 (2.24765 iter/s, 5.33891s/12 iters), loss = 5.28237
I0405 13:03:01.097223 18799 solver.cpp:237]     Train net output #0: loss = 5.28237 (* 1 = 5.28237 loss)
I0405 13:03:01.097231 18799 sgd_solver.cpp:105] Iteration 1776, lr = 0.0001
I0405 13:03:06.133766 18799 solver.cpp:218] Iteration 1788 (2.38261 iter/s, 5.0365s/12 iters), loss = 5.27512
I0405 13:03:06.133805 18799 solver.cpp:237]     Train net output #0: loss = 5.27512 (* 1 = 5.27512 loss)
I0405 13:03:06.133810 18799 sgd_solver.cpp:105] Iteration 1788, lr = 0.0001
I0405 13:03:11.424679 18799 solver.cpp:218] Iteration 1800 (2.26808 iter/s, 5.29082s/12 iters), loss = 5.25963
I0405 13:03:11.424732 18799 solver.cpp:237]     Train net output #0: loss = 5.25963 (* 1 = 5.25963 loss)
I0405 13:03:11.424739 18799 sgd_solver.cpp:105] Iteration 1800, lr = 0.0001
I0405 13:03:16.809998 18799 solver.cpp:218] Iteration 1812 (2.22832 iter/s, 5.38522s/12 iters), loss = 5.2763
I0405 13:03:16.810058 18799 solver.cpp:237]     Train net output #0: loss = 5.2763 (* 1 = 5.2763 loss)
I0405 13:03:16.810068 18799 sgd_solver.cpp:105] Iteration 1812, lr = 0.0001
I0405 13:03:20.193665 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:03:22.137230 18799 solver.cpp:218] Iteration 1824 (2.25262 iter/s, 5.32713s/12 iters), loss = 5.26023
I0405 13:03:22.137401 18799 solver.cpp:237]     Train net output #0: loss = 5.26023 (* 1 = 5.26023 loss)
I0405 13:03:22.137409 18799 sgd_solver.cpp:105] Iteration 1824, lr = 0.0001
I0405 13:03:26.783715 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel
I0405 13:03:29.769901 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate
I0405 13:03:32.080476 18799 solver.cpp:330] Iteration 1836, Testing net (#0)
I0405 13:03:32.080502 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:03:35.634780 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:03:36.378192 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:03:36.378232 18799 solver.cpp:397]     Test net output #1: loss = 5.28025 (* 1 = 5.28025 loss)
I0405 13:03:36.519621 18799 solver.cpp:218] Iteration 1836 (0.834369 iter/s, 14.3821s/12 iters), loss = 5.25508
I0405 13:03:36.519680 18799 solver.cpp:237]     Train net output #0: loss = 5.25508 (* 1 = 5.25508 loss)
I0405 13:03:36.519687 18799 sgd_solver.cpp:105] Iteration 1836, lr = 0.0001
I0405 13:03:40.863514 18799 solver.cpp:218] Iteration 1848 (2.76256 iter/s, 4.3438s/12 iters), loss = 5.26309
I0405 13:03:40.863554 18799 solver.cpp:237]     Train net output #0: loss = 5.26309 (* 1 = 5.26309 loss)
I0405 13:03:40.863559 18799 sgd_solver.cpp:105] Iteration 1848, lr = 0.0001
I0405 13:03:46.103018 18799 solver.cpp:218] Iteration 1860 (2.29033 iter/s, 5.23942s/12 iters), loss = 5.27504
I0405 13:03:46.103065 18799 solver.cpp:237]     Train net output #0: loss = 5.27504 (* 1 = 5.27504 loss)
I0405 13:03:46.103073 18799 sgd_solver.cpp:105] Iteration 1860, lr = 0.0001
I0405 13:03:51.519610 18799 solver.cpp:218] Iteration 1872 (2.21546 iter/s, 5.41649s/12 iters), loss = 5.26779
I0405 13:03:51.519666 18799 solver.cpp:237]     Train net output #0: loss = 5.26779 (* 1 = 5.26779 loss)
I0405 13:03:51.519673 18799 sgd_solver.cpp:105] Iteration 1872, lr = 0.0001
I0405 13:03:56.915664 18799 solver.cpp:218] Iteration 1884 (2.22389 iter/s, 5.39595s/12 iters), loss = 5.27978
I0405 13:03:56.915827 18799 solver.cpp:237]     Train net output #0: loss = 5.27978 (* 1 = 5.27978 loss)
I0405 13:03:56.915834 18799 sgd_solver.cpp:105] Iteration 1884, lr = 0.0001
I0405 13:04:02.205670 18799 solver.cpp:218] Iteration 1896 (2.26852 iter/s, 5.2898s/12 iters), loss = 5.26355
I0405 13:04:02.205716 18799 solver.cpp:237]     Train net output #0: loss = 5.26355 (* 1 = 5.26355 loss)
I0405 13:04:02.205722 18799 sgd_solver.cpp:105] Iteration 1896, lr = 0.0001
I0405 13:04:07.462821 18799 solver.cpp:218] Iteration 1908 (2.28265 iter/s, 5.25706s/12 iters), loss = 5.28586
I0405 13:04:07.462872 18799 solver.cpp:237]     Train net output #0: loss = 5.28586 (* 1 = 5.28586 loss)
I0405 13:04:07.462880 18799 sgd_solver.cpp:105] Iteration 1908, lr = 0.0001
I0405 13:04:12.754647 18799 solver.cpp:218] Iteration 1920 (2.26769 iter/s, 5.29173s/12 iters), loss = 5.26151
I0405 13:04:12.754695 18799 solver.cpp:237]     Train net output #0: loss = 5.26151 (* 1 = 5.26151 loss)
I0405 13:04:12.754703 18799 sgd_solver.cpp:105] Iteration 1920, lr = 0.0001
I0405 13:04:13.010773 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:04:17.918140 18799 solver.cpp:218] Iteration 1932 (2.32405 iter/s, 5.1634s/12 iters), loss = 5.27399
I0405 13:04:17.918179 18799 solver.cpp:237]     Train net output #0: loss = 5.27399 (* 1 = 5.27399 loss)
I0405 13:04:17.918186 18799 sgd_solver.cpp:105] Iteration 1932, lr = 0.0001
I0405 13:04:19.959466 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel
I0405 13:04:23.039151 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate
I0405 13:04:25.784097 18799 solver.cpp:330] Iteration 1938, Testing net (#0)
I0405 13:04:25.784118 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:04:29.409898 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:04:30.229470 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:04:30.229503 18799 solver.cpp:397]     Test net output #1: loss = 5.27956 (* 1 = 5.27956 loss)
I0405 13:04:32.158576 18799 solver.cpp:218] Iteration 1944 (0.842679 iter/s, 14.2403s/12 iters), loss = 5.29974
I0405 13:04:32.158638 18799 solver.cpp:237]     Train net output #0: loss = 5.29974 (* 1 = 5.29974 loss)
I0405 13:04:32.158648 18799 sgd_solver.cpp:105] Iteration 1944, lr = 0.0001
I0405 13:04:37.279508 18799 solver.cpp:218] Iteration 1956 (2.34337 iter/s, 5.12083s/12 iters), loss = 5.28473
I0405 13:04:37.279544 18799 solver.cpp:237]     Train net output #0: loss = 5.28473 (* 1 = 5.28473 loss)
I0405 13:04:37.279551 18799 sgd_solver.cpp:105] Iteration 1956, lr = 0.0001
I0405 13:04:42.366750 18799 solver.cpp:218] Iteration 1968 (2.35888 iter/s, 5.08716s/12 iters), loss = 5.27356
I0405 13:04:42.366797 18799 solver.cpp:237]     Train net output #0: loss = 5.27356 (* 1 = 5.27356 loss)
I0405 13:04:42.366806 18799 sgd_solver.cpp:105] Iteration 1968, lr = 0.0001
I0405 13:04:47.410147 18799 solver.cpp:218] Iteration 1980 (2.37939 iter/s, 5.04331s/12 iters), loss = 5.28199
I0405 13:04:47.410188 18799 solver.cpp:237]     Train net output #0: loss = 5.28199 (* 1 = 5.28199 loss)
I0405 13:04:47.410194 18799 sgd_solver.cpp:105] Iteration 1980, lr = 0.0001
I0405 13:04:52.749199 18799 solver.cpp:218] Iteration 1992 (2.24763 iter/s, 5.33896s/12 iters), loss = 5.2565
I0405 13:04:52.749238 18799 solver.cpp:237]     Train net output #0: loss = 5.2565 (* 1 = 5.2565 loss)
I0405 13:04:52.749244 18799 sgd_solver.cpp:105] Iteration 1992, lr = 0.0001
I0405 13:04:57.993782 18799 solver.cpp:218] Iteration 2004 (2.28811 iter/s, 5.24449s/12 iters), loss = 5.2912
I0405 13:04:57.993829 18799 solver.cpp:237]     Train net output #0: loss = 5.2912 (* 1 = 5.2912 loss)
I0405 13:04:57.993834 18799 sgd_solver.cpp:105] Iteration 2004, lr = 0.0001
I0405 13:05:03.423467 18799 solver.cpp:218] Iteration 2016 (2.21011 iter/s, 5.42959s/12 iters), loss = 5.26528
I0405 13:05:03.423559 18799 solver.cpp:237]     Train net output #0: loss = 5.26528 (* 1 = 5.26528 loss)
I0405 13:05:03.423566 18799 sgd_solver.cpp:105] Iteration 2016, lr = 0.0001
I0405 13:05:06.201234 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:05:08.878388 18799 solver.cpp:218] Iteration 2028 (2.1999 iter/s, 5.45478s/12 iters), loss = 5.29174
I0405 13:05:08.878430 18799 solver.cpp:237]     Train net output #0: loss = 5.29174 (* 1 = 5.29174 loss)
I0405 13:05:08.878437 18799 sgd_solver.cpp:105] Iteration 2028, lr = 0.0001
I0405 13:05:13.635740 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel
I0405 13:05:16.636739 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate
I0405 13:05:18.951133 18799 solver.cpp:330] Iteration 2040, Testing net (#0)
I0405 13:05:18.951161 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:05:22.510403 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:05:23.345674 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:05:23.345702 18799 solver.cpp:397]     Test net output #1: loss = 5.28043 (* 1 = 5.28043 loss)
I0405 13:05:23.487841 18799 solver.cpp:218] Iteration 2040 (0.821394 iter/s, 14.6093s/12 iters), loss = 5.29399
I0405 13:05:23.487901 18799 solver.cpp:237]     Train net output #0: loss = 5.29399 (* 1 = 5.29399 loss)
I0405 13:05:23.487910 18799 sgd_solver.cpp:105] Iteration 2040, lr = 0.0001
I0405 13:05:28.156388 18799 solver.cpp:218] Iteration 2052 (2.57045 iter/s, 4.66845s/12 iters), loss = 5.26466
I0405 13:05:28.156441 18799 solver.cpp:237]     Train net output #0: loss = 5.26466 (* 1 = 5.26466 loss)
I0405 13:05:28.156450 18799 sgd_solver.cpp:105] Iteration 2052, lr = 0.0001
I0405 13:05:29.865872 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:05:33.483327 18799 solver.cpp:218] Iteration 2064 (2.25274 iter/s, 5.32684s/12 iters), loss = 5.28078
I0405 13:05:33.483481 18799 solver.cpp:237]     Train net output #0: loss = 5.28078 (* 1 = 5.28078 loss)
I0405 13:05:33.483491 18799 sgd_solver.cpp:105] Iteration 2064, lr = 0.0001
I0405 13:05:38.911475 18799 solver.cpp:218] Iteration 2076 (2.21078 iter/s, 5.42795s/12 iters), loss = 5.27054
I0405 13:05:38.911533 18799 solver.cpp:237]     Train net output #0: loss = 5.27054 (* 1 = 5.27054 loss)
I0405 13:05:38.911542 18799 sgd_solver.cpp:105] Iteration 2076, lr = 0.0001
I0405 13:05:44.213377 18799 solver.cpp:218] Iteration 2088 (2.26338 iter/s, 5.3018s/12 iters), loss = 5.28487
I0405 13:05:44.213418 18799 solver.cpp:237]     Train net output #0: loss = 5.28487 (* 1 = 5.28487 loss)
I0405 13:05:44.213424 18799 sgd_solver.cpp:105] Iteration 2088, lr = 0.0001
I0405 13:05:49.330212 18799 solver.cpp:218] Iteration 2100 (2.34524 iter/s, 5.11675s/12 iters), loss = 5.28476
I0405 13:05:49.330251 18799 solver.cpp:237]     Train net output #0: loss = 5.28476 (* 1 = 5.28476 loss)
I0405 13:05:49.330256 18799 sgd_solver.cpp:105] Iteration 2100, lr = 0.0001
I0405 13:05:54.512162 18799 solver.cpp:218] Iteration 2112 (2.31577 iter/s, 5.18186s/12 iters), loss = 5.28458
I0405 13:05:54.512213 18799 solver.cpp:237]     Train net output #0: loss = 5.28458 (* 1 = 5.28458 loss)
I0405 13:05:54.512221 18799 sgd_solver.cpp:105] Iteration 2112, lr = 0.0001
I0405 13:05:59.479236 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:05:59.838304 18799 solver.cpp:218] Iteration 2124 (2.25308 iter/s, 5.32604s/12 iters), loss = 5.27156
I0405 13:05:59.838349 18799 solver.cpp:237]     Train net output #0: loss = 5.27156 (* 1 = 5.27156 loss)
I0405 13:05:59.838356 18799 sgd_solver.cpp:105] Iteration 2124, lr = 0.0001
I0405 13:06:05.071712 18799 solver.cpp:218] Iteration 2136 (2.293 iter/s, 5.23331s/12 iters), loss = 5.25607
I0405 13:06:05.071854 18799 solver.cpp:237]     Train net output #0: loss = 5.25607 (* 1 = 5.25607 loss)
I0405 13:06:05.071862 18799 sgd_solver.cpp:105] Iteration 2136, lr = 0.0001
I0405 13:06:07.132964 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel
I0405 13:06:10.215138 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate
I0405 13:06:12.521260 18799 solver.cpp:330] Iteration 2142, Testing net (#0)
I0405 13:06:12.521283 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:06:16.238312 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:06:17.096117 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:06:17.096150 18799 solver.cpp:397]     Test net output #1: loss = 5.28052 (* 1 = 5.28052 loss)
I0405 13:06:19.016647 18799 solver.cpp:218] Iteration 2148 (0.860542 iter/s, 13.9447s/12 iters), loss = 5.26529
I0405 13:06:19.016690 18799 solver.cpp:237]     Train net output #0: loss = 5.26529 (* 1 = 5.26529 loss)
I0405 13:06:19.016696 18799 sgd_solver.cpp:105] Iteration 2148, lr = 0.0001
I0405 13:06:24.270977 18799 solver.cpp:218] Iteration 2160 (2.28387 iter/s, 5.25424s/12 iters), loss = 5.2861
I0405 13:06:24.271018 18799 solver.cpp:237]     Train net output #0: loss = 5.2861 (* 1 = 5.2861 loss)
I0405 13:06:24.271023 18799 sgd_solver.cpp:105] Iteration 2160, lr = 0.0001
I0405 13:06:29.373175 18799 solver.cpp:218] Iteration 2172 (2.35197 iter/s, 5.10211s/12 iters), loss = 5.26316
I0405 13:06:29.373217 18799 solver.cpp:237]     Train net output #0: loss = 5.26316 (* 1 = 5.26316 loss)
I0405 13:06:29.373222 18799 sgd_solver.cpp:105] Iteration 2172, lr = 0.0001
I0405 13:06:34.861865 18799 solver.cpp:218] Iteration 2184 (2.18635 iter/s, 5.4886s/12 iters), loss = 5.2742
I0405 13:06:34.861903 18799 solver.cpp:237]     Train net output #0: loss = 5.2742 (* 1 = 5.2742 loss)
I0405 13:06:34.861909 18799 sgd_solver.cpp:105] Iteration 2184, lr = 0.0001
I0405 13:06:40.140877 18799 solver.cpp:218] Iteration 2196 (2.27319 iter/s, 5.27892s/12 iters), loss = 5.27939
I0405 13:06:40.141014 18799 solver.cpp:237]     Train net output #0: loss = 5.27939 (* 1 = 5.27939 loss)
I0405 13:06:40.141021 18799 sgd_solver.cpp:105] Iteration 2196, lr = 0.0001
I0405 13:06:45.527511 18799 solver.cpp:218] Iteration 2208 (2.22781 iter/s, 5.38645s/12 iters), loss = 5.27407
I0405 13:06:45.527557 18799 solver.cpp:237]     Train net output #0: loss = 5.27407 (* 1 = 5.27407 loss)
I0405 13:06:45.527565 18799 sgd_solver.cpp:105] Iteration 2208, lr = 0.0001
I0405 13:06:50.921716 18799 solver.cpp:218] Iteration 2220 (2.22465 iter/s, 5.39411s/12 iters), loss = 5.27047
I0405 13:06:50.921761 18799 solver.cpp:237]     Train net output #0: loss = 5.27047 (* 1 = 5.27047 loss)
I0405 13:06:50.921767 18799 sgd_solver.cpp:105] Iteration 2220, lr = 0.0001
I0405 13:06:52.842752 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:06:56.373720 18799 solver.cpp:218] Iteration 2232 (2.20106 iter/s, 5.45191s/12 iters), loss = 5.28713
I0405 13:06:56.373775 18799 solver.cpp:237]     Train net output #0: loss = 5.28713 (* 1 = 5.28713 loss)
I0405 13:06:56.373782 18799 sgd_solver.cpp:105] Iteration 2232, lr = 0.0001
I0405 13:07:01.388684 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel
I0405 13:07:04.434785 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate
I0405 13:07:07.211764 18799 solver.cpp:330] Iteration 2244, Testing net (#0)
I0405 13:07:07.211786 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:07:10.728363 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:07:11.689045 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:07:11.689078 18799 solver.cpp:397]     Test net output #1: loss = 5.2798 (* 1 = 5.2798 loss)
I0405 13:07:11.830889 18799 solver.cpp:218] Iteration 2244 (0.776347 iter/s, 15.457s/12 iters), loss = 5.268
I0405 13:07:11.830955 18799 solver.cpp:237]     Train net output #0: loss = 5.268 (* 1 = 5.268 loss)
I0405 13:07:11.830965 18799 sgd_solver.cpp:105] Iteration 2244, lr = 0.0001
I0405 13:07:16.248256 18799 solver.cpp:218] Iteration 2256 (2.71662 iter/s, 4.41726s/12 iters), loss = 5.27083
I0405 13:07:16.248298 18799 solver.cpp:237]     Train net output #0: loss = 5.27083 (* 1 = 5.27083 loss)
I0405 13:07:16.248304 18799 sgd_solver.cpp:105] Iteration 2256, lr = 0.0001
I0405 13:07:21.312924 18799 solver.cpp:218] Iteration 2268 (2.3694 iter/s, 5.06458s/12 iters), loss = 5.27136
I0405 13:07:21.312976 18799 solver.cpp:237]     Train net output #0: loss = 5.27136 (* 1 = 5.27136 loss)
I0405 13:07:21.312984 18799 sgd_solver.cpp:105] Iteration 2268, lr = 0.0001
I0405 13:07:26.610527 18799 solver.cpp:218] Iteration 2280 (2.26522 iter/s, 5.2975s/12 iters), loss = 5.27104
I0405 13:07:26.610584 18799 solver.cpp:237]     Train net output #0: loss = 5.27104 (* 1 = 5.27104 loss)
I0405 13:07:26.610592 18799 sgd_solver.cpp:105] Iteration 2280, lr = 0.0001
I0405 13:07:31.919540 18799 solver.cpp:218] Iteration 2292 (2.26035 iter/s, 5.30892s/12 iters), loss = 5.25383
I0405 13:07:31.919587 18799 solver.cpp:237]     Train net output #0: loss = 5.25383 (* 1 = 5.25383 loss)
I0405 13:07:31.919595 18799 sgd_solver.cpp:105] Iteration 2292, lr = 0.0001
I0405 13:07:37.279259 18799 solver.cpp:218] Iteration 2304 (2.23896 iter/s, 5.35962s/12 iters), loss = 5.27561
I0405 13:07:37.279309 18799 solver.cpp:237]     Train net output #0: loss = 5.27561 (* 1 = 5.27561 loss)
I0405 13:07:37.279315 18799 sgd_solver.cpp:105] Iteration 2304, lr = 0.0001
I0405 13:07:42.769420 18799 solver.cpp:218] Iteration 2316 (2.18577 iter/s, 5.49006s/12 iters), loss = 5.26382
I0405 13:07:42.769601 18799 solver.cpp:237]     Train net output #0: loss = 5.26382 (* 1 = 5.26382 loss)
I0405 13:07:42.769611 18799 sgd_solver.cpp:105] Iteration 2316, lr = 0.0001
I0405 13:07:46.967818 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:07:48.183732 18799 solver.cpp:218] Iteration 2328 (2.21644 iter/s, 5.41409s/12 iters), loss = 5.27438
I0405 13:07:48.183779 18799 solver.cpp:237]     Train net output #0: loss = 5.27438 (* 1 = 5.27438 loss)
I0405 13:07:48.183784 18799 sgd_solver.cpp:105] Iteration 2328, lr = 0.0001
I0405 13:07:53.484474 18799 solver.cpp:218] Iteration 2340 (2.26387 iter/s, 5.30065s/12 iters), loss = 5.2525
I0405 13:07:53.484517 18799 solver.cpp:237]     Train net output #0: loss = 5.2525 (* 1 = 5.2525 loss)
I0405 13:07:53.484524 18799 sgd_solver.cpp:105] Iteration 2340, lr = 0.0001
I0405 13:07:55.584161 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel
I0405 13:07:58.585165 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate
I0405 13:08:00.875622 18799 solver.cpp:330] Iteration 2346, Testing net (#0)
I0405 13:08:00.875643 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:08:04.260808 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:08:05.192502 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:08:05.192534 18799 solver.cpp:397]     Test net output #1: loss = 5.28003 (* 1 = 5.28003 loss)
I0405 13:08:07.193816 18799 solver.cpp:218] Iteration 2352 (0.875325 iter/s, 13.7092s/12 iters), loss = 5.28748
I0405 13:08:07.193881 18799 solver.cpp:237]     Train net output #0: loss = 5.28748 (* 1 = 5.28748 loss)
I0405 13:08:07.193889 18799 sgd_solver.cpp:105] Iteration 2352, lr = 0.0001
I0405 13:08:12.599454 18799 solver.cpp:218] Iteration 2364 (2.21995 iter/s, 5.40553s/12 iters), loss = 5.26594
I0405 13:08:12.599498 18799 solver.cpp:237]     Train net output #0: loss = 5.26594 (* 1 = 5.26594 loss)
I0405 13:08:12.599503 18799 sgd_solver.cpp:105] Iteration 2364, lr = 0.0001
I0405 13:08:18.048982 18799 solver.cpp:218] Iteration 2376 (2.20206 iter/s, 5.44943s/12 iters), loss = 5.28467
I0405 13:08:18.049104 18799 solver.cpp:237]     Train net output #0: loss = 5.28467 (* 1 = 5.28467 loss)
I0405 13:08:18.049113 18799 sgd_solver.cpp:105] Iteration 2376, lr = 0.0001
I0405 13:08:23.347960 18799 solver.cpp:218] Iteration 2388 (2.26466 iter/s, 5.29881s/12 iters), loss = 5.27916
I0405 13:08:23.348012 18799 solver.cpp:237]     Train net output #0: loss = 5.27916 (* 1 = 5.27916 loss)
I0405 13:08:23.348018 18799 sgd_solver.cpp:105] Iteration 2388, lr = 0.0001
I0405 13:08:28.660778 18799 solver.cpp:218] Iteration 2400 (2.25873 iter/s, 5.31271s/12 iters), loss = 5.27835
I0405 13:08:28.660838 18799 solver.cpp:237]     Train net output #0: loss = 5.27835 (* 1 = 5.27835 loss)
I0405 13:08:28.660847 18799 sgd_solver.cpp:105] Iteration 2400, lr = 0.0001
I0405 13:08:34.036989 18799 solver.cpp:218] Iteration 2412 (2.2321 iter/s, 5.3761s/12 iters), loss = 5.26072
I0405 13:08:34.037047 18799 solver.cpp:237]     Train net output #0: loss = 5.26072 (* 1 = 5.26072 loss)
I0405 13:08:34.037056 18799 sgd_solver.cpp:105] Iteration 2412, lr = 0.0001
I0405 13:08:39.354483 18799 solver.cpp:218] Iteration 2424 (2.25675 iter/s, 5.31739s/12 iters), loss = 5.28084
I0405 13:08:39.354537 18799 solver.cpp:237]     Train net output #0: loss = 5.28084 (* 1 = 5.28084 loss)
I0405 13:08:39.354547 18799 sgd_solver.cpp:105] Iteration 2424, lr = 0.0001
I0405 13:08:40.459473 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:08:44.681941 18799 solver.cpp:218] Iteration 2436 (2.25252 iter/s, 5.32736s/12 iters), loss = 5.28239
I0405 13:08:44.681982 18799 solver.cpp:237]     Train net output #0: loss = 5.28239 (* 1 = 5.28239 loss)
I0405 13:08:44.681988 18799 sgd_solver.cpp:105] Iteration 2436, lr = 0.0001
I0405 13:08:49.535338 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel
I0405 13:08:52.587541 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate
I0405 13:08:54.878201 18799 solver.cpp:330] Iteration 2448, Testing net (#0)
I0405 13:08:54.878222 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:08:58.585909 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:08:59.550320 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:08:59.550356 18799 solver.cpp:397]     Test net output #1: loss = 5.28028 (* 1 = 5.28028 loss)
I0405 13:08:59.689976 18799 solver.cpp:218] Iteration 2448 (0.799579 iter/s, 15.0079s/12 iters), loss = 5.28876
I0405 13:08:59.690033 18799 solver.cpp:237]     Train net output #0: loss = 5.28876 (* 1 = 5.28876 loss)
I0405 13:08:59.690040 18799 sgd_solver.cpp:105] Iteration 2448, lr = 0.0001
I0405 13:09:04.060089 18799 solver.cpp:218] Iteration 2460 (2.74599 iter/s, 4.37002s/12 iters), loss = 5.26806
I0405 13:09:04.060132 18799 solver.cpp:237]     Train net output #0: loss = 5.26806 (* 1 = 5.26806 loss)
I0405 13:09:04.060137 18799 sgd_solver.cpp:105] Iteration 2460, lr = 0.0001
I0405 13:09:09.529454 18799 solver.cpp:218] Iteration 2472 (2.19408 iter/s, 5.46927s/12 iters), loss = 5.27004
I0405 13:09:09.529502 18799 solver.cpp:237]     Train net output #0: loss = 5.27004 (* 1 = 5.27004 loss)
I0405 13:09:09.529511 18799 sgd_solver.cpp:105] Iteration 2472, lr = 0.0001
I0405 13:09:14.812942 18799 solver.cpp:218] Iteration 2484 (2.27127 iter/s, 5.2834s/12 iters), loss = 5.28912
I0405 13:09:14.812978 18799 solver.cpp:237]     Train net output #0: loss = 5.28912 (* 1 = 5.28912 loss)
I0405 13:09:14.812983 18799 sgd_solver.cpp:105] Iteration 2484, lr = 0.0001
I0405 13:09:20.278733 18799 solver.cpp:218] Iteration 2496 (2.19551 iter/s, 5.46571s/12 iters), loss = 5.2761
I0405 13:09:20.278843 18799 solver.cpp:237]     Train net output #0: loss = 5.2761 (* 1 = 5.2761 loss)
I0405 13:09:20.278851 18799 sgd_solver.cpp:105] Iteration 2496, lr = 0.0001
I0405 13:09:25.483088 18799 solver.cpp:218] Iteration 2508 (2.30583 iter/s, 5.2042s/12 iters), loss = 5.27493
I0405 13:09:25.483141 18799 solver.cpp:237]     Train net output #0: loss = 5.27493 (* 1 = 5.27493 loss)
I0405 13:09:25.483152 18799 sgd_solver.cpp:105] Iteration 2508, lr = 0.0001
I0405 13:09:30.728965 18799 solver.cpp:218] Iteration 2520 (2.28755 iter/s, 5.24578s/12 iters), loss = 5.29713
I0405 13:09:30.729007 18799 solver.cpp:237]     Train net output #0: loss = 5.29713 (* 1 = 5.29713 loss)
I0405 13:09:30.729013 18799 sgd_solver.cpp:105] Iteration 2520, lr = 0.0001
I0405 13:09:34.187783 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:09:36.199416 18799 solver.cpp:218] Iteration 2532 (2.19364 iter/s, 5.47036s/12 iters), loss = 5.24609
I0405 13:09:36.199467 18799 solver.cpp:237]     Train net output #0: loss = 5.24609 (* 1 = 5.24609 loss)
I0405 13:09:36.199473 18799 sgd_solver.cpp:105] Iteration 2532, lr = 0.0001
I0405 13:09:41.585511 18799 solver.cpp:218] Iteration 2544 (2.228 iter/s, 5.386s/12 iters), loss = 5.26424
I0405 13:09:41.585556 18799 solver.cpp:237]     Train net output #0: loss = 5.26424 (* 1 = 5.26424 loss)
I0405 13:09:41.585561 18799 sgd_solver.cpp:105] Iteration 2544, lr = 0.0001
I0405 13:09:43.787549 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel
I0405 13:09:46.762853 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate
I0405 13:09:49.074641 18799 solver.cpp:330] Iteration 2550, Testing net (#0)
I0405 13:09:49.074661 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:09:52.511415 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:09:53.547204 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:09:53.547245 18799 solver.cpp:397]     Test net output #1: loss = 5.2805 (* 1 = 5.2805 loss)
I0405 13:09:55.631703 18799 solver.cpp:218] Iteration 2556 (0.854333 iter/s, 14.0461s/12 iters), loss = 5.25548
I0405 13:09:55.638054 18799 solver.cpp:237]     Train net output #0: loss = 5.25548 (* 1 = 5.25548 loss)
I0405 13:09:55.638069 18799 sgd_solver.cpp:105] Iteration 2556, lr = 0.0001
I0405 13:10:00.828265 18799 solver.cpp:218] Iteration 2568 (2.31206 iter/s, 5.19018s/12 iters), loss = 5.25286
I0405 13:10:00.828302 18799 solver.cpp:237]     Train net output #0: loss = 5.25286 (* 1 = 5.25286 loss)
I0405 13:10:00.828308 18799 sgd_solver.cpp:105] Iteration 2568, lr = 0.0001
I0405 13:10:06.131294 18799 solver.cpp:218] Iteration 2580 (2.26289 iter/s, 5.30295s/12 iters), loss = 5.28245
I0405 13:10:06.131331 18799 solver.cpp:237]     Train net output #0: loss = 5.28245 (* 1 = 5.28245 loss)
I0405 13:10:06.131337 18799 sgd_solver.cpp:105] Iteration 2580, lr = 0.0001
I0405 13:10:11.358397 18799 solver.cpp:218] Iteration 2592 (2.29577 iter/s, 5.22701s/12 iters), loss = 5.25884
I0405 13:10:11.358449 18799 solver.cpp:237]     Train net output #0: loss = 5.25884 (* 1 = 5.25884 loss)
I0405 13:10:11.358459 18799 sgd_solver.cpp:105] Iteration 2592, lr = 0.0001
I0405 13:10:16.646873 18799 solver.cpp:218] Iteration 2604 (2.26913 iter/s, 5.28838s/12 iters), loss = 5.25307
I0405 13:10:16.646916 18799 solver.cpp:237]     Train net output #0: loss = 5.25307 (* 1 = 5.25307 loss)
I0405 13:10:16.646924 18799 sgd_solver.cpp:105] Iteration 2604, lr = 0.0001
I0405 13:10:21.902595 18799 solver.cpp:218] Iteration 2616 (2.28327 iter/s, 5.25563s/12 iters), loss = 5.28521
I0405 13:10:21.902640 18799 solver.cpp:237]     Train net output #0: loss = 5.28521 (* 1 = 5.28521 loss)
I0405 13:10:21.902647 18799 sgd_solver.cpp:105] Iteration 2616, lr = 0.0001
I0405 13:10:27.294050 18799 solver.cpp:218] Iteration 2628 (2.22578 iter/s, 5.39136s/12 iters), loss = 5.28501
I0405 13:10:27.294191 18799 solver.cpp:237]     Train net output #0: loss = 5.28501 (* 1 = 5.28501 loss)
I0405 13:10:27.294198 18799 sgd_solver.cpp:105] Iteration 2628, lr = 0.0001
I0405 13:10:27.799687 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:10:32.742913 18799 solver.cpp:218] Iteration 2640 (2.20237 iter/s, 5.44867s/12 iters), loss = 5.28688
I0405 13:10:32.742967 18799 solver.cpp:237]     Train net output #0: loss = 5.28688 (* 1 = 5.28688 loss)
I0405 13:10:32.742976 18799 sgd_solver.cpp:105] Iteration 2640, lr = 0.0001
I0405 13:10:37.594841 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel
I0405 13:10:40.588821 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate
I0405 13:10:43.406718 18799 solver.cpp:330] Iteration 2652, Testing net (#0)
I0405 13:10:43.406738 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:10:46.648658 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:10:47.685638 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:10:47.685673 18799 solver.cpp:397]     Test net output #1: loss = 5.28028 (* 1 = 5.28028 loss)
I0405 13:10:47.827483 18799 solver.cpp:218] Iteration 2652 (0.795523 iter/s, 15.0844s/12 iters), loss = 5.28669
I0405 13:10:47.827535 18799 solver.cpp:237]     Train net output #0: loss = 5.28669 (* 1 = 5.28669 loss)
I0405 13:10:47.827543 18799 sgd_solver.cpp:105] Iteration 2652, lr = 0.0001
I0405 13:10:52.376689 18799 solver.cpp:218] Iteration 2664 (2.63788 iter/s, 4.54912s/12 iters), loss = 5.28289
I0405 13:10:52.376734 18799 solver.cpp:237]     Train net output #0: loss = 5.28289 (* 1 = 5.28289 loss)
I0405 13:10:52.376742 18799 sgd_solver.cpp:105] Iteration 2664, lr = 0.0001
I0405 13:10:57.724560 18799 solver.cpp:218] Iteration 2676 (2.24392 iter/s, 5.34778s/12 iters), loss = 5.27011
I0405 13:10:57.724653 18799 solver.cpp:237]     Train net output #0: loss = 5.27011 (* 1 = 5.27011 loss)
I0405 13:10:57.724659 18799 sgd_solver.cpp:105] Iteration 2676, lr = 0.0001
I0405 13:11:03.047410 18799 solver.cpp:218] Iteration 2688 (2.25449 iter/s, 5.32271s/12 iters), loss = 5.277
I0405 13:11:03.047458 18799 solver.cpp:237]     Train net output #0: loss = 5.277 (* 1 = 5.277 loss)
I0405 13:11:03.047464 18799 sgd_solver.cpp:105] Iteration 2688, lr = 0.0001
I0405 13:11:08.201229 18799 solver.cpp:218] Iteration 2700 (2.32841 iter/s, 5.15372s/12 iters), loss = 5.28239
I0405 13:11:08.201514 18799 solver.cpp:237]     Train net output #0: loss = 5.28239 (* 1 = 5.28239 loss)
I0405 13:11:08.201522 18799 sgd_solver.cpp:105] Iteration 2700, lr = 0.0001
I0405 13:11:13.383677 18799 solver.cpp:218] Iteration 2712 (2.31566 iter/s, 5.18211s/12 iters), loss = 5.27826
I0405 13:11:13.383728 18799 solver.cpp:237]     Train net output #0: loss = 5.27826 (* 1 = 5.27826 loss)
I0405 13:11:13.383739 18799 sgd_solver.cpp:105] Iteration 2712, lr = 0.0001
I0405 13:11:18.605733 18799 solver.cpp:218] Iteration 2724 (2.29799 iter/s, 5.22196s/12 iters), loss = 5.27116
I0405 13:11:18.605790 18799 solver.cpp:237]     Train net output #0: loss = 5.27116 (* 1 = 5.27116 loss)
I0405 13:11:18.605799 18799 sgd_solver.cpp:105] Iteration 2724, lr = 0.0001
I0405 13:11:21.316390 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:11:23.946410 18799 solver.cpp:218] Iteration 2736 (2.24695 iter/s, 5.34058s/12 iters), loss = 5.2936
I0405 13:11:23.946450 18799 solver.cpp:237]     Train net output #0: loss = 5.2936 (* 1 = 5.2936 loss)
I0405 13:11:23.946455 18799 sgd_solver.cpp:105] Iteration 2736, lr = 0.0001
I0405 13:11:29.321584 18799 solver.cpp:218] Iteration 2748 (2.23252 iter/s, 5.37508s/12 iters), loss = 5.27347
I0405 13:11:29.321727 18799 solver.cpp:237]     Train net output #0: loss = 5.27347 (* 1 = 5.27347 loss)
I0405 13:11:29.321734 18799 sgd_solver.cpp:105] Iteration 2748, lr = 0.0001
I0405 13:11:31.338028 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel
I0405 13:11:34.373721 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate
I0405 13:11:36.774137 18799 solver.cpp:330] Iteration 2754, Testing net (#0)
I0405 13:11:36.774159 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:11:39.782917 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:11:40.014075 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:11:41.151703 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:11:41.151736 18799 solver.cpp:397]     Test net output #1: loss = 5.28026 (* 1 = 5.28026 loss)
I0405 13:11:42.979346 18799 solver.cpp:218] Iteration 2760 (0.878636 iter/s, 13.6575s/12 iters), loss = 5.26099
I0405 13:11:42.979378 18799 solver.cpp:237]     Train net output #0: loss = 5.26099 (* 1 = 5.26099 loss)
I0405 13:11:42.979384 18799 sgd_solver.cpp:105] Iteration 2760, lr = 0.0001
I0405 13:11:48.206319 18799 solver.cpp:218] Iteration 2772 (2.29582 iter/s, 5.22689s/12 iters), loss = 5.28626
I0405 13:11:48.206368 18799 solver.cpp:237]     Train net output #0: loss = 5.28626 (* 1 = 5.28626 loss)
I0405 13:11:48.206375 18799 sgd_solver.cpp:105] Iteration 2772, lr = 0.0001
I0405 13:11:53.428038 18799 solver.cpp:218] Iteration 2784 (2.29814 iter/s, 5.22162s/12 iters), loss = 5.2773
I0405 13:11:53.428078 18799 solver.cpp:237]     Train net output #0: loss = 5.2773 (* 1 = 5.2773 loss)
I0405 13:11:53.428084 18799 sgd_solver.cpp:105] Iteration 2784, lr = 0.0001
I0405 13:11:58.716892 18799 solver.cpp:218] Iteration 2796 (2.26896 iter/s, 5.28876s/12 iters), loss = 5.27611
I0405 13:11:58.716931 18799 solver.cpp:237]     Train net output #0: loss = 5.27611 (* 1 = 5.27611 loss)
I0405 13:11:58.716938 18799 sgd_solver.cpp:105] Iteration 2796, lr = 0.0001
I0405 13:12:04.045318 18799 solver.cpp:218] Iteration 2808 (2.25211 iter/s, 5.32834s/12 iters), loss = 5.28967
I0405 13:12:04.045434 18799 solver.cpp:237]     Train net output #0: loss = 5.28967 (* 1 = 5.28967 loss)
I0405 13:12:04.045444 18799 sgd_solver.cpp:105] Iteration 2808, lr = 0.0001
I0405 13:12:09.411058 18799 solver.cpp:218] Iteration 2820 (2.23648 iter/s, 5.36557s/12 iters), loss = 5.26827
I0405 13:12:09.411119 18799 solver.cpp:237]     Train net output #0: loss = 5.26827 (* 1 = 5.26827 loss)
I0405 13:12:09.411128 18799 sgd_solver.cpp:105] Iteration 2820, lr = 0.0001
I0405 13:12:14.334316 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:12:14.664505 18799 solver.cpp:218] Iteration 2832 (2.28426 iter/s, 5.25334s/12 iters), loss = 5.2753
I0405 13:12:14.664561 18799 solver.cpp:237]     Train net output #0: loss = 5.2753 (* 1 = 5.2753 loss)
I0405 13:12:14.664568 18799 sgd_solver.cpp:105] Iteration 2832, lr = 0.0001
I0405 13:12:19.670192 18799 solver.cpp:218] Iteration 2844 (2.39732 iter/s, 5.00559s/12 iters), loss = 5.2595
I0405 13:12:19.670233 18799 solver.cpp:237]     Train net output #0: loss = 5.2595 (* 1 = 5.2595 loss)
I0405 13:12:19.670239 18799 sgd_solver.cpp:105] Iteration 2844, lr = 0.0001
I0405 13:12:24.202806 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel
I0405 13:12:27.317628 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate
I0405 13:12:29.631572 18799 solver.cpp:330] Iteration 2856, Testing net (#0)
I0405 13:12:29.631593 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:12:32.825718 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:12:33.946830 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:12:33.946863 18799 solver.cpp:397]     Test net output #1: loss = 5.27987 (* 1 = 5.27987 loss)
I0405 13:12:34.088716 18799 solver.cpp:218] Iteration 2856 (0.832271 iter/s, 14.4184s/12 iters), loss = 5.27092
I0405 13:12:34.088860 18799 solver.cpp:237]     Train net output #0: loss = 5.27092 (* 1 = 5.27092 loss)
I0405 13:12:34.088867 18799 sgd_solver.cpp:105] Iteration 2856, lr = 0.0001
I0405 13:12:38.570196 18799 solver.cpp:218] Iteration 2868 (2.6778 iter/s, 4.48129s/12 iters), loss = 5.29245
I0405 13:12:38.570237 18799 solver.cpp:237]     Train net output #0: loss = 5.29245 (* 1 = 5.29245 loss)
I0405 13:12:38.570245 18799 sgd_solver.cpp:105] Iteration 2868, lr = 0.0001
I0405 13:12:43.841497 18799 solver.cpp:218] Iteration 2880 (2.27652 iter/s, 5.27121s/12 iters), loss = 5.27535
I0405 13:12:43.841540 18799 solver.cpp:237]     Train net output #0: loss = 5.27535 (* 1 = 5.27535 loss)
I0405 13:12:43.841547 18799 sgd_solver.cpp:105] Iteration 2880, lr = 0.0001
I0405 13:12:49.010891 18799 solver.cpp:218] Iteration 2892 (2.3214 iter/s, 5.1693s/12 iters), loss = 5.26864
I0405 13:12:49.010947 18799 solver.cpp:237]     Train net output #0: loss = 5.26864 (* 1 = 5.26864 loss)
I0405 13:12:49.010954 18799 sgd_solver.cpp:105] Iteration 2892, lr = 0.0001
I0405 13:12:54.363670 18799 solver.cpp:218] Iteration 2904 (2.24187 iter/s, 5.35267s/12 iters), loss = 5.27655
I0405 13:12:54.363727 18799 solver.cpp:237]     Train net output #0: loss = 5.27655 (* 1 = 5.27655 loss)
I0405 13:12:54.363736 18799 sgd_solver.cpp:105] Iteration 2904, lr = 0.0001
I0405 13:12:59.552037 18799 solver.cpp:218] Iteration 2916 (2.31291 iter/s, 5.18826s/12 iters), loss = 5.27731
I0405 13:12:59.552081 18799 solver.cpp:237]     Train net output #0: loss = 5.27731 (* 1 = 5.27731 loss)
I0405 13:12:59.552088 18799 sgd_solver.cpp:105] Iteration 2916, lr = 0.0001
I0405 13:13:04.887799 18799 solver.cpp:218] Iteration 2928 (2.24901 iter/s, 5.33568s/12 iters), loss = 5.26194
I0405 13:13:04.887899 18799 solver.cpp:237]     Train net output #0: loss = 5.26194 (* 1 = 5.26194 loss)
I0405 13:13:04.887905 18799 sgd_solver.cpp:105] Iteration 2928, lr = 0.0001
I0405 13:13:06.724900 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:13:10.147697 18799 solver.cpp:218] Iteration 2940 (2.28148 iter/s, 5.25975s/12 iters), loss = 5.29249
I0405 13:13:10.147743 18799 solver.cpp:237]     Train net output #0: loss = 5.29249 (* 1 = 5.29249 loss)
I0405 13:13:10.147748 18799 sgd_solver.cpp:105] Iteration 2940, lr = 0.0001
I0405 13:13:15.319326 18799 solver.cpp:218] Iteration 2952 (2.32039 iter/s, 5.17154s/12 iters), loss = 5.26916
I0405 13:13:15.319384 18799 solver.cpp:237]     Train net output #0: loss = 5.26916 (* 1 = 5.26916 loss)
I0405 13:13:15.319393 18799 sgd_solver.cpp:105] Iteration 2952, lr = 0.0001
I0405 13:13:17.476351 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel
I0405 13:13:20.498564 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate
I0405 13:13:23.329309 18799 solver.cpp:330] Iteration 2958, Testing net (#0)
I0405 13:13:23.329330 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:13:26.639930 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:13:27.837875 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:13:27.837910 18799 solver.cpp:397]     Test net output #1: loss = 5.27961 (* 1 = 5.27961 loss)
I0405 13:13:29.728317 18799 solver.cpp:218] Iteration 2964 (0.832822 iter/s, 14.4088s/12 iters), loss = 5.25231
I0405 13:13:29.728372 18799 solver.cpp:237]     Train net output #0: loss = 5.25231 (* 1 = 5.25231 loss)
I0405 13:13:29.728380 18799 sgd_solver.cpp:105] Iteration 2964, lr = 0.0001
I0405 13:13:35.105597 18799 solver.cpp:218] Iteration 2976 (2.23166 iter/s, 5.37717s/12 iters), loss = 5.2655
I0405 13:13:35.105756 18799 solver.cpp:237]     Train net output #0: loss = 5.2655 (* 1 = 5.2655 loss)
I0405 13:13:35.105765 18799 sgd_solver.cpp:105] Iteration 2976, lr = 0.0001
I0405 13:13:40.166740 18799 solver.cpp:218] Iteration 2988 (2.3711 iter/s, 5.06095s/12 iters), loss = 5.26561
I0405 13:13:40.166775 18799 solver.cpp:237]     Train net output #0: loss = 5.26561 (* 1 = 5.26561 loss)
I0405 13:13:40.166781 18799 sgd_solver.cpp:105] Iteration 2988, lr = 0.0001
I0405 13:13:45.297731 18799 solver.cpp:218] Iteration 3000 (2.33877 iter/s, 5.13091s/12 iters), loss = 5.25398
I0405 13:13:45.297775 18799 solver.cpp:237]     Train net output #0: loss = 5.25398 (* 1 = 5.25398 loss)
I0405 13:13:45.297780 18799 sgd_solver.cpp:105] Iteration 3000, lr = 0.0001
I0405 13:13:50.554092 18799 solver.cpp:218] Iteration 3012 (2.28298 iter/s, 5.25628s/12 iters), loss = 5.28582
I0405 13:13:50.554122 18799 solver.cpp:237]     Train net output #0: loss = 5.28582 (* 1 = 5.28582 loss)
I0405 13:13:50.554127 18799 sgd_solver.cpp:105] Iteration 3012, lr = 0.0001
I0405 13:13:55.891839 18799 solver.cpp:218] Iteration 3024 (2.24818 iter/s, 5.33766s/12 iters), loss = 5.26273
I0405 13:13:55.891885 18799 solver.cpp:237]     Train net output #0: loss = 5.26273 (* 1 = 5.26273 loss)
I0405 13:13:55.891891 18799 sgd_solver.cpp:105] Iteration 3024, lr = 0.0001
I0405 13:14:00.163404 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:14:01.223121 18799 solver.cpp:218] Iteration 3036 (2.2509 iter/s, 5.33119s/12 iters), loss = 5.27112
I0405 13:14:01.223160 18799 solver.cpp:237]     Train net output #0: loss = 5.27112 (* 1 = 5.27112 loss)
I0405 13:14:01.223166 18799 sgd_solver.cpp:105] Iteration 3036, lr = 0.0001
I0405 13:14:06.498591 18799 solver.cpp:218] Iteration 3048 (2.27472 iter/s, 5.27539s/12 iters), loss = 5.25576
I0405 13:14:06.498694 18799 solver.cpp:237]     Train net output #0: loss = 5.25576 (* 1 = 5.25576 loss)
I0405 13:14:06.498700 18799 sgd_solver.cpp:105] Iteration 3048, lr = 0.0001
I0405 13:14:11.356976 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel
I0405 13:14:14.342957 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate
I0405 13:14:16.633327 18799 solver.cpp:330] Iteration 3060, Testing net (#0)
I0405 13:14:16.633345 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:14:19.794421 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:14:21.037657 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:14:21.037693 18799 solver.cpp:397]     Test net output #1: loss = 5.27999 (* 1 = 5.27999 loss)
I0405 13:14:21.178335 18799 solver.cpp:218] Iteration 3060 (0.817464 iter/s, 14.6795s/12 iters), loss = 5.27504
I0405 13:14:21.179956 18799 solver.cpp:237]     Train net output #0: loss = 5.27504 (* 1 = 5.27504 loss)
I0405 13:14:21.179973 18799 sgd_solver.cpp:105] Iteration 3060, lr = 0.0001
I0405 13:14:25.438561 18799 solver.cpp:218] Iteration 3072 (2.81784 iter/s, 4.25858s/12 iters), loss = 5.27068
I0405 13:14:25.438601 18799 solver.cpp:237]     Train net output #0: loss = 5.27068 (* 1 = 5.27068 loss)
I0405 13:14:25.438607 18799 sgd_solver.cpp:105] Iteration 3072, lr = 0.0001
I0405 13:14:30.691370 18799 solver.cpp:218] Iteration 3084 (2.28453 iter/s, 5.25272s/12 iters), loss = 5.27037
I0405 13:14:30.691414 18799 solver.cpp:237]     Train net output #0: loss = 5.27037 (* 1 = 5.27037 loss)
I0405 13:14:30.691419 18799 sgd_solver.cpp:105] Iteration 3084, lr = 0.0001
I0405 13:14:36.107429 18799 solver.cpp:218] Iteration 3096 (2.21567 iter/s, 5.41597s/12 iters), loss = 5.27931
I0405 13:14:36.107486 18799 solver.cpp:237]     Train net output #0: loss = 5.27931 (* 1 = 5.27931 loss)
I0405 13:14:36.107494 18799 sgd_solver.cpp:105] Iteration 3096, lr = 0.0001
I0405 13:14:41.480718 18799 solver.cpp:218] Iteration 3108 (2.23331 iter/s, 5.37319s/12 iters), loss = 5.28184
I0405 13:14:41.480866 18799 solver.cpp:237]     Train net output #0: loss = 5.28184 (* 1 = 5.28184 loss)
I0405 13:14:41.480875 18799 sgd_solver.cpp:105] Iteration 3108, lr = 0.0001
I0405 13:14:46.923547 18799 solver.cpp:218] Iteration 3120 (2.20481 iter/s, 5.44264s/12 iters), loss = 5.26362
I0405 13:14:46.923586 18799 solver.cpp:237]     Train net output #0: loss = 5.26362 (* 1 = 5.26362 loss)
I0405 13:14:46.923591 18799 sgd_solver.cpp:105] Iteration 3120, lr = 0.0001
I0405 13:14:52.397307 18799 solver.cpp:218] Iteration 3132 (2.19231 iter/s, 5.47368s/12 iters), loss = 5.26988
I0405 13:14:52.397346 18799 solver.cpp:237]     Train net output #0: loss = 5.26988 (* 1 = 5.26988 loss)
I0405 13:14:52.397352 18799 sgd_solver.cpp:105] Iteration 3132, lr = 0.0001
I0405 13:14:53.475061 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:14:57.841928 18799 solver.cpp:218] Iteration 3144 (2.20405 iter/s, 5.44453s/12 iters), loss = 5.27995
I0405 13:14:57.841974 18799 solver.cpp:237]     Train net output #0: loss = 5.27995 (* 1 = 5.27995 loss)
I0405 13:14:57.841980 18799 sgd_solver.cpp:105] Iteration 3144, lr = 0.0001
I0405 13:15:03.170965 18799 solver.cpp:218] Iteration 3156 (2.25186 iter/s, 5.32894s/12 iters), loss = 5.27642
I0405 13:15:03.171020 18799 solver.cpp:237]     Train net output #0: loss = 5.27642 (* 1 = 5.27642 loss)
I0405 13:15:03.171032 18799 sgd_solver.cpp:105] Iteration 3156, lr = 0.0001
I0405 13:15:05.302450 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel
I0405 13:15:08.833976 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate
I0405 13:15:11.129093 18799 solver.cpp:330] Iteration 3162, Testing net (#0)
I0405 13:15:11.129114 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:15:14.330446 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:15:15.647765 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:15:15.647809 18799 solver.cpp:397]     Test net output #1: loss = 5.27944 (* 1 = 5.27944 loss)
I0405 13:15:17.629896 18799 solver.cpp:218] Iteration 3168 (0.829946 iter/s, 14.4588s/12 iters), loss = 5.26161
I0405 13:15:17.629946 18799 solver.cpp:237]     Train net output #0: loss = 5.26161 (* 1 = 5.26161 loss)
I0405 13:15:17.629951 18799 sgd_solver.cpp:105] Iteration 3168, lr = 0.0001
I0405 13:15:22.948921 18799 solver.cpp:218] Iteration 3180 (2.25676 iter/s, 5.31736s/12 iters), loss = 5.2556
I0405 13:15:22.948959 18799 solver.cpp:237]     Train net output #0: loss = 5.2556 (* 1 = 5.2556 loss)
I0405 13:15:22.948972 18799 sgd_solver.cpp:105] Iteration 3180, lr = 0.0001
I0405 13:15:28.259781 18799 solver.cpp:218] Iteration 3192 (2.25956 iter/s, 5.31077s/12 iters), loss = 5.28084
I0405 13:15:28.259831 18799 solver.cpp:237]     Train net output #0: loss = 5.28084 (* 1 = 5.28084 loss)
I0405 13:15:28.259840 18799 sgd_solver.cpp:105] Iteration 3192, lr = 0.0001
I0405 13:15:33.670086 18799 solver.cpp:218] Iteration 3204 (2.21803 iter/s, 5.41021s/12 iters), loss = 5.25289
I0405 13:15:33.670125 18799 solver.cpp:237]     Train net output #0: loss = 5.25289 (* 1 = 5.25289 loss)
I0405 13:15:33.670130 18799 sgd_solver.cpp:105] Iteration 3204, lr = 0.0001
I0405 13:15:39.040558 18799 solver.cpp:218] Iteration 3216 (2.23448 iter/s, 5.37038s/12 iters), loss = 5.26112
I0405 13:15:39.040606 18799 solver.cpp:237]     Train net output #0: loss = 5.26112 (* 1 = 5.26112 loss)
I0405 13:15:39.040611 18799 sgd_solver.cpp:105] Iteration 3216, lr = 0.0001
I0405 13:15:44.431790 18799 solver.cpp:218] Iteration 3228 (2.22588 iter/s, 5.39113s/12 iters), loss = 5.28193
I0405 13:15:44.431958 18799 solver.cpp:237]     Train net output #0: loss = 5.28193 (* 1 = 5.28193 loss)
I0405 13:15:44.431968 18799 sgd_solver.cpp:105] Iteration 3228, lr = 0.0001
I0405 13:15:47.751801 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:15:49.660306 18799 solver.cpp:218] Iteration 3240 (2.2952 iter/s, 5.22831s/12 iters), loss = 5.25583
I0405 13:15:49.660344 18799 solver.cpp:237]     Train net output #0: loss = 5.25583 (* 1 = 5.25583 loss)
I0405 13:15:49.660351 18799 sgd_solver.cpp:105] Iteration 3240, lr = 0.0001
I0405 13:15:55.035799 18799 solver.cpp:218] Iteration 3252 (2.23239 iter/s, 5.37541s/12 iters), loss = 5.2619
I0405 13:15:55.035861 18799 solver.cpp:237]     Train net output #0: loss = 5.2619 (* 1 = 5.2619 loss)
I0405 13:15:55.035871 18799 sgd_solver.cpp:105] Iteration 3252, lr = 0.0001
I0405 13:15:59.883342 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel
I0405 13:16:03.012809 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate
I0405 13:16:05.350994 18799 solver.cpp:330] Iteration 3264, Testing net (#0)
I0405 13:16:05.351013 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:16:08.591178 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:16:09.891010 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:16:09.891036 18799 solver.cpp:397]     Test net output #1: loss = 5.27984 (* 1 = 5.27984 loss)
I0405 13:16:10.031293 18799 solver.cpp:218] Iteration 3264 (0.800249 iter/s, 14.9953s/12 iters), loss = 5.25423
I0405 13:16:10.031355 18799 solver.cpp:237]     Train net output #0: loss = 5.25423 (* 1 = 5.25423 loss)
I0405 13:16:10.031363 18799 sgd_solver.cpp:105] Iteration 3264, lr = 0.0001
I0405 13:16:14.461441 18799 solver.cpp:218] Iteration 3276 (2.70878 iter/s, 4.43004s/12 iters), loss = 5.27078
I0405 13:16:14.461575 18799 solver.cpp:237]     Train net output #0: loss = 5.27078 (* 1 = 5.27078 loss)
I0405 13:16:14.461583 18799 sgd_solver.cpp:105] Iteration 3276, lr = 0.0001
I0405 13:16:19.943766 18799 solver.cpp:218] Iteration 3288 (2.18893 iter/s, 5.48214s/12 iters), loss = 5.26731
I0405 13:16:19.943828 18799 solver.cpp:237]     Train net output #0: loss = 5.26731 (* 1 = 5.26731 loss)
I0405 13:16:19.943837 18799 sgd_solver.cpp:105] Iteration 3288, lr = 0.0001
I0405 13:16:25.232692 18799 solver.cpp:218] Iteration 3300 (2.26894 iter/s, 5.28882s/12 iters), loss = 5.26997
I0405 13:16:25.232735 18799 solver.cpp:237]     Train net output #0: loss = 5.26997 (* 1 = 5.26997 loss)
I0405 13:16:25.232740 18799 sgd_solver.cpp:105] Iteration 3300, lr = 0.0001
I0405 13:16:30.348872 18799 solver.cpp:218] Iteration 3312 (2.34554 iter/s, 5.11609s/12 iters), loss = 5.26378
I0405 13:16:30.348920 18799 solver.cpp:237]     Train net output #0: loss = 5.26378 (* 1 = 5.26378 loss)
I0405 13:16:30.348927 18799 sgd_solver.cpp:105] Iteration 3312, lr = 0.0001
I0405 13:16:35.665593 18799 solver.cpp:218] Iteration 3324 (2.25707 iter/s, 5.31662s/12 iters), loss = 5.26684
I0405 13:16:35.665643 18799 solver.cpp:237]     Train net output #0: loss = 5.26684 (* 1 = 5.26684 loss)
I0405 13:16:35.665648 18799 sgd_solver.cpp:105] Iteration 3324, lr = 0.0001
I0405 13:16:41.005537 18799 solver.cpp:218] Iteration 3336 (2.24726 iter/s, 5.33985s/12 iters), loss = 5.25586
I0405 13:16:41.005584 18799 solver.cpp:237]     Train net output #0: loss = 5.25586 (* 1 = 5.25586 loss)
I0405 13:16:41.005590 18799 sgd_solver.cpp:105] Iteration 3336, lr = 0.0001
I0405 13:16:41.453531 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:16:46.313716 18799 solver.cpp:218] Iteration 3348 (2.2607 iter/s, 5.30809s/12 iters), loss = 5.27815
I0405 13:16:46.313832 18799 solver.cpp:237]     Train net output #0: loss = 5.27815 (* 1 = 5.27815 loss)
I0405 13:16:46.313839 18799 sgd_solver.cpp:105] Iteration 3348, lr = 0.0001
I0405 13:16:51.463104 18799 solver.cpp:218] Iteration 3360 (2.33045 iter/s, 5.14923s/12 iters), loss = 5.27742
I0405 13:16:51.463147 18799 solver.cpp:237]     Train net output #0: loss = 5.27742 (* 1 = 5.27742 loss)
I0405 13:16:51.463153 18799 sgd_solver.cpp:105] Iteration 3360, lr = 0.0001
I0405 13:16:53.655807 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel
I0405 13:16:56.611232 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate
I0405 13:16:58.931774 18799 solver.cpp:330] Iteration 3366, Testing net (#0)
I0405 13:16:58.931797 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:17:02.094496 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:03.443444 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:17:03.443471 18799 solver.cpp:397]     Test net output #1: loss = 5.27988 (* 1 = 5.27988 loss)
I0405 13:17:05.617681 18799 solver.cpp:218] Iteration 3372 (0.847791 iter/s, 14.1544s/12 iters), loss = 5.26183
I0405 13:17:05.617727 18799 solver.cpp:237]     Train net output #0: loss = 5.26183 (* 1 = 5.26183 loss)
I0405 13:17:05.617733 18799 sgd_solver.cpp:105] Iteration 3372, lr = 0.0001
I0405 13:17:10.953606 18799 solver.cpp:218] Iteration 3384 (2.24895 iter/s, 5.33583s/12 iters), loss = 5.27545
I0405 13:17:10.953649 18799 solver.cpp:237]     Train net output #0: loss = 5.27545 (* 1 = 5.27545 loss)
I0405 13:17:10.953655 18799 sgd_solver.cpp:105] Iteration 3384, lr = 0.0001
I0405 13:17:15.971446 18799 solver.cpp:218] Iteration 3396 (2.39151 iter/s, 5.01775s/12 iters), loss = 5.25206
I0405 13:17:15.971489 18799 solver.cpp:237]     Train net output #0: loss = 5.25206 (* 1 = 5.25206 loss)
I0405 13:17:15.971494 18799 sgd_solver.cpp:105] Iteration 3396, lr = 0.0001
I0405 13:17:21.235791 18799 solver.cpp:218] Iteration 3408 (2.27952 iter/s, 5.26426s/12 iters), loss = 5.2749
I0405 13:17:21.235874 18799 solver.cpp:237]     Train net output #0: loss = 5.2749 (* 1 = 5.2749 loss)
I0405 13:17:21.235880 18799 sgd_solver.cpp:105] Iteration 3408, lr = 0.0001
I0405 13:17:26.582404 18799 solver.cpp:218] Iteration 3420 (2.24447 iter/s, 5.34648s/12 iters), loss = 5.26701
I0405 13:17:26.582451 18799 solver.cpp:237]     Train net output #0: loss = 5.26701 (* 1 = 5.26701 loss)
I0405 13:17:26.582458 18799 sgd_solver.cpp:105] Iteration 3420, lr = 0.0001
I0405 13:17:31.799113 18799 solver.cpp:218] Iteration 3432 (2.30034 iter/s, 5.21661s/12 iters), loss = 5.24943
I0405 13:17:31.799163 18799 solver.cpp:237]     Train net output #0: loss = 5.24943 (* 1 = 5.24943 loss)
I0405 13:17:31.799171 18799 sgd_solver.cpp:105] Iteration 3432, lr = 0.0001
I0405 13:17:34.583868 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:37.162676 18799 solver.cpp:218] Iteration 3444 (2.23736 iter/s, 5.36346s/12 iters), loss = 5.29519
I0405 13:17:37.162719 18799 solver.cpp:237]     Train net output #0: loss = 5.29519 (* 1 = 5.29519 loss)
I0405 13:17:37.162725 18799 sgd_solver.cpp:105] Iteration 3444, lr = 0.0001
I0405 13:17:42.431461 18799 solver.cpp:218] Iteration 3456 (2.2776 iter/s, 5.26869s/12 iters), loss = 5.26331
I0405 13:17:42.431509 18799 solver.cpp:237]     Train net output #0: loss = 5.26331 (* 1 = 5.26331 loss)
I0405 13:17:42.431514 18799 sgd_solver.cpp:105] Iteration 3456, lr = 0.0001
I0405 13:17:47.238595 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel
I0405 13:17:50.332899 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate
I0405 13:17:52.685165 18799 solver.cpp:330] Iteration 3468, Testing net (#0)
I0405 13:17:52.685261 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:17:53.102607 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:17:55.664098 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:57.288991 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:17:57.289041 18799 solver.cpp:397]     Test net output #1: loss = 5.27952 (* 1 = 5.27952 loss)
I0405 13:17:57.428635 18799 solver.cpp:218] Iteration 3468 (0.800159 iter/s, 14.997s/12 iters), loss = 5.25771
I0405 13:17:57.428691 18799 solver.cpp:237]     Train net output #0: loss = 5.25771 (* 1 = 5.25771 loss)
I0405 13:17:57.428699 18799 sgd_solver.cpp:105] Iteration 3468, lr = 0.0001
I0405 13:18:01.866070 18799 solver.cpp:218] Iteration 3480 (2.70432 iter/s, 4.43734s/12 iters), loss = 5.26359
I0405 13:18:01.866132 18799 solver.cpp:237]     Train net output #0: loss = 5.26359 (* 1 = 5.26359 loss)
I0405 13:18:01.866142 18799 sgd_solver.cpp:105] Iteration 3480, lr = 0.0001
I0405 13:18:07.210996 18799 solver.cpp:218] Iteration 3492 (2.24517 iter/s, 5.34482s/12 iters), loss = 5.27744
I0405 13:18:07.211050 18799 solver.cpp:237]     Train net output #0: loss = 5.27744 (* 1 = 5.27744 loss)
I0405 13:18:07.211059 18799 sgd_solver.cpp:105] Iteration 3492, lr = 0.0001
I0405 13:18:12.328397 18799 solver.cpp:218] Iteration 3504 (2.34499 iter/s, 5.1173s/12 iters), loss = 5.28694
I0405 13:18:12.328440 18799 solver.cpp:237]     Train net output #0: loss = 5.28694 (* 1 = 5.28694 loss)
I0405 13:18:12.328446 18799 sgd_solver.cpp:105] Iteration 3504, lr = 0.0001
I0405 13:18:17.703145 18799 solver.cpp:218] Iteration 3516 (2.2327 iter/s, 5.37465s/12 iters), loss = 5.2839
I0405 13:18:17.703191 18799 solver.cpp:237]     Train net output #0: loss = 5.2839 (* 1 = 5.2839 loss)
I0405 13:18:17.703197 18799 sgd_solver.cpp:105] Iteration 3516, lr = 0.0001
I0405 13:18:22.946185 18799 solver.cpp:218] Iteration 3528 (2.28879 iter/s, 5.24295s/12 iters), loss = 5.2769
I0405 13:18:22.946316 18799 solver.cpp:237]     Train net output #0: loss = 5.2769 (* 1 = 5.2769 loss)
I0405 13:18:22.946323 18799 sgd_solver.cpp:105] Iteration 3528, lr = 0.0001
I0405 13:18:27.933691 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:18:28.238417 18799 solver.cpp:218] Iteration 3540 (2.26755 iter/s, 5.29205s/12 iters), loss = 5.2775
I0405 13:18:28.238467 18799 solver.cpp:237]     Train net output #0: loss = 5.2775 (* 1 = 5.2775 loss)
I0405 13:18:28.238476 18799 sgd_solver.cpp:105] Iteration 3540, lr = 0.0001
I0405 13:18:33.511340 18799 solver.cpp:218] Iteration 3552 (2.27582 iter/s, 5.27283s/12 iters), loss = 5.25464
I0405 13:18:33.511376 18799 solver.cpp:237]     Train net output #0: loss = 5.25464 (* 1 = 5.25464 loss)
I0405 13:18:33.511382 18799 sgd_solver.cpp:105] Iteration 3552, lr = 0.0001
I0405 13:18:38.757925 18799 solver.cpp:218] Iteration 3564 (2.28724 iter/s, 5.2465s/12 iters), loss = 5.28127
I0405 13:18:38.757970 18799 solver.cpp:237]     Train net output #0: loss = 5.28127 (* 1 = 5.28127 loss)
I0405 13:18:38.757977 18799 sgd_solver.cpp:105] Iteration 3564, lr = 0.0001
I0405 13:18:40.933210 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel
I0405 13:18:43.920151 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate
I0405 13:18:46.984690 18799 solver.cpp:330] Iteration 3570, Testing net (#0)
I0405 13:18:46.984710 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:18:50.084556 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:18:51.470466 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:18:51.470504 18799 solver.cpp:397]     Test net output #1: loss = 5.27904 (* 1 = 5.27904 loss)
I0405 13:18:53.229971 18799 solver.cpp:218] Iteration 3576 (0.829193 iter/s, 14.4719s/12 iters), loss = 5.27365
I0405 13:18:53.230064 18799 solver.cpp:237]     Train net output #0: loss = 5.27365 (* 1 = 5.27365 loss)
I0405 13:18:53.230072 18799 sgd_solver.cpp:105] Iteration 3576, lr = 0.0001
I0405 13:18:58.550964 18799 solver.cpp:218] Iteration 3588 (2.25528 iter/s, 5.32085s/12 iters), loss = 5.26359
I0405 13:18:58.551003 18799 solver.cpp:237]     Train net output #0: loss = 5.26359 (* 1 = 5.26359 loss)
I0405 13:18:58.551009 18799 sgd_solver.cpp:105] Iteration 3588, lr = 0.0001
I0405 13:19:03.866119 18799 solver.cpp:218] Iteration 3600 (2.25773 iter/s, 5.31507s/12 iters), loss = 5.25822
I0405 13:19:03.866168 18799 solver.cpp:237]     Train net output #0: loss = 5.25822 (* 1 = 5.25822 loss)
I0405 13:19:03.866173 18799 sgd_solver.cpp:105] Iteration 3600, lr = 0.0001
I0405 13:19:09.130815 18799 solver.cpp:218] Iteration 3612 (2.27937 iter/s, 5.2646s/12 iters), loss = 5.26727
I0405 13:19:09.130853 18799 solver.cpp:237]     Train net output #0: loss = 5.26727 (* 1 = 5.26727 loss)
I0405 13:19:09.130858 18799 sgd_solver.cpp:105] Iteration 3612, lr = 0.0001
I0405 13:19:14.563298 18799 solver.cpp:218] Iteration 3624 (2.20897 iter/s, 5.43239s/12 iters), loss = 5.28421
I0405 13:19:14.563349 18799 solver.cpp:237]     Train net output #0: loss = 5.28421 (* 1 = 5.28421 loss)
I0405 13:19:14.563355 18799 sgd_solver.cpp:105] Iteration 3624, lr = 0.0001
I0405 13:19:19.958684 18799 solver.cpp:218] Iteration 3636 (2.22416 iter/s, 5.39529s/12 iters), loss = 5.28004
I0405 13:19:19.958724 18799 solver.cpp:237]     Train net output #0: loss = 5.28004 (* 1 = 5.28004 loss)
I0405 13:19:19.958729 18799 sgd_solver.cpp:105] Iteration 3636, lr = 0.0001
I0405 13:19:21.914809 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:19:25.310865 18799 solver.cpp:218] Iteration 3648 (2.24211 iter/s, 5.35209s/12 iters), loss = 5.27808
I0405 13:19:25.310993 18799 solver.cpp:237]     Train net output #0: loss = 5.27808 (* 1 = 5.27808 loss)
I0405 13:19:25.311000 18799 sgd_solver.cpp:105] Iteration 3648, lr = 0.0001
I0405 13:19:30.512392 18799 solver.cpp:218] Iteration 3660 (2.30709 iter/s, 5.20135s/12 iters), loss = 5.24539
I0405 13:19:30.512435 18799 solver.cpp:237]     Train net output #0: loss = 5.24539 (* 1 = 5.24539 loss)
I0405 13:19:30.512441 18799 sgd_solver.cpp:105] Iteration 3660, lr = 0.0001
I0405 13:19:35.276965 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel
I0405 13:19:38.328873 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate
I0405 13:19:40.642613 18799 solver.cpp:330] Iteration 3672, Testing net (#0)
I0405 13:19:40.642632 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:19:43.825598 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:19:45.364255 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:19:45.364284 18799 solver.cpp:397]     Test net output #1: loss = 5.27898 (* 1 = 5.27898 loss)
I0405 13:19:45.498793 18799 solver.cpp:218] Iteration 3672 (0.800734 iter/s, 14.9862s/12 iters), loss = 5.2679
I0405 13:19:45.498844 18799 solver.cpp:237]     Train net output #0: loss = 5.2679 (* 1 = 5.2679 loss)
I0405 13:19:45.498853 18799 sgd_solver.cpp:105] Iteration 3672, lr = 0.0001
I0405 13:19:49.771332 18799 solver.cpp:218] Iteration 3684 (2.8087 iter/s, 4.27244s/12 iters), loss = 5.25619
I0405 13:19:49.771373 18799 solver.cpp:237]     Train net output #0: loss = 5.25619 (* 1 = 5.25619 loss)
I0405 13:19:49.771379 18799 sgd_solver.cpp:105] Iteration 3684, lr = 0.0001
I0405 13:19:55.196907 18799 solver.cpp:218] Iteration 3696 (2.21179 iter/s, 5.42548s/12 iters), loss = 5.28088
I0405 13:19:55.196956 18799 solver.cpp:237]     Train net output #0: loss = 5.28088 (* 1 = 5.28088 loss)
I0405 13:19:55.196964 18799 sgd_solver.cpp:105] Iteration 3696, lr = 0.0001
I0405 13:20:00.521394 18799 solver.cpp:218] Iteration 3708 (2.25378 iter/s, 5.32439s/12 iters), loss = 5.24472
I0405 13:20:00.521484 18799 solver.cpp:237]     Train net output #0: loss = 5.24472 (* 1 = 5.24472 loss)
I0405 13:20:00.521492 18799 sgd_solver.cpp:105] Iteration 3708, lr = 0.0001
I0405 13:20:05.959482 18799 solver.cpp:218] Iteration 3720 (2.20671 iter/s, 5.43795s/12 iters), loss = 5.26042
I0405 13:20:05.959533 18799 solver.cpp:237]     Train net output #0: loss = 5.26042 (* 1 = 5.26042 loss)
I0405 13:20:05.959542 18799 sgd_solver.cpp:105] Iteration 3720, lr = 0.0001
I0405 13:20:11.309016 18799 solver.cpp:218] Iteration 3732 (2.24322 iter/s, 5.34944s/12 iters), loss = 5.25345
I0405 13:20:11.309051 18799 solver.cpp:237]     Train net output #0: loss = 5.25345 (* 1 = 5.25345 loss)
I0405 13:20:11.309056 18799 sgd_solver.cpp:105] Iteration 3732, lr = 0.0001
I0405 13:20:15.235644 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:20:16.430462 18799 solver.cpp:218] Iteration 3744 (2.34313 iter/s, 5.12136s/12 iters), loss = 5.25586
I0405 13:20:16.430516 18799 solver.cpp:237]     Train net output #0: loss = 5.25586 (* 1 = 5.25586 loss)
I0405 13:20:16.430526 18799 sgd_solver.cpp:105] Iteration 3744, lr = 0.0001
I0405 13:20:21.870482 18799 solver.cpp:218] Iteration 3756 (2.20591 iter/s, 5.43992s/12 iters), loss = 5.26956
I0405 13:20:21.870519 18799 solver.cpp:237]     Train net output #0: loss = 5.26956 (* 1 = 5.26956 loss)
I0405 13:20:21.870524 18799 sgd_solver.cpp:105] Iteration 3756, lr = 0.0001
I0405 13:20:26.957594 18799 solver.cpp:218] Iteration 3768 (2.35894 iter/s, 5.08703s/12 iters), loss = 5.29083
I0405 13:20:26.957634 18799 solver.cpp:237]     Train net output #0: loss = 5.29083 (* 1 = 5.29083 loss)
I0405 13:20:26.957640 18799 sgd_solver.cpp:105] Iteration 3768, lr = 0.0001
I0405 13:20:29.129709 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel
I0405 13:20:32.152865 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate
I0405 13:20:34.629813 18799 solver.cpp:330] Iteration 3774, Testing net (#0)
I0405 13:20:34.629832 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:20:37.662709 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:20:39.221580 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:20:39.221614 18799 solver.cpp:397]     Test net output #1: loss = 5.27881 (* 1 = 5.27881 loss)
I0405 13:20:41.078622 18799 solver.cpp:218] Iteration 3780 (0.849805 iter/s, 14.1209s/12 iters), loss = 5.26651
I0405 13:20:41.078665 18799 solver.cpp:237]     Train net output #0: loss = 5.26651 (* 1 = 5.26651 loss)
I0405 13:20:41.078671 18799 sgd_solver.cpp:105] Iteration 3780, lr = 0.0001
I0405 13:20:46.377672 18799 solver.cpp:218] Iteration 3792 (2.2646 iter/s, 5.29895s/12 iters), loss = 5.27406
I0405 13:20:46.377722 18799 solver.cpp:237]     Train net output #0: loss = 5.27406 (* 1 = 5.27406 loss)
I0405 13:20:46.377732 18799 sgd_solver.cpp:105] Iteration 3792, lr = 0.0001
I0405 13:20:51.857491 18799 solver.cpp:218] Iteration 3804 (2.18989 iter/s, 5.47972s/12 iters), loss = 5.26229
I0405 13:20:51.857537 18799 solver.cpp:237]     Train net output #0: loss = 5.26229 (* 1 = 5.26229 loss)
I0405 13:20:51.857542 18799 sgd_solver.cpp:105] Iteration 3804, lr = 0.0001
I0405 13:20:57.183290 18799 solver.cpp:218] Iteration 3816 (2.25322 iter/s, 5.3257s/12 iters), loss = 5.27809
I0405 13:20:57.183331 18799 solver.cpp:237]     Train net output #0: loss = 5.27809 (* 1 = 5.27809 loss)
I0405 13:20:57.183337 18799 sgd_solver.cpp:105] Iteration 3816, lr = 0.0001
I0405 13:21:02.290848 18799 solver.cpp:218] Iteration 3828 (2.3495 iter/s, 5.10747s/12 iters), loss = 5.2617
I0405 13:21:02.290951 18799 solver.cpp:237]     Train net output #0: loss = 5.2617 (* 1 = 5.2617 loss)
I0405 13:21:02.290957 18799 sgd_solver.cpp:105] Iteration 3828, lr = 0.0001
I0405 13:21:07.455859 18799 solver.cpp:218] Iteration 3840 (2.32339 iter/s, 5.16486s/12 iters), loss = 5.26809
I0405 13:21:07.455917 18799 solver.cpp:237]     Train net output #0: loss = 5.26809 (* 1 = 5.26809 loss)
I0405 13:21:07.455927 18799 sgd_solver.cpp:105] Iteration 3840, lr = 0.0001
I0405 13:21:08.649231 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:21:12.680668 18799 solver.cpp:218] Iteration 3852 (2.29678 iter/s, 5.2247s/12 iters), loss = 5.27473
I0405 13:21:12.680718 18799 solver.cpp:237]     Train net output #0: loss = 5.27473 (* 1 = 5.27473 loss)
I0405 13:21:12.680727 18799 sgd_solver.cpp:105] Iteration 3852, lr = 0.0001
I0405 13:21:17.909137 18799 solver.cpp:218] Iteration 3864 (2.29517 iter/s, 5.22837s/12 iters), loss = 5.27187
I0405 13:21:17.909181 18799 solver.cpp:237]     Train net output #0: loss = 5.27187 (* 1 = 5.27187 loss)
I0405 13:21:17.909188 18799 sgd_solver.cpp:105] Iteration 3864, lr = 0.0001
I0405 13:21:22.386807 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel
I0405 13:21:25.407979 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate
I0405 13:21:27.729280 18799 solver.cpp:330] Iteration 3876, Testing net (#0)
I0405 13:21:27.729300 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:21:30.579344 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:21:32.093803 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:21:32.093838 18799 solver.cpp:397]     Test net output #1: loss = 5.27785 (* 1 = 5.27785 loss)
I0405 13:21:32.235792 18799 solver.cpp:218] Iteration 3876 (0.837608 iter/s, 14.3265s/12 iters), loss = 5.26276
I0405 13:21:32.235849 18799 solver.cpp:237]     Train net output #0: loss = 5.26276 (* 1 = 5.26276 loss)
I0405 13:21:32.235857 18799 sgd_solver.cpp:105] Iteration 3876, lr = 0.0001
I0405 13:21:36.807960 18799 solver.cpp:218] Iteration 3888 (2.62463 iter/s, 4.57207s/12 iters), loss = 5.26147
I0405 13:21:36.808090 18799 solver.cpp:237]     Train net output #0: loss = 5.26147 (* 1 = 5.26147 loss)
I0405 13:21:36.808097 18799 sgd_solver.cpp:105] Iteration 3888, lr = 0.0001
I0405 13:21:42.062283 18799 solver.cpp:218] Iteration 3900 (2.28391 iter/s, 5.25414s/12 iters), loss = 5.27787
I0405 13:21:42.062322 18799 solver.cpp:237]     Train net output #0: loss = 5.27787 (* 1 = 5.27787 loss)
I0405 13:21:42.062328 18799 sgd_solver.cpp:105] Iteration 3900, lr = 0.0001
I0405 13:21:47.323613 18799 solver.cpp:218] Iteration 3912 (2.28083 iter/s, 5.26124s/12 iters), loss = 5.24702
I0405 13:21:47.323657 18799 solver.cpp:237]     Train net output #0: loss = 5.24702 (* 1 = 5.24702 loss)
I0405 13:21:47.323662 18799 sgd_solver.cpp:105] Iteration 3912, lr = 0.0001
I0405 13:21:52.592653 18799 solver.cpp:218] Iteration 3924 (2.2775 iter/s, 5.26894s/12 iters), loss = 5.26461
I0405 13:21:52.592713 18799 solver.cpp:237]     Train net output #0: loss = 5.26461 (* 1 = 5.26461 loss)
I0405 13:21:52.592723 18799 sgd_solver.cpp:105] Iteration 3924, lr = 0.0001
I0405 13:21:57.770287 18799 solver.cpp:218] Iteration 3936 (2.31771 iter/s, 5.17753s/12 iters), loss = 5.27635
I0405 13:21:57.770325 18799 solver.cpp:237]     Train net output #0: loss = 5.27635 (* 1 = 5.27635 loss)
I0405 13:21:57.770331 18799 sgd_solver.cpp:105] Iteration 3936, lr = 0.0001
I0405 13:22:01.406757 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:22:03.195787 18799 solver.cpp:218] Iteration 3948 (2.21181 iter/s, 5.42541s/12 iters), loss = 5.24499
I0405 13:22:03.195837 18799 solver.cpp:237]     Train net output #0: loss = 5.24499 (* 1 = 5.24499 loss)
I0405 13:22:03.195845 18799 sgd_solver.cpp:105] Iteration 3948, lr = 0.0001
I0405 13:22:08.570654 18799 solver.cpp:218] Iteration 3960 (2.23265 iter/s, 5.37477s/12 iters), loss = 5.24732
I0405 13:22:08.570776 18799 solver.cpp:237]     Train net output #0: loss = 5.24732 (* 1 = 5.24732 loss)
I0405 13:22:08.570786 18799 sgd_solver.cpp:105] Iteration 3960, lr = 0.0001
I0405 13:22:13.570681 18799 solver.cpp:218] Iteration 3972 (2.40006 iter/s, 4.99986s/12 iters), loss = 5.26595
I0405 13:22:13.570719 18799 solver.cpp:237]     Train net output #0: loss = 5.26595 (* 1 = 5.26595 loss)
I0405 13:22:13.570724 18799 sgd_solver.cpp:105] Iteration 3972, lr = 0.0001
I0405 13:22:15.740159 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel
I0405 13:22:18.784195 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate
I0405 13:22:22.302026 18799 solver.cpp:330] Iteration 3978, Testing net (#0)
I0405 13:22:22.302048 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:22:25.201546 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:22:26.777935 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:22:26.777974 18799 solver.cpp:397]     Test net output #1: loss = 5.27734 (* 1 = 5.27734 loss)
I0405 13:22:28.634452 18799 solver.cpp:218] Iteration 3984 (0.796621 iter/s, 15.0636s/12 iters), loss = 5.258
I0405 13:22:28.634513 18799 solver.cpp:237]     Train net output #0: loss = 5.258 (* 1 = 5.258 loss)
I0405 13:22:28.634521 18799 sgd_solver.cpp:105] Iteration 3984, lr = 0.0001
I0405 13:22:33.686102 18799 solver.cpp:218] Iteration 3996 (2.37551 iter/s, 5.05155s/12 iters), loss = 5.27466
I0405 13:22:33.686139 18799 solver.cpp:237]     Train net output #0: loss = 5.27466 (* 1 = 5.27466 loss)
I0405 13:22:33.686144 18799 sgd_solver.cpp:105] Iteration 3996, lr = 0.0001
I0405 13:22:39.037452 18799 solver.cpp:218] Iteration 4008 (2.24246 iter/s, 5.35126s/12 iters), loss = 5.2519
I0405 13:22:39.037606 18799 solver.cpp:237]     Train net output #0: loss = 5.2519 (* 1 = 5.2519 loss)
I0405 13:22:39.037616 18799 sgd_solver.cpp:105] Iteration 4008, lr = 0.0001
I0405 13:22:44.402272 18799 solver.cpp:218] Iteration 4020 (2.23688 iter/s, 5.36462s/12 iters), loss = 5.27019
I0405 13:22:44.402329 18799 solver.cpp:237]     Train net output #0: loss = 5.27019 (* 1 = 5.27019 loss)
I0405 13:22:44.402339 18799 sgd_solver.cpp:105] Iteration 4020, lr = 0.0001
I0405 13:22:49.624558 18799 solver.cpp:218] Iteration 4032 (2.29789 iter/s, 5.22218s/12 iters), loss = 5.2813
I0405 13:22:49.624603 18799 solver.cpp:237]     Train net output #0: loss = 5.2813 (* 1 = 5.2813 loss)
I0405 13:22:49.624608 18799 sgd_solver.cpp:105] Iteration 4032, lr = 0.0001
I0405 13:22:55.050899 18799 solver.cpp:218] Iteration 4044 (2.21147 iter/s, 5.42624s/12 iters), loss = 5.2657
I0405 13:22:55.050935 18799 solver.cpp:237]     Train net output #0: loss = 5.2657 (* 1 = 5.2657 loss)
I0405 13:22:55.050940 18799 sgd_solver.cpp:105] Iteration 4044, lr = 0.0001
I0405 13:22:55.623606 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:23:00.230047 18799 solver.cpp:218] Iteration 4056 (2.31702 iter/s, 5.17906s/12 iters), loss = 5.27168
I0405 13:23:00.230094 18799 solver.cpp:237]     Train net output #0: loss = 5.27168 (* 1 = 5.27168 loss)
I0405 13:23:00.230101 18799 sgd_solver.cpp:105] Iteration 4056, lr = 0.0001
I0405 13:23:05.371451 18799 solver.cpp:218] Iteration 4068 (2.33404 iter/s, 5.14131s/12 iters), loss = 5.26368
I0405 13:23:05.371500 18799 solver.cpp:237]     Train net output #0: loss = 5.26368 (* 1 = 5.26368 loss)
I0405 13:23:05.371510 18799 sgd_solver.cpp:105] Iteration 4068, lr = 0.0001
I0405 13:23:10.023855 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel
I0405 13:23:13.094558 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate
I0405 13:23:15.982422 18799 solver.cpp:330] Iteration 4080, Testing net (#0)
I0405 13:23:15.982443 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:23:18.682968 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:23:20.370811 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:23:20.370852 18799 solver.cpp:397]     Test net output #1: loss = 5.2772 (* 1 = 5.2772 loss)
I0405 13:23:20.513083 18799 solver.cpp:218] Iteration 4080 (0.792525 iter/s, 15.1415s/12 iters), loss = 5.26201
I0405 13:23:20.513125 18799 solver.cpp:237]     Train net output #0: loss = 5.26201 (* 1 = 5.26201 loss)
I0405 13:23:20.513131 18799 sgd_solver.cpp:105] Iteration 4080, lr = 0.0001
I0405 13:23:24.868165 18799 solver.cpp:218] Iteration 4092 (2.75546 iter/s, 4.35499s/12 iters), loss = 5.26352
I0405 13:23:24.868208 18799 solver.cpp:237]     Train net output #0: loss = 5.26352 (* 1 = 5.26352 loss)
I0405 13:23:24.868214 18799 sgd_solver.cpp:105] Iteration 4092, lr = 0.0001
I0405 13:23:30.120712 18799 solver.cpp:218] Iteration 4104 (2.28465 iter/s, 5.25246s/12 iters), loss = 5.24327
I0405 13:23:30.120749 18799 solver.cpp:237]     Train net output #0: loss = 5.24327 (* 1 = 5.24327 loss)
I0405 13:23:30.120755 18799 sgd_solver.cpp:105] Iteration 4104, lr = 0.0001
I0405 13:23:35.356846 18799 solver.cpp:218] Iteration 4116 (2.2918 iter/s, 5.23605s/12 iters), loss = 5.26013
I0405 13:23:35.356894 18799 solver.cpp:237]     Train net output #0: loss = 5.26013 (* 1 = 5.26013 loss)
I0405 13:23:35.356900 18799 sgd_solver.cpp:105] Iteration 4116, lr = 0.0001
I0405 13:23:40.558621 18799 solver.cpp:218] Iteration 4128 (2.30695 iter/s, 5.20168s/12 iters), loss = 5.26454
I0405 13:23:40.559769 18799 solver.cpp:237]     Train net output #0: loss = 5.26454 (* 1 = 5.26454 loss)
I0405 13:23:40.559779 18799 sgd_solver.cpp:105] Iteration 4128, lr = 0.0001
I0405 13:23:45.850394 18799 solver.cpp:218] Iteration 4140 (2.26818 iter/s, 5.29059s/12 iters), loss = 5.25821
I0405 13:23:45.850430 18799 solver.cpp:237]     Train net output #0: loss = 5.25821 (* 1 = 5.25821 loss)
I0405 13:23:45.850435 18799 sgd_solver.cpp:105] Iteration 4140, lr = 0.0001
I0405 13:23:48.647133 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:23:51.182477 18799 solver.cpp:218] Iteration 4152 (2.25056 iter/s, 5.332s/12 iters), loss = 5.27981
I0405 13:23:51.182530 18799 solver.cpp:237]     Train net output #0: loss = 5.27981 (* 1 = 5.27981 loss)
I0405 13:23:51.182538 18799 sgd_solver.cpp:105] Iteration 4152, lr = 0.0001
I0405 13:23:52.878464 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:23:56.474822 18799 solver.cpp:218] Iteration 4164 (2.26747 iter/s, 5.29225s/12 iters), loss = 5.25105
I0405 13:23:56.474862 18799 solver.cpp:237]     Train net output #0: loss = 5.25105 (* 1 = 5.25105 loss)
I0405 13:23:56.474869 18799 sgd_solver.cpp:105] Iteration 4164, lr = 0.0001
I0405 13:24:01.610718 18799 solver.cpp:218] Iteration 4176 (2.33654 iter/s, 5.1358s/12 iters), loss = 5.25141
I0405 13:24:01.610765 18799 solver.cpp:237]     Train net output #0: loss = 5.25141 (* 1 = 5.25141 loss)
I0405 13:24:01.610774 18799 sgd_solver.cpp:105] Iteration 4176, lr = 0.0001
I0405 13:24:03.781805 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel
I0405 13:24:06.792062 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate
I0405 13:24:09.134375 18799 solver.cpp:330] Iteration 4182, Testing net (#0)
I0405 13:24:09.134397 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:24:11.967746 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:24:13.641219 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:24:13.641245 18799 solver.cpp:397]     Test net output #1: loss = 5.27673 (* 1 = 5.27673 loss)
I0405 13:24:15.630888 18799 solver.cpp:218] Iteration 4188 (0.855919 iter/s, 14.02s/12 iters), loss = 5.25734
I0405 13:24:15.630939 18799 solver.cpp:237]     Train net output #0: loss = 5.25734 (* 1 = 5.25734 loss)
I0405 13:24:15.630947 18799 sgd_solver.cpp:105] Iteration 4188, lr = 0.0001
I0405 13:24:20.925915 18799 solver.cpp:218] Iteration 4200 (2.26632 iter/s, 5.29493s/12 iters), loss = 5.26282
I0405 13:24:20.925951 18799 solver.cpp:237]     Train net output #0: loss = 5.26282 (* 1 = 5.26282 loss)
I0405 13:24:20.925956 18799 sgd_solver.cpp:105] Iteration 4200, lr = 0.0001
I0405 13:24:26.137473 18799 solver.cpp:218] Iteration 4212 (2.30261 iter/s, 5.21148s/12 iters), loss = 5.27754
I0405 13:24:26.137512 18799 solver.cpp:237]     Train net output #0: loss = 5.27754 (* 1 = 5.27754 loss)
I0405 13:24:26.137518 18799 sgd_solver.cpp:105] Iteration 4212, lr = 0.0001
I0405 13:24:31.491755 18799 solver.cpp:218] Iteration 4224 (2.24124 iter/s, 5.35419s/12 iters), loss = 5.28012
I0405 13:24:31.491820 18799 solver.cpp:237]     Train net output #0: loss = 5.28012 (* 1 = 5.28012 loss)
I0405 13:24:31.491830 18799 sgd_solver.cpp:105] Iteration 4224, lr = 0.0001
I0405 13:24:36.806506 18799 solver.cpp:218] Iteration 4236 (2.25791 iter/s, 5.31464s/12 iters), loss = 5.28494
I0405 13:24:36.806550 18799 solver.cpp:237]     Train net output #0: loss = 5.28494 (* 1 = 5.28494 loss)
I0405 13:24:36.806555 18799 sgd_solver.cpp:105] Iteration 4236, lr = 0.0001
I0405 13:24:41.838419 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:24:42.116539 18799 solver.cpp:218] Iteration 4248 (2.25991 iter/s, 5.30994s/12 iters), loss = 5.29538
I0405 13:24:42.116699 18799 solver.cpp:237]     Train net output #0: loss = 5.29538 (* 1 = 5.29538 loss)
I0405 13:24:42.116710 18799 sgd_solver.cpp:105] Iteration 4248, lr = 0.0001
I0405 13:24:47.458146 18799 solver.cpp:218] Iteration 4260 (2.2466 iter/s, 5.3414s/12 iters), loss = 5.25544
I0405 13:24:47.458189 18799 solver.cpp:237]     Train net output #0: loss = 5.25544 (* 1 = 5.25544 loss)
I0405 13:24:47.458194 18799 sgd_solver.cpp:105] Iteration 4260, lr = 0.0001
I0405 13:24:52.778663 18799 solver.cpp:218] Iteration 4272 (2.25546 iter/s, 5.32043s/12 iters), loss = 5.27448
I0405 13:24:52.778704 18799 solver.cpp:237]     Train net output #0: loss = 5.27448 (* 1 = 5.27448 loss)
I0405 13:24:52.778709 18799 sgd_solver.cpp:105] Iteration 4272, lr = 0.0001
I0405 13:24:57.666249 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel
I0405 13:25:00.679275 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate
I0405 13:25:03.843189 18799 solver.cpp:330] Iteration 4284, Testing net (#0)
I0405 13:25:03.843210 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:25:06.508411 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:25:08.189283 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:25:08.189319 18799 solver.cpp:397]     Test net output #1: loss = 5.27577 (* 1 = 5.27577 loss)
I0405 13:25:08.328162 18799 solver.cpp:218] Iteration 4284 (0.771736 iter/s, 15.5494s/12 iters), loss = 5.27366
I0405 13:25:08.329727 18799 solver.cpp:237]     Train net output #0: loss = 5.27366 (* 1 = 5.27366 loss)
I0405 13:25:08.329741 18799 sgd_solver.cpp:105] Iteration 4284, lr = 0.0001
I0405 13:25:12.752157 18799 solver.cpp:218] Iteration 4296 (2.71346 iter/s, 4.42239s/12 iters), loss = 5.2455
I0405 13:25:12.752285 18799 solver.cpp:237]     Train net output #0: loss = 5.2455 (* 1 = 5.2455 loss)
I0405 13:25:12.752292 18799 sgd_solver.cpp:105] Iteration 4296, lr = 0.0001
I0405 13:25:18.148416 18799 solver.cpp:218] Iteration 4308 (2.22383 iter/s, 5.39609s/12 iters), loss = 5.24899
I0405 13:25:18.148473 18799 solver.cpp:237]     Train net output #0: loss = 5.24899 (* 1 = 5.24899 loss)
I0405 13:25:18.148481 18799 sgd_solver.cpp:105] Iteration 4308, lr = 0.0001
I0405 13:25:23.330945 18799 solver.cpp:218] Iteration 4320 (2.31552 iter/s, 5.18242s/12 iters), loss = 5.25379
I0405 13:25:23.331001 18799 solver.cpp:237]     Train net output #0: loss = 5.25379 (* 1 = 5.25379 loss)
I0405 13:25:23.331008 18799 sgd_solver.cpp:105] Iteration 4320, lr = 0.0001
I0405 13:25:28.530560 18799 solver.cpp:218] Iteration 4332 (2.30791 iter/s, 5.19951s/12 iters), loss = 5.26383
I0405 13:25:28.530613 18799 solver.cpp:237]     Train net output #0: loss = 5.26383 (* 1 = 5.26383 loss)
I0405 13:25:28.530622 18799 sgd_solver.cpp:105] Iteration 4332, lr = 0.0001
I0405 13:25:33.774848 18799 solver.cpp:218] Iteration 4344 (2.28825 iter/s, 5.24419s/12 iters), loss = 5.2708
I0405 13:25:33.774890 18799 solver.cpp:237]     Train net output #0: loss = 5.2708 (* 1 = 5.2708 loss)
I0405 13:25:33.774895 18799 sgd_solver.cpp:105] Iteration 4344, lr = 0.0001
I0405 13:25:35.903671 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:25:39.301801 18799 solver.cpp:218] Iteration 4356 (2.17121 iter/s, 5.52686s/12 iters), loss = 5.27648
I0405 13:25:39.301851 18799 solver.cpp:237]     Train net output #0: loss = 5.27648 (* 1 = 5.27648 loss)
I0405 13:25:39.301858 18799 sgd_solver.cpp:105] Iteration 4356, lr = 0.0001
I0405 13:25:44.676156 18799 solver.cpp:218] Iteration 4368 (2.23287 iter/s, 5.37426s/12 iters), loss = 5.24879
I0405 13:25:44.676323 18799 solver.cpp:237]     Train net output #0: loss = 5.24879 (* 1 = 5.24879 loss)
I0405 13:25:44.676331 18799 sgd_solver.cpp:105] Iteration 4368, lr = 0.0001
I0405 13:25:50.046113 18799 solver.cpp:218] Iteration 4380 (2.23474 iter/s, 5.36975s/12 iters), loss = 5.26663
I0405 13:25:50.046150 18799 solver.cpp:237]     Train net output #0: loss = 5.26663 (* 1 = 5.26663 loss)
I0405 13:25:50.046156 18799 sgd_solver.cpp:105] Iteration 4380, lr = 0.0001
I0405 13:25:52.281888 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel
I0405 13:25:55.273855 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate
I0405 13:25:57.593202 18799 solver.cpp:330] Iteration 4386, Testing net (#0)
I0405 13:25:57.593220 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:26:00.304287 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:26:02.018487 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:26:02.018524 18799 solver.cpp:397]     Test net output #1: loss = 5.27503 (* 1 = 5.27503 loss)
I0405 13:26:03.855479 18799 solver.cpp:218] Iteration 4392 (0.868984 iter/s, 13.8092s/12 iters), loss = 5.25577
I0405 13:26:03.855521 18799 solver.cpp:237]     Train net output #0: loss = 5.25577 (* 1 = 5.25577 loss)
I0405 13:26:03.855527 18799 sgd_solver.cpp:105] Iteration 4392, lr = 0.0001
I0405 13:26:09.399296 18799 solver.cpp:218] Iteration 4404 (2.16461 iter/s, 5.54373s/12 iters), loss = 5.24558
I0405 13:26:09.399333 18799 solver.cpp:237]     Train net output #0: loss = 5.24558 (* 1 = 5.24558 loss)
I0405 13:26:09.399339 18799 sgd_solver.cpp:105] Iteration 4404, lr = 0.0001
I0405 13:26:14.450460 18799 solver.cpp:218] Iteration 4416 (2.37573 iter/s, 5.05108s/12 iters), loss = 5.23432
I0405 13:26:14.450503 18799 solver.cpp:237]     Train net output #0: loss = 5.23432 (* 1 = 5.23432 loss)
I0405 13:26:14.450511 18799 sgd_solver.cpp:105] Iteration 4416, lr = 0.0001
I0405 13:26:19.878291 18799 solver.cpp:218] Iteration 4428 (2.21086 iter/s, 5.42774s/12 iters), loss = 5.2509
I0405 13:26:19.878405 18799 solver.cpp:237]     Train net output #0: loss = 5.2509 (* 1 = 5.2509 loss)
I0405 13:26:19.878412 18799 sgd_solver.cpp:105] Iteration 4428, lr = 0.0001
I0405 13:26:25.063995 18799 solver.cpp:218] Iteration 4440 (2.31412 iter/s, 5.18555s/12 iters), loss = 5.2497
I0405 13:26:25.064034 18799 solver.cpp:237]     Train net output #0: loss = 5.2497 (* 1 = 5.2497 loss)
I0405 13:26:25.064039 18799 sgd_solver.cpp:105] Iteration 4440, lr = 0.0001
I0405 13:26:29.361272 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:26:30.472426 18799 solver.cpp:218] Iteration 4452 (2.21879 iter/s, 5.40834s/12 iters), loss = 5.25699
I0405 13:26:30.472463 18799 solver.cpp:237]     Train net output #0: loss = 5.25699 (* 1 = 5.25699 loss)
I0405 13:26:30.472468 18799 sgd_solver.cpp:105] Iteration 4452, lr = 0.0001
I0405 13:26:35.949066 18799 solver.cpp:218] Iteration 4464 (2.19116 iter/s, 5.47656s/12 iters), loss = 5.26733
I0405 13:26:35.949105 18799 solver.cpp:237]     Train net output #0: loss = 5.26733 (* 1 = 5.26733 loss)
I0405 13:26:35.949111 18799 sgd_solver.cpp:105] Iteration 4464, lr = 0.0001
I0405 13:26:41.142573 18799 solver.cpp:218] Iteration 4476 (2.31062 iter/s, 5.19342s/12 iters), loss = 5.28513
I0405 13:26:41.142618 18799 solver.cpp:237]     Train net output #0: loss = 5.28513 (* 1 = 5.28513 loss)
I0405 13:26:41.142627 18799 sgd_solver.cpp:105] Iteration 4476, lr = 0.0001
I0405 13:26:45.794656 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel
I0405 13:26:48.805857 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate
I0405 13:26:51.114799 18799 solver.cpp:330] Iteration 4488, Testing net (#0)
I0405 13:26:51.114861 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:26:53.805974 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:26:55.648218 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:26:55.648255 18799 solver.cpp:397]     Test net output #1: loss = 5.27365 (* 1 = 5.27365 loss)
I0405 13:26:55.790012 18799 solver.cpp:218] Iteration 4488 (0.819264 iter/s, 14.6473s/12 iters), loss = 5.25713
I0405 13:26:55.791612 18799 solver.cpp:237]     Train net output #0: loss = 5.25713 (* 1 = 5.25713 loss)
I0405 13:26:55.791630 18799 sgd_solver.cpp:105] Iteration 4488, lr = 0.0001
I0405 13:27:00.106022 18799 solver.cpp:218] Iteration 4500 (2.7814 iter/s, 4.31438s/12 iters), loss = 5.26577
I0405 13:27:00.106081 18799 solver.cpp:237]     Train net output #0: loss = 5.26577 (* 1 = 5.26577 loss)
I0405 13:27:00.106091 18799 sgd_solver.cpp:105] Iteration 4500, lr = 0.0001
I0405 13:27:05.525837 18799 solver.cpp:218] Iteration 4512 (2.21414 iter/s, 5.41971s/12 iters), loss = 5.2573
I0405 13:27:05.525877 18799 solver.cpp:237]     Train net output #0: loss = 5.2573 (* 1 = 5.2573 loss)
I0405 13:27:05.525882 18799 sgd_solver.cpp:105] Iteration 4512, lr = 0.0001
I0405 13:27:11.115208 18799 solver.cpp:218] Iteration 4524 (2.14697 iter/s, 5.58928s/12 iters), loss = 5.26652
I0405 13:27:11.115257 18799 solver.cpp:237]     Train net output #0: loss = 5.26652 (* 1 = 5.26652 loss)
I0405 13:27:11.115265 18799 sgd_solver.cpp:105] Iteration 4524, lr = 0.0001
I0405 13:27:16.488798 18799 solver.cpp:218] Iteration 4536 (2.23319 iter/s, 5.37349s/12 iters), loss = 5.24904
I0405 13:27:16.488854 18799 solver.cpp:237]     Train net output #0: loss = 5.24904 (* 1 = 5.24904 loss)
I0405 13:27:16.488864 18799 sgd_solver.cpp:105] Iteration 4536, lr = 0.0001
I0405 13:27:21.713028 18799 solver.cpp:218] Iteration 4548 (2.29703 iter/s, 5.22413s/12 iters), loss = 5.26094
I0405 13:27:21.713145 18799 solver.cpp:237]     Train net output #0: loss = 5.26094 (* 1 = 5.26094 loss)
I0405 13:27:21.713152 18799 sgd_solver.cpp:105] Iteration 4548, lr = 0.0001
I0405 13:27:22.904923 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:27:26.997516 18799 solver.cpp:218] Iteration 4560 (2.27087 iter/s, 5.28432s/12 iters), loss = 5.26417
I0405 13:27:26.997575 18799 solver.cpp:237]     Train net output #0: loss = 5.26417 (* 1 = 5.26417 loss)
I0405 13:27:26.997582 18799 sgd_solver.cpp:105] Iteration 4560, lr = 0.0001
I0405 13:27:32.247897 18799 solver.cpp:218] Iteration 4572 (2.2856 iter/s, 5.25026s/12 iters), loss = 5.25764
I0405 13:27:32.247943 18799 solver.cpp:237]     Train net output #0: loss = 5.25764 (* 1 = 5.25764 loss)
I0405 13:27:32.247949 18799 sgd_solver.cpp:105] Iteration 4572, lr = 0.0001
I0405 13:27:37.428459 18799 solver.cpp:218] Iteration 4584 (2.31639 iter/s, 5.18047s/12 iters), loss = 5.27085
I0405 13:27:37.428512 18799 solver.cpp:237]     Train net output #0: loss = 5.27085 (* 1 = 5.27085 loss)
I0405 13:27:37.428521 18799 sgd_solver.cpp:105] Iteration 4584, lr = 0.0001
I0405 13:27:39.570312 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel
I0405 13:27:42.601852 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate
I0405 13:27:45.856748 18799 solver.cpp:330] Iteration 4590, Testing net (#0)
I0405 13:27:45.856772 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:27:48.658434 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:27:50.577527 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:27:50.577564 18799 solver.cpp:397]     Test net output #1: loss = 5.27302 (* 1 = 5.27302 loss)
I0405 13:27:52.465986 18799 solver.cpp:218] Iteration 4596 (0.798012 iter/s, 15.0374s/12 iters), loss = 5.25527
I0405 13:27:52.466085 18799 solver.cpp:237]     Train net output #0: loss = 5.25527 (* 1 = 5.25527 loss)
I0405 13:27:52.466091 18799 sgd_solver.cpp:105] Iteration 4596, lr = 0.0001
I0405 13:27:58.081439 18799 solver.cpp:218] Iteration 4608 (2.13702 iter/s, 5.6153s/12 iters), loss = 5.28779
I0405 13:27:58.081493 18799 solver.cpp:237]     Train net output #0: loss = 5.28779 (* 1 = 5.28779 loss)
I0405 13:27:58.081502 18799 sgd_solver.cpp:105] Iteration 4608, lr = 0.0001
I0405 13:28:03.371827 18799 solver.cpp:218] Iteration 4620 (2.26831 iter/s, 5.29028s/12 iters), loss = 5.24243
I0405 13:28:03.371878 18799 solver.cpp:237]     Train net output #0: loss = 5.24243 (* 1 = 5.24243 loss)
I0405 13:28:03.371884 18799 sgd_solver.cpp:105] Iteration 4620, lr = 0.0001
I0405 13:28:08.505946 18799 solver.cpp:218] Iteration 4632 (2.33735 iter/s, 5.13402s/12 iters), loss = 5.26495
I0405 13:28:08.505996 18799 solver.cpp:237]     Train net output #0: loss = 5.26495 (* 1 = 5.26495 loss)
I0405 13:28:08.506003 18799 sgd_solver.cpp:105] Iteration 4632, lr = 0.0001
I0405 13:28:13.698774 18799 solver.cpp:218] Iteration 4644 (2.31092 iter/s, 5.19274s/12 iters), loss = 5.28903
I0405 13:28:13.698815 18799 solver.cpp:237]     Train net output #0: loss = 5.28903 (* 1 = 5.28903 loss)
I0405 13:28:13.698820 18799 sgd_solver.cpp:105] Iteration 4644, lr = 0.0001
I0405 13:28:17.196756 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:28:18.935185 18799 solver.cpp:218] Iteration 4656 (2.29168 iter/s, 5.23632s/12 iters), loss = 5.23948
I0405 13:28:18.935222 18799 solver.cpp:237]     Train net output #0: loss = 5.23948 (* 1 = 5.23948 loss)
I0405 13:28:18.935228 18799 sgd_solver.cpp:105] Iteration 4656, lr = 0.0001
I0405 13:28:24.310503 18799 solver.cpp:218] Iteration 4668 (2.23246 iter/s, 5.37523s/12 iters), loss = 5.24626
I0405 13:28:24.312479 18799 solver.cpp:237]     Train net output #0: loss = 5.24626 (* 1 = 5.24626 loss)
I0405 13:28:24.312489 18799 sgd_solver.cpp:105] Iteration 4668, lr = 0.0001
I0405 13:28:29.361157 18799 solver.cpp:218] Iteration 4680 (2.37688 iter/s, 5.04864s/12 iters), loss = 5.2599
I0405 13:28:29.361194 18799 solver.cpp:237]     Train net output #0: loss = 5.2599 (* 1 = 5.2599 loss)
I0405 13:28:29.361200 18799 sgd_solver.cpp:105] Iteration 4680, lr = 0.0001
I0405 13:28:34.067180 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel
I0405 13:28:37.151530 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate
I0405 13:28:40.720096 18799 solver.cpp:330] Iteration 4692, Testing net (#0)
I0405 13:28:40.720115 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:28:43.334300 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:28:45.304811 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:28:45.304847 18799 solver.cpp:397]     Test net output #1: loss = 5.27136 (* 1 = 5.27136 loss)
I0405 13:28:45.447113 18799 solver.cpp:218] Iteration 4692 (0.745999 iter/s, 16.0858s/12 iters), loss = 5.26614
I0405 13:28:45.447156 18799 solver.cpp:237]     Train net output #0: loss = 5.26614 (* 1 = 5.26614 loss)
I0405 13:28:45.447161 18799 sgd_solver.cpp:105] Iteration 4692, lr = 0.0001
I0405 13:28:49.910181 18799 solver.cpp:218] Iteration 4704 (2.68879 iter/s, 4.46298s/12 iters), loss = 5.26653
I0405 13:28:49.910218 18799 solver.cpp:237]     Train net output #0: loss = 5.26653 (* 1 = 5.26653 loss)
I0405 13:28:49.910224 18799 sgd_solver.cpp:105] Iteration 4704, lr = 0.0001
I0405 13:28:55.246922 18799 solver.cpp:218] Iteration 4716 (2.2486 iter/s, 5.33665s/12 iters), loss = 5.24623
I0405 13:28:55.247036 18799 solver.cpp:237]     Train net output #0: loss = 5.24623 (* 1 = 5.24623 loss)
I0405 13:28:55.247045 18799 sgd_solver.cpp:105] Iteration 4716, lr = 0.0001
I0405 13:29:00.368044 18799 solver.cpp:218] Iteration 4728 (2.34331 iter/s, 5.12096s/12 iters), loss = 5.25108
I0405 13:29:00.368104 18799 solver.cpp:237]     Train net output #0: loss = 5.25108 (* 1 = 5.25108 loss)
I0405 13:29:00.368113 18799 sgd_solver.cpp:105] Iteration 4728, lr = 0.0001
I0405 13:29:05.720767 18799 solver.cpp:218] Iteration 4740 (2.2419 iter/s, 5.35261s/12 iters), loss = 5.25507
I0405 13:29:05.720821 18799 solver.cpp:237]     Train net output #0: loss = 5.25507 (* 1 = 5.25507 loss)
I0405 13:29:05.720831 18799 sgd_solver.cpp:105] Iteration 4740, lr = 0.0001
I0405 13:29:10.996848 18799 solver.cpp:218] Iteration 4752 (2.27446 iter/s, 5.27598s/12 iters), loss = 5.26394
I0405 13:29:10.996893 18799 solver.cpp:237]     Train net output #0: loss = 5.26394 (* 1 = 5.26394 loss)
I0405 13:29:10.996899 18799 sgd_solver.cpp:105] Iteration 4752, lr = 0.0001
I0405 13:29:11.631692 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:29:16.354773 18799 solver.cpp:218] Iteration 4764 (2.23971 iter/s, 5.35784s/12 iters), loss = 5.26613
I0405 13:29:16.354820 18799 solver.cpp:237]     Train net output #0: loss = 5.26613 (* 1 = 5.26613 loss)
I0405 13:29:16.354825 18799 sgd_solver.cpp:105] Iteration 4764, lr = 0.0001
I0405 13:29:21.612242 18799 solver.cpp:218] Iteration 4776 (2.28251 iter/s, 5.25738s/12 iters), loss = 5.25709
I0405 13:29:21.612282 18799 solver.cpp:237]     Train net output #0: loss = 5.25709 (* 1 = 5.25709 loss)
I0405 13:29:21.612289 18799 sgd_solver.cpp:105] Iteration 4776, lr = 0.0001
I0405 13:29:26.800760 18799 solver.cpp:218] Iteration 4788 (2.31284 iter/s, 5.18843s/12 iters), loss = 5.25414
I0405 13:29:26.800930 18799 solver.cpp:237]     Train net output #0: loss = 5.25414 (* 1 = 5.25414 loss)
I0405 13:29:26.800938 18799 sgd_solver.cpp:105] Iteration 4788, lr = 0.0001
I0405 13:29:28.955991 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel
I0405 13:29:32.748390 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate
I0405 13:29:36.902381 18799 solver.cpp:330] Iteration 4794, Testing net (#0)
I0405 13:29:36.902405 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:29:39.491061 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:29:41.588125 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:29:41.588162 18799 solver.cpp:397]     Test net output #1: loss = 5.2696 (* 1 = 5.2696 loss)
I0405 13:29:43.451401 18799 solver.cpp:218] Iteration 4800 (0.720705 iter/s, 16.6504s/12 iters), loss = 5.27043
I0405 13:29:43.451453 18799 solver.cpp:237]     Train net output #0: loss = 5.27043 (* 1 = 5.27043 loss)
I0405 13:29:43.451462 18799 sgd_solver.cpp:105] Iteration 4800, lr = 0.0001
I0405 13:29:48.760605 18799 solver.cpp:218] Iteration 4812 (2.26027 iter/s, 5.3091s/12 iters), loss = 5.22859
I0405 13:29:48.760644 18799 solver.cpp:237]     Train net output #0: loss = 5.22859 (* 1 = 5.22859 loss)
I0405 13:29:48.760650 18799 sgd_solver.cpp:105] Iteration 4812, lr = 0.0001
I0405 13:29:54.052353 18799 solver.cpp:218] Iteration 4824 (2.26772 iter/s, 5.29166s/12 iters), loss = 5.25995
I0405 13:29:54.052412 18799 solver.cpp:237]     Train net output #0: loss = 5.25995 (* 1 = 5.25995 loss)
I0405 13:29:54.052420 18799 sgd_solver.cpp:105] Iteration 4824, lr = 0.0001
I0405 13:29:59.462800 18799 solver.cpp:218] Iteration 4836 (2.21798 iter/s, 5.41033s/12 iters), loss = 5.24177
I0405 13:29:59.462911 18799 solver.cpp:237]     Train net output #0: loss = 5.24177 (* 1 = 5.24177 loss)
I0405 13:29:59.462919 18799 sgd_solver.cpp:105] Iteration 4836, lr = 0.0001
I0405 13:30:01.634692 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:30:04.850167 18799 solver.cpp:218] Iteration 4848 (2.2275 iter/s, 5.38721s/12 iters), loss = 5.25706
I0405 13:30:04.850219 18799 solver.cpp:237]     Train net output #0: loss = 5.25706 (* 1 = 5.25706 loss)
I0405 13:30:04.850227 18799 sgd_solver.cpp:105] Iteration 4848, lr = 0.0001
I0405 13:30:07.688560 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:30:10.130645 18799 solver.cpp:218] Iteration 4860 (2.27256 iter/s, 5.28038s/12 iters), loss = 5.24949
I0405 13:30:10.130690 18799 solver.cpp:237]     Train net output #0: loss = 5.24949 (* 1 = 5.24949 loss)
I0405 13:30:10.130695 18799 sgd_solver.cpp:105] Iteration 4860, lr = 0.0001
I0405 13:30:15.274767 18799 solver.cpp:218] Iteration 4872 (2.3328 iter/s, 5.14403s/12 iters), loss = 5.25203
I0405 13:30:15.274817 18799 solver.cpp:237]     Train net output #0: loss = 5.25203 (* 1 = 5.25203 loss)
I0405 13:30:15.274825 18799 sgd_solver.cpp:105] Iteration 4872, lr = 0.0001
I0405 13:30:20.429414 18799 solver.cpp:218] Iteration 4884 (2.32817 iter/s, 5.15425s/12 iters), loss = 5.25851
I0405 13:30:20.429463 18799 solver.cpp:237]     Train net output #0: loss = 5.25851 (* 1 = 5.25851 loss)
I0405 13:30:20.429471 18799 sgd_solver.cpp:105] Iteration 4884, lr = 0.0001
I0405 13:30:25.176488 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel
I0405 13:30:28.248692 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate
I0405 13:30:32.497581 18799 solver.cpp:330] Iteration 4896, Testing net (#0)
I0405 13:30:32.497687 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:30:34.899611 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:30:36.807718 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:30:36.807751 18799 solver.cpp:397]     Test net output #1: loss = 5.26703 (* 1 = 5.26703 loss)
I0405 13:30:36.945580 18799 solver.cpp:218] Iteration 4896 (0.726568 iter/s, 16.516s/12 iters), loss = 5.24768
I0405 13:30:36.945623 18799 solver.cpp:237]     Train net output #0: loss = 5.24768 (* 1 = 5.24768 loss)
I0405 13:30:36.945628 18799 sgd_solver.cpp:105] Iteration 4896, lr = 0.0001
I0405 13:30:41.439889 18799 solver.cpp:218] Iteration 4908 (2.67009 iter/s, 4.49422s/12 iters), loss = 5.26202
I0405 13:30:41.439939 18799 solver.cpp:237]     Train net output #0: loss = 5.26202 (* 1 = 5.26202 loss)
I0405 13:30:41.439945 18799 sgd_solver.cpp:105] Iteration 4908, lr = 0.0001
I0405 13:30:46.803287 18799 solver.cpp:218] Iteration 4920 (2.23743 iter/s, 5.3633s/12 iters), loss = 5.26291
I0405 13:30:46.803326 18799 solver.cpp:237]     Train net output #0: loss = 5.26291 (* 1 = 5.26291 loss)
I0405 13:30:46.803333 18799 sgd_solver.cpp:105] Iteration 4920, lr = 0.0001
I0405 13:30:52.054672 18799 solver.cpp:218] Iteration 4932 (2.28515 iter/s, 5.2513s/12 iters), loss = 5.26266
I0405 13:30:52.054713 18799 solver.cpp:237]     Train net output #0: loss = 5.26266 (* 1 = 5.26266 loss)
I0405 13:30:52.054718 18799 sgd_solver.cpp:105] Iteration 4932, lr = 0.0001
I0405 13:30:57.427112 18799 solver.cpp:218] Iteration 4944 (2.23366 iter/s, 5.37235s/12 iters), loss = 5.2817
I0405 13:30:57.427151 18799 solver.cpp:237]     Train net output #0: loss = 5.2817 (* 1 = 5.2817 loss)
I0405 13:30:57.427156 18799 sgd_solver.cpp:105] Iteration 4944, lr = 0.0001
I0405 13:31:02.517429 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:31:02.768147 18799 solver.cpp:218] Iteration 4956 (2.24679 iter/s, 5.34095s/12 iters), loss = 5.26471
I0405 13:31:02.768191 18799 solver.cpp:237]     Train net output #0: loss = 5.26471 (* 1 = 5.26471 loss)
I0405 13:31:02.768196 18799 sgd_solver.cpp:105] Iteration 4956, lr = 0.0001
I0405 13:31:07.890695 18799 solver.cpp:218] Iteration 4968 (2.34263 iter/s, 5.12246s/12 iters), loss = 5.24363
I0405 13:31:07.890738 18799 solver.cpp:237]     Train net output #0: loss = 5.24363 (* 1 = 5.24363 loss)
I0405 13:31:07.890744 18799 sgd_solver.cpp:105] Iteration 4968, lr = 0.0001
I0405 13:31:13.045512 18799 solver.cpp:218] Iteration 4980 (2.32796 iter/s, 5.15473s/12 iters), loss = 5.25901
I0405 13:31:13.045562 18799 solver.cpp:237]     Train net output #0: loss = 5.25901 (* 1 = 5.25901 loss)
I0405 13:31:13.045569 18799 sgd_solver.cpp:105] Iteration 4980, lr = 0.0001
I0405 13:31:18.410861 18799 solver.cpp:218] Iteration 4992 (2.23662 iter/s, 5.36525s/12 iters), loss = 5.26566
I0405 13:31:18.410905 18799 solver.cpp:237]     Train net output #0: loss = 5.26566 (* 1 = 5.26566 loss)
I0405 13:31:18.410910 18799 sgd_solver.cpp:105] Iteration 4992, lr = 0.0001
I0405 13:31:20.564205 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel
I0405 13:31:23.624902 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate
I0405 13:31:27.677256 18799 solver.cpp:330] Iteration 4998, Testing net (#0)
I0405 13:31:27.677275 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:31:30.127698 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:31:32.129021 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:31:32.129057 18799 solver.cpp:397]     Test net output #1: loss = 5.26571 (* 1 = 5.26571 loss)
I0405 13:31:34.018790 18799 solver.cpp:218] Iteration 5004 (0.768847 iter/s, 15.6078s/12 iters), loss = 5.24139
I0405 13:31:34.018926 18799 solver.cpp:237]     Train net output #0: loss = 5.24139 (* 1 = 5.24139 loss)
I0405 13:31:34.018932 18799 sgd_solver.cpp:105] Iteration 5004, lr = 0.0001
I0405 13:31:39.298318 18799 solver.cpp:218] Iteration 5016 (2.27301 iter/s, 5.27934s/12 iters), loss = 5.26017
I0405 13:31:39.298382 18799 solver.cpp:237]     Train net output #0: loss = 5.26017 (* 1 = 5.26017 loss)
I0405 13:31:39.298391 18799 sgd_solver.cpp:105] Iteration 5016, lr = 0.0001
I0405 13:31:44.671995 18799 solver.cpp:218] Iteration 5028 (2.23315 iter/s, 5.37357s/12 iters), loss = 5.23937
I0405 13:31:44.672049 18799 solver.cpp:237]     Train net output #0: loss = 5.23937 (* 1 = 5.23937 loss)
I0405 13:31:44.672057 18799 sgd_solver.cpp:105] Iteration 5028, lr = 0.0001
I0405 13:31:49.871927 18799 solver.cpp:218] Iteration 5040 (2.30777 iter/s, 5.19983s/12 iters), loss = 5.24513
I0405 13:31:49.871975 18799 solver.cpp:237]     Train net output #0: loss = 5.24513 (* 1 = 5.24513 loss)
I0405 13:31:49.871982 18799 sgd_solver.cpp:105] Iteration 5040, lr = 0.0001
I0405 13:31:55.087939 18799 solver.cpp:218] Iteration 5052 (2.30065 iter/s, 5.21592s/12 iters), loss = 5.25384
I0405 13:31:55.087985 18799 solver.cpp:237]     Train net output #0: loss = 5.25384 (* 1 = 5.25384 loss)
I0405 13:31:55.087991 18799 sgd_solver.cpp:105] Iteration 5052, lr = 0.0001
I0405 13:31:57.151589 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:32:00.348556 18799 solver.cpp:218] Iteration 5064 (2.28114 iter/s, 5.26052s/12 iters), loss = 5.29678
I0405 13:32:00.348609 18799 solver.cpp:237]     Train net output #0: loss = 5.29678 (* 1 = 5.29678 loss)
I0405 13:32:00.348618 18799 sgd_solver.cpp:105] Iteration 5064, lr = 0.0001
I0405 13:32:05.457139 18799 solver.cpp:218] Iteration 5076 (2.34904 iter/s, 5.10848s/12 iters), loss = 5.2451
I0405 13:32:05.457278 18799 solver.cpp:237]     Train net output #0: loss = 5.2451 (* 1 = 5.2451 loss)
I0405 13:32:05.457285 18799 sgd_solver.cpp:105] Iteration 5076, lr = 0.0001
I0405 13:32:10.846004 18799 solver.cpp:218] Iteration 5088 (2.22689 iter/s, 5.38869s/12 iters), loss = 5.26859
I0405 13:32:10.846040 18799 solver.cpp:237]     Train net output #0: loss = 5.26859 (* 1 = 5.26859 loss)
I0405 13:32:10.846045 18799 sgd_solver.cpp:105] Iteration 5088, lr = 0.0001
I0405 13:32:15.486003 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel
I0405 13:32:18.595168 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate
I0405 13:32:22.415951 18799 solver.cpp:330] Iteration 5100, Testing net (#0)
I0405 13:32:22.415980 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:32:24.807998 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:32:26.852834 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0067402
I0405 13:32:26.852860 18799 solver.cpp:397]     Test net output #1: loss = 5.26255 (* 1 = 5.26255 loss)
I0405 13:32:26.992166 18799 solver.cpp:218] Iteration 5100 (0.743218 iter/s, 16.146s/12 iters), loss = 5.2487
I0405 13:32:26.992213 18799 solver.cpp:237]     Train net output #0: loss = 5.2487 (* 1 = 5.2487 loss)
I0405 13:32:26.992219 18799 sgd_solver.cpp:105] Iteration 5100, lr = 0.0001
I0405 13:32:31.133797 18799 solver.cpp:218] Iteration 5112 (2.89747 iter/s, 4.14154s/12 iters), loss = 5.23363
I0405 13:32:31.133846 18799 solver.cpp:237]     Train net output #0: loss = 5.23363 (* 1 = 5.23363 loss)
I0405 13:32:31.133852 18799 sgd_solver.cpp:105] Iteration 5112, lr = 0.0001
I0405 13:32:36.439949 18799 solver.cpp:218] Iteration 5124 (2.26157 iter/s, 5.30606s/12 iters), loss = 5.24152
I0405 13:32:36.440054 18799 solver.cpp:237]     Train net output #0: loss = 5.24152 (* 1 = 5.24152 loss)
I0405 13:32:36.440060 18799 sgd_solver.cpp:105] Iteration 5124, lr = 0.0001
I0405 13:32:41.729867 18799 solver.cpp:218] Iteration 5136 (2.26853 iter/s, 5.28977s/12 iters), loss = 5.25469
I0405 13:32:41.729920 18799 solver.cpp:237]     Train net output #0: loss = 5.25469 (* 1 = 5.25469 loss)
I0405 13:32:41.729928 18799 sgd_solver.cpp:105] Iteration 5136, lr = 0.0001
I0405 13:32:47.135486 18799 solver.cpp:218] Iteration 5148 (2.21995 iter/s, 5.40552s/12 iters), loss = 5.26101
I0405 13:32:47.135527 18799 solver.cpp:237]     Train net output #0: loss = 5.26101 (* 1 = 5.26101 loss)
I0405 13:32:47.135532 18799 sgd_solver.cpp:105] Iteration 5148, lr = 0.0001
I0405 13:32:51.274542 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:32:52.329785 18799 solver.cpp:218] Iteration 5160 (2.31027 iter/s, 5.19421s/12 iters), loss = 5.23627
I0405 13:32:52.329828 18799 solver.cpp:237]     Train net output #0: loss = 5.23627 (* 1 = 5.23627 loss)
I0405 13:32:52.329834 18799 sgd_solver.cpp:105] Iteration 5160, lr = 0.0001
I0405 13:32:57.455765 18799 solver.cpp:218] Iteration 5172 (2.34106 iter/s, 5.12589s/12 iters), loss = 5.26112
I0405 13:32:57.455827 18799 solver.cpp:237]     Train net output #0: loss = 5.26112 (* 1 = 5.26112 loss)
I0405 13:32:57.455840 18799 sgd_solver.cpp:105] Iteration 5172, lr = 0.0001
I0405 13:33:02.583076 18799 solver.cpp:218] Iteration 5184 (2.34046 iter/s, 5.12721s/12 iters), loss = 5.29074
I0405 13:33:02.583115 18799 solver.cpp:237]     Train net output #0: loss = 5.29074 (* 1 = 5.29074 loss)
I0405 13:33:02.583120 18799 sgd_solver.cpp:105] Iteration 5184, lr = 0.0001
I0405 13:33:07.891120 18799 solver.cpp:218] Iteration 5196 (2.26076 iter/s, 5.30795s/12 iters), loss = 5.25159
I0405 13:33:07.891289 18799 solver.cpp:237]     Train net output #0: loss = 5.25159 (* 1 = 5.25159 loss)
I0405 13:33:07.891297 18799 sgd_solver.cpp:105] Iteration 5196, lr = 0.0001
I0405 13:33:09.965574 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel
I0405 13:33:12.982192 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate
I0405 13:33:16.536551 18799 solver.cpp:330] Iteration 5202, Testing net (#0)
I0405 13:33:16.536571 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:33:18.825613 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:33:20.917940 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:33:20.917980 18799 solver.cpp:397]     Test net output #1: loss = 5.26017 (* 1 = 5.26017 loss)
I0405 13:33:22.796273 18799 solver.cpp:218] Iteration 5208 (0.805105 iter/s, 14.9049s/12 iters), loss = 5.25609
I0405 13:33:22.796325 18799 solver.cpp:237]     Train net output #0: loss = 5.25609 (* 1 = 5.25609 loss)
I0405 13:33:22.796334 18799 sgd_solver.cpp:105] Iteration 5208, lr = 0.0001
I0405 13:33:28.225039 18799 solver.cpp:218] Iteration 5220 (2.21049 iter/s, 5.42866s/12 iters), loss = 5.23765
I0405 13:33:28.225090 18799 solver.cpp:237]     Train net output #0: loss = 5.23765 (* 1 = 5.23765 loss)
I0405 13:33:28.225098 18799 sgd_solver.cpp:105] Iteration 5220, lr = 0.0001
I0405 13:33:33.654469 18799 solver.cpp:218] Iteration 5232 (2.21022 iter/s, 5.42933s/12 iters), loss = 5.24215
I0405 13:33:33.654506 18799 solver.cpp:237]     Train net output #0: loss = 5.24215 (* 1 = 5.24215 loss)
I0405 13:33:33.654512 18799 sgd_solver.cpp:105] Iteration 5232, lr = 0.0001
I0405 13:33:38.980973 18799 solver.cpp:218] Iteration 5244 (2.25292 iter/s, 5.32642s/12 iters), loss = 5.26279
I0405 13:33:38.981082 18799 solver.cpp:237]     Train net output #0: loss = 5.26279 (* 1 = 5.26279 loss)
I0405 13:33:38.981088 18799 sgd_solver.cpp:105] Iteration 5244, lr = 0.0001
I0405 13:33:44.166076 18799 solver.cpp:218] Iteration 5256 (2.31439 iter/s, 5.18495s/12 iters), loss = 5.24805
I0405 13:33:44.166117 18799 solver.cpp:237]     Train net output #0: loss = 5.24805 (* 1 = 5.24805 loss)
I0405 13:33:44.166123 18799 sgd_solver.cpp:105] Iteration 5256, lr = 0.0001
I0405 13:33:45.512075 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:33:49.585022 18799 solver.cpp:218] Iteration 5268 (2.21449 iter/s, 5.41886s/12 iters), loss = 5.24041
I0405 13:33:49.585064 18799 solver.cpp:237]     Train net output #0: loss = 5.24041 (* 1 = 5.24041 loss)
I0405 13:33:49.585070 18799 sgd_solver.cpp:105] Iteration 5268, lr = 0.0001
I0405 13:33:54.999080 18799 solver.cpp:218] Iteration 5280 (2.21649 iter/s, 5.41396s/12 iters), loss = 5.25809
I0405 13:33:54.999125 18799 solver.cpp:237]     Train net output #0: loss = 5.25809 (* 1 = 5.25809 loss)
I0405 13:33:54.999130 18799 sgd_solver.cpp:105] Iteration 5280, lr = 0.0001
I0405 13:34:00.425901 18799 solver.cpp:218] Iteration 5292 (2.21128 iter/s, 5.42672s/12 iters), loss = 5.23927
I0405 13:34:00.425956 18799 solver.cpp:237]     Train net output #0: loss = 5.23927 (* 1 = 5.23927 loss)
I0405 13:34:00.425966 18799 sgd_solver.cpp:105] Iteration 5292, lr = 0.0001
I0405 13:34:05.179387 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel
I0405 13:34:08.186522 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate
I0405 13:34:11.889134 18799 solver.cpp:330] Iteration 5304, Testing net (#0)
I0405 13:34:11.889231 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:34:14.248349 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:34:16.393988 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:34:16.394019 18799 solver.cpp:397]     Test net output #1: loss = 5.25682 (* 1 = 5.25682 loss)
I0405 13:34:16.534684 18799 solver.cpp:218] Iteration 5304 (0.744943 iter/s, 16.1086s/12 iters), loss = 5.21712
I0405 13:34:16.534734 18799 solver.cpp:237]     Train net output #0: loss = 5.21712 (* 1 = 5.21712 loss)
I0405 13:34:16.534739 18799 sgd_solver.cpp:105] Iteration 5304, lr = 0.0001
I0405 13:34:20.768147 18799 solver.cpp:218] Iteration 5316 (2.83462 iter/s, 4.23337s/12 iters), loss = 5.25807
I0405 13:34:20.768187 18799 solver.cpp:237]     Train net output #0: loss = 5.25807 (* 1 = 5.25807 loss)
I0405 13:34:20.768193 18799 sgd_solver.cpp:105] Iteration 5316, lr = 0.0001
I0405 13:34:26.006001 18799 solver.cpp:218] Iteration 5328 (2.29105 iter/s, 5.23777s/12 iters), loss = 5.2341
I0405 13:34:26.006044 18799 solver.cpp:237]     Train net output #0: loss = 5.2341 (* 1 = 5.2341 loss)
I0405 13:34:26.006050 18799 sgd_solver.cpp:105] Iteration 5328, lr = 0.0001
I0405 13:34:31.484745 18799 solver.cpp:218] Iteration 5340 (2.19032 iter/s, 5.47865s/12 iters), loss = 5.24166
I0405 13:34:31.484788 18799 solver.cpp:237]     Train net output #0: loss = 5.24166 (* 1 = 5.24166 loss)
I0405 13:34:31.484794 18799 sgd_solver.cpp:105] Iteration 5340, lr = 0.0001
I0405 13:34:36.725399 18799 solver.cpp:218] Iteration 5352 (2.28983 iter/s, 5.24056s/12 iters), loss = 5.26114
I0405 13:34:36.725446 18799 solver.cpp:237]     Train net output #0: loss = 5.26114 (* 1 = 5.26114 loss)
I0405 13:34:36.725453 18799 sgd_solver.cpp:105] Iteration 5352, lr = 0.0001
I0405 13:34:40.144635 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:34:41.725312 18799 solver.cpp:218] Iteration 5364 (2.40009 iter/s, 4.99982s/12 iters), loss = 5.22684
I0405 13:34:41.725349 18799 solver.cpp:237]     Train net output #0: loss = 5.22684 (* 1 = 5.22684 loss)
I0405 13:34:41.725354 18799 sgd_solver.cpp:105] Iteration 5364, lr = 0.0001
I0405 13:34:47.194001 18799 solver.cpp:218] Iteration 5376 (2.19434 iter/s, 5.4686s/12 iters), loss = 5.23658
I0405 13:34:47.194106 18799 solver.cpp:237]     Train net output #0: loss = 5.23658 (* 1 = 5.23658 loss)
I0405 13:34:47.194113 18799 sgd_solver.cpp:105] Iteration 5376, lr = 0.0001
I0405 13:34:52.688194 18799 solver.cpp:218] Iteration 5388 (2.18418 iter/s, 5.49404s/12 iters), loss = 5.24593
I0405 13:34:52.688231 18799 solver.cpp:237]     Train net output #0: loss = 5.24593 (* 1 = 5.24593 loss)
I0405 13:34:52.688237 18799 sgd_solver.cpp:105] Iteration 5388, lr = 0.0001
I0405 13:34:58.156322 18799 solver.cpp:218] Iteration 5400 (2.19457 iter/s, 5.46804s/12 iters), loss = 5.22228
I0405 13:34:58.156360 18799 solver.cpp:237]     Train net output #0: loss = 5.22228 (* 1 = 5.22228 loss)
I0405 13:34:58.156366 18799 sgd_solver.cpp:105] Iteration 5400, lr = 0.0001
I0405 13:35:00.248297 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel
I0405 13:35:03.273600 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate
I0405 13:35:06.577090 18799 solver.cpp:330] Iteration 5406, Testing net (#0)
I0405 13:35:06.577112 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:35:08.779486 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:35:10.873510 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:35:10.873548 18799 solver.cpp:397]     Test net output #1: loss = 5.25238 (* 1 = 5.25238 loss)
I0405 13:35:12.756127 18799 solver.cpp:218] Iteration 5412 (0.821937 iter/s, 14.5997s/12 iters), loss = 5.25194
I0405 13:35:12.756170 18799 solver.cpp:237]     Train net output #0: loss = 5.25194 (* 1 = 5.25194 loss)
I0405 13:35:12.756176 18799 sgd_solver.cpp:105] Iteration 5412, lr = 0.0001
I0405 13:35:18.108314 18799 solver.cpp:218] Iteration 5424 (2.24211 iter/s, 5.35209s/12 iters), loss = 5.23526
I0405 13:35:18.108453 18799 solver.cpp:237]     Train net output #0: loss = 5.23526 (* 1 = 5.23526 loss)
I0405 13:35:18.108460 18799 sgd_solver.cpp:105] Iteration 5424, lr = 0.0001
I0405 13:35:23.240798 18799 solver.cpp:218] Iteration 5436 (2.33813 iter/s, 5.1323s/12 iters), loss = 5.2232
I0405 13:35:23.240855 18799 solver.cpp:237]     Train net output #0: loss = 5.2232 (* 1 = 5.2232 loss)
I0405 13:35:23.240864 18799 sgd_solver.cpp:105] Iteration 5436, lr = 0.0001
I0405 13:35:28.520190 18799 solver.cpp:218] Iteration 5448 (2.27303 iter/s, 5.27929s/12 iters), loss = 5.24454
I0405 13:35:28.520231 18799 solver.cpp:237]     Train net output #0: loss = 5.24454 (* 1 = 5.24454 loss)
I0405 13:35:28.520237 18799 sgd_solver.cpp:105] Iteration 5448, lr = 0.0001
I0405 13:35:33.937077 18799 solver.cpp:218] Iteration 5460 (2.21533 iter/s, 5.41679s/12 iters), loss = 5.2215
I0405 13:35:33.937119 18799 solver.cpp:237]     Train net output #0: loss = 5.2215 (* 1 = 5.2215 loss)
I0405 13:35:33.937124 18799 sgd_solver.cpp:105] Iteration 5460, lr = 0.0001
I0405 13:35:34.439304 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:35:39.231784 18799 solver.cpp:218] Iteration 5472 (2.26645 iter/s, 5.29462s/12 iters), loss = 5.2462
I0405 13:35:39.231827 18799 solver.cpp:237]     Train net output #0: loss = 5.2462 (* 1 = 5.2462 loss)
I0405 13:35:39.231832 18799 sgd_solver.cpp:105] Iteration 5472, lr = 0.0001
I0405 13:35:44.544386 18799 solver.cpp:218] Iteration 5484 (2.25882 iter/s, 5.31251s/12 iters), loss = 5.25622
I0405 13:35:44.544428 18799 solver.cpp:237]     Train net output #0: loss = 5.25622 (* 1 = 5.25622 loss)
I0405 13:35:44.544433 18799 sgd_solver.cpp:105] Iteration 5484, lr = 0.0001
I0405 13:35:49.707144 18799 solver.cpp:218] Iteration 5496 (2.32438 iter/s, 5.16267s/12 iters), loss = 5.24469
I0405 13:35:49.707235 18799 solver.cpp:237]     Train net output #0: loss = 5.24469 (* 1 = 5.24469 loss)
I0405 13:35:49.707243 18799 sgd_solver.cpp:105] Iteration 5496, lr = 0.0001
I0405 13:35:54.514628 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel
I0405 13:35:57.625586 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate
I0405 13:36:01.048920 18799 solver.cpp:330] Iteration 5508, Testing net (#0)
I0405 13:36:01.048943 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:36:03.180842 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:36:05.361452 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:36:05.361488 18799 solver.cpp:397]     Test net output #1: loss = 5.24715 (* 1 = 5.24715 loss)
I0405 13:36:05.503301 18799 solver.cpp:218] Iteration 5508 (0.759688 iter/s, 15.796s/12 iters), loss = 5.23397
I0405 13:36:05.503350 18799 solver.cpp:237]     Train net output #0: loss = 5.23397 (* 1 = 5.23397 loss)
I0405 13:36:05.503355 18799 sgd_solver.cpp:105] Iteration 5508, lr = 0.0001
I0405 13:36:09.628845 18799 solver.cpp:218] Iteration 5520 (2.90877 iter/s, 4.12546s/12 iters), loss = 5.21977
I0405 13:36:09.628907 18799 solver.cpp:237]     Train net output #0: loss = 5.21977 (* 1 = 5.21977 loss)
I0405 13:36:09.628916 18799 sgd_solver.cpp:105] Iteration 5520, lr = 0.0001
I0405 13:36:12.303803 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:36:14.860823 18799 solver.cpp:218] Iteration 5532 (2.29363 iter/s, 5.23188s/12 iters), loss = 5.2379
I0405 13:36:14.860867 18799 solver.cpp:237]     Train net output #0: loss = 5.2379 (* 1 = 5.2379 loss)
I0405 13:36:14.860872 18799 sgd_solver.cpp:105] Iteration 5532, lr = 0.0001
I0405 13:36:20.239825 18799 solver.cpp:218] Iteration 5544 (2.23094 iter/s, 5.3789s/12 iters), loss = 5.233
I0405 13:36:20.239972 18799 solver.cpp:237]     Train net output #0: loss = 5.233 (* 1 = 5.233 loss)
I0405 13:36:20.239981 18799 sgd_solver.cpp:105] Iteration 5544, lr = 0.0001
I0405 13:36:25.292194 18799 solver.cpp:218] Iteration 5556 (2.37521 iter/s, 5.05218s/12 iters), loss = 5.2515
I0405 13:36:25.292240 18799 solver.cpp:237]     Train net output #0: loss = 5.2515 (* 1 = 5.2515 loss)
I0405 13:36:25.292246 18799 sgd_solver.cpp:105] Iteration 5556, lr = 0.0001
I0405 13:36:28.086057 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:36:30.601163 18799 solver.cpp:218] Iteration 5568 (2.26037 iter/s, 5.30888s/12 iters), loss = 5.23646
I0405 13:36:30.601208 18799 solver.cpp:237]     Train net output #0: loss = 5.23646 (* 1 = 5.23646 loss)
I0405 13:36:30.601217 18799 sgd_solver.cpp:105] Iteration 5568, lr = 0.0001
I0405 13:36:35.966614 18799 solver.cpp:218] Iteration 5580 (2.23657 iter/s, 5.36536s/12 iters), loss = 5.23635
I0405 13:36:35.966657 18799 solver.cpp:237]     Train net output #0: loss = 5.23635 (* 1 = 5.23635 loss)
I0405 13:36:35.966665 18799 sgd_solver.cpp:105] Iteration 5580, lr = 0.0001
I0405 13:36:41.133953 18799 solver.cpp:218] Iteration 5592 (2.32232 iter/s, 5.16725s/12 iters), loss = 5.22653
I0405 13:36:41.133993 18799 solver.cpp:237]     Train net output #0: loss = 5.22653 (* 1 = 5.22653 loss)
I0405 13:36:41.133999 18799 sgd_solver.cpp:105] Iteration 5592, lr = 0.0001
I0405 13:36:46.516631 18799 solver.cpp:218] Iteration 5604 (2.22941 iter/s, 5.38259s/12 iters), loss = 5.23406
I0405 13:36:46.516669 18799 solver.cpp:237]     Train net output #0: loss = 5.23406 (* 1 = 5.23406 loss)
I0405 13:36:46.516675 18799 sgd_solver.cpp:105] Iteration 5604, lr = 0.0001
I0405 13:36:48.710372 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel
I0405 13:36:51.651093 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate
I0405 13:36:55.104769 18799 solver.cpp:330] Iteration 5610, Testing net (#0)
I0405 13:36:55.104797 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:36:57.423913 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:36:59.703071 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:36:59.703100 18799 solver.cpp:397]     Test net output #1: loss = 5.2404 (* 1 = 5.2404 loss)
I0405 13:37:01.644174 18799 solver.cpp:218] Iteration 5616 (0.793263 iter/s, 15.1274s/12 iters), loss = 5.23406
I0405 13:37:01.644217 18799 solver.cpp:237]     Train net output #0: loss = 5.23406 (* 1 = 5.23406 loss)
I0405 13:37:01.644223 18799 sgd_solver.cpp:105] Iteration 5616, lr = 0.0001
I0405 13:37:06.995975 18799 solver.cpp:218] Iteration 5628 (2.24227 iter/s, 5.35171s/12 iters), loss = 5.2689
I0405 13:37:06.996016 18799 solver.cpp:237]     Train net output #0: loss = 5.2689 (* 1 = 5.2689 loss)
I0405 13:37:06.996022 18799 sgd_solver.cpp:105] Iteration 5628, lr = 0.0001
I0405 13:37:12.342070 18799 solver.cpp:218] Iteration 5640 (2.24467 iter/s, 5.346s/12 iters), loss = 5.24209
I0405 13:37:12.342124 18799 solver.cpp:237]     Train net output #0: loss = 5.24209 (* 1 = 5.24209 loss)
I0405 13:37:12.342133 18799 sgd_solver.cpp:105] Iteration 5640, lr = 0.0001
I0405 13:37:17.717708 18799 solver.cpp:218] Iteration 5652 (2.23234 iter/s, 5.37553s/12 iters), loss = 5.24229
I0405 13:37:17.717751 18799 solver.cpp:237]     Train net output #0: loss = 5.24229 (* 1 = 5.24229 loss)
I0405 13:37:17.717754 18799 sgd_solver.cpp:105] Iteration 5652, lr = 0.0001
I0405 13:37:22.889143 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:37:23.112345 18799 solver.cpp:218] Iteration 5664 (2.22447 iter/s, 5.39455s/12 iters), loss = 5.24795
I0405 13:37:23.112396 18799 solver.cpp:237]     Train net output #0: loss = 5.24795 (* 1 = 5.24795 loss)
I0405 13:37:23.112401 18799 sgd_solver.cpp:105] Iteration 5664, lr = 0.0001
I0405 13:37:28.530238 18799 solver.cpp:218] Iteration 5676 (2.21492 iter/s, 5.4178s/12 iters), loss = 5.19546
I0405 13:37:28.530279 18799 solver.cpp:237]     Train net output #0: loss = 5.19546 (* 1 = 5.19546 loss)
I0405 13:37:28.530285 18799 sgd_solver.cpp:105] Iteration 5676, lr = 0.0001
I0405 13:37:34.045517 18799 solver.cpp:218] Iteration 5688 (2.17581 iter/s, 5.51519s/12 iters), loss = 5.23191
I0405 13:37:34.045557 18799 solver.cpp:237]     Train net output #0: loss = 5.23191 (* 1 = 5.23191 loss)
I0405 13:37:34.045562 18799 sgd_solver.cpp:105] Iteration 5688, lr = 0.0001
I0405 13:37:39.231747 18799 solver.cpp:218] Iteration 5700 (2.31386 iter/s, 5.18614s/12 iters), loss = 5.24833
I0405 13:37:39.231791 18799 solver.cpp:237]     Train net output #0: loss = 5.24833 (* 1 = 5.24833 loss)
I0405 13:37:39.231797 18799 sgd_solver.cpp:105] Iteration 5700, lr = 0.0001
I0405 13:37:44.114310 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel
I0405 13:37:47.200445 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate
I0405 13:37:51.457597 18799 solver.cpp:330] Iteration 5712, Testing net (#0)
I0405 13:37:51.457617 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:37:53.669137 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:37:55.974174 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:37:55.974205 18799 solver.cpp:397]     Test net output #1: loss = 5.2316 (* 1 = 5.2316 loss)
I0405 13:37:56.116128 18799 solver.cpp:218] Iteration 5712 (0.710723 iter/s, 16.8842s/12 iters), loss = 5.21725
I0405 13:37:56.116183 18799 solver.cpp:237]     Train net output #0: loss = 5.21725 (* 1 = 5.21725 loss)
I0405 13:37:56.116192 18799 sgd_solver.cpp:105] Iteration 5712, lr = 0.0001
I0405 13:38:00.497196 18799 solver.cpp:218] Iteration 5724 (2.73912 iter/s, 4.38097s/12 iters), loss = 5.20348
I0405 13:38:00.497236 18799 solver.cpp:237]     Train net output #0: loss = 5.20348 (* 1 = 5.20348 loss)
I0405 13:38:00.497241 18799 sgd_solver.cpp:105] Iteration 5724, lr = 0.0001
I0405 13:38:05.970736 18799 solver.cpp:218] Iteration 5736 (2.1924 iter/s, 5.47345s/12 iters), loss = 5.17657
I0405 13:38:05.970772 18799 solver.cpp:237]     Train net output #0: loss = 5.17657 (* 1 = 5.17657 loss)
I0405 13:38:05.970778 18799 sgd_solver.cpp:105] Iteration 5736, lr = 0.0001
I0405 13:38:11.193620 18799 solver.cpp:218] Iteration 5748 (2.29762 iter/s, 5.2228s/12 iters), loss = 5.21425
I0405 13:38:11.193661 18799 solver.cpp:237]     Train net output #0: loss = 5.21425 (* 1 = 5.21425 loss)
I0405 13:38:11.193667 18799 sgd_solver.cpp:105] Iteration 5748, lr = 0.0001
I0405 13:38:16.443806 18799 solver.cpp:218] Iteration 5760 (2.28567 iter/s, 5.2501s/12 iters), loss = 5.18641
I0405 13:38:16.443847 18799 solver.cpp:237]     Train net output #0: loss = 5.18641 (* 1 = 5.18641 loss)
I0405 13:38:16.443853 18799 sgd_solver.cpp:105] Iteration 5760, lr = 0.0001
I0405 13:38:18.357399 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:38:21.563160 18799 solver.cpp:218] Iteration 5772 (2.34409 iter/s, 5.11926s/12 iters), loss = 5.24815
I0405 13:38:21.563202 18799 solver.cpp:237]     Train net output #0: loss = 5.24815 (* 1 = 5.24815 loss)
I0405 13:38:21.563208 18799 sgd_solver.cpp:105] Iteration 5772, lr = 0.0001
I0405 13:38:26.858665 18799 solver.cpp:218] Iteration 5784 (2.26611 iter/s, 5.29542s/12 iters), loss = 5.21532
I0405 13:38:26.858755 18799 solver.cpp:237]     Train net output #0: loss = 5.21532 (* 1 = 5.21532 loss)
I0405 13:38:26.858762 18799 sgd_solver.cpp:105] Iteration 5784, lr = 0.0001
I0405 13:38:31.947515 18799 solver.cpp:218] Iteration 5796 (2.35816 iter/s, 5.08872s/12 iters), loss = 5.26217
I0405 13:38:31.947554 18799 solver.cpp:237]     Train net output #0: loss = 5.26217 (* 1 = 5.26217 loss)
I0405 13:38:31.947559 18799 sgd_solver.cpp:105] Iteration 5796, lr = 0.0001
I0405 13:38:37.066287 18799 solver.cpp:218] Iteration 5808 (2.34435 iter/s, 5.11868s/12 iters), loss = 5.2151
I0405 13:38:37.066332 18799 solver.cpp:237]     Train net output #0: loss = 5.2151 (* 1 = 5.2151 loss)
I0405 13:38:37.066339 18799 sgd_solver.cpp:105] Iteration 5808, lr = 0.0001
I0405 13:38:39.257419 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel
I0405 13:38:42.291513 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate
I0405 13:38:46.388232 18799 solver.cpp:330] Iteration 5814, Testing net (#0)
I0405 13:38:46.388252 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:38:48.542781 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:38:50.891424 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00735294
I0405 13:38:50.891466 18799 solver.cpp:397]     Test net output #1: loss = 5.22093 (* 1 = 5.22093 loss)
I0405 13:38:52.734627 18799 solver.cpp:218] Iteration 5820 (0.765883 iter/s, 15.6682s/12 iters), loss = 5.16058
I0405 13:38:52.734674 18799 solver.cpp:237]     Train net output #0: loss = 5.16058 (* 1 = 5.16058 loss)
I0405 13:38:52.734683 18799 sgd_solver.cpp:105] Iteration 5820, lr = 0.0001
I0405 13:38:58.125032 18799 solver.cpp:218] Iteration 5832 (2.22622 iter/s, 5.39031s/12 iters), loss = 5.21301
I0405 13:38:58.125195 18799 solver.cpp:237]     Train net output #0: loss = 5.21301 (* 1 = 5.21301 loss)
I0405 13:38:58.125202 18799 sgd_solver.cpp:105] Iteration 5832, lr = 0.0001
I0405 13:39:03.299072 18799 solver.cpp:218] Iteration 5844 (2.31937 iter/s, 5.17383s/12 iters), loss = 5.1893
I0405 13:39:03.299124 18799 solver.cpp:237]     Train net output #0: loss = 5.1893 (* 1 = 5.1893 loss)
I0405 13:39:03.299130 18799 sgd_solver.cpp:105] Iteration 5844, lr = 0.0001
I0405 13:39:08.727396 18799 solver.cpp:218] Iteration 5856 (2.21067 iter/s, 5.42823s/12 iters), loss = 5.2027
I0405 13:39:08.727435 18799 solver.cpp:237]     Train net output #0: loss = 5.2027 (* 1 = 5.2027 loss)
I0405 13:39:08.727440 18799 sgd_solver.cpp:105] Iteration 5856, lr = 0.0001
I0405 13:39:13.019762 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:39:13.892446 18799 solver.cpp:218] Iteration 5868 (2.32335 iter/s, 5.16496s/12 iters), loss = 5.18642
I0405 13:39:13.892488 18799 solver.cpp:237]     Train net output #0: loss = 5.18642 (* 1 = 5.18642 loss)
I0405 13:39:13.892493 18799 sgd_solver.cpp:105] Iteration 5868, lr = 0.0001
I0405 13:39:19.108253 18799 solver.cpp:218] Iteration 5880 (2.30074 iter/s, 5.21571s/12 iters), loss = 5.21984
I0405 13:39:19.108311 18799 solver.cpp:237]     Train net output #0: loss = 5.21984 (* 1 = 5.21984 loss)
I0405 13:39:19.108321 18799 sgd_solver.cpp:105] Iteration 5880, lr = 0.0001
I0405 13:39:24.440836 18799 solver.cpp:218] Iteration 5892 (2.25036 iter/s, 5.33248s/12 iters), loss = 5.21496
I0405 13:39:24.440902 18799 solver.cpp:237]     Train net output #0: loss = 5.21496 (* 1 = 5.21496 loss)
I0405 13:39:24.440912 18799 sgd_solver.cpp:105] Iteration 5892, lr = 0.0001
I0405 13:39:29.831487 18799 solver.cpp:218] Iteration 5904 (2.22612 iter/s, 5.39054s/12 iters), loss = 5.17276
I0405 13:39:29.831601 18799 solver.cpp:237]     Train net output #0: loss = 5.17276 (* 1 = 5.17276 loss)
I0405 13:39:29.831607 18799 sgd_solver.cpp:105] Iteration 5904, lr = 0.0001
I0405 13:39:34.661532 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel
I0405 13:39:37.772850 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate
I0405 13:39:41.655498 18799 solver.cpp:330] Iteration 5916, Testing net (#0)
I0405 13:39:41.655519 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:39:43.764876 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:39:46.070534 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 13:39:46.070561 18799 solver.cpp:397]     Test net output #1: loss = 5.20759 (* 1 = 5.20759 loss)
I0405 13:39:46.209486 18799 solver.cpp:218] Iteration 5916 (0.7327 iter/s, 16.3778s/12 iters), loss = 5.22393
I0405 13:39:46.209544 18799 solver.cpp:237]     Train net output #0: loss = 5.22393 (* 1 = 5.22393 loss)
I0405 13:39:46.209551 18799 sgd_solver.cpp:105] Iteration 5916, lr = 0.0001
I0405 13:39:50.576637 18799 solver.cpp:218] Iteration 5928 (2.74785 iter/s, 4.36705s/12 iters), loss = 5.23449
I0405 13:39:50.576678 18799 solver.cpp:237]     Train net output #0: loss = 5.23449 (* 1 = 5.23449 loss)
I0405 13:39:50.576683 18799 sgd_solver.cpp:105] Iteration 5928, lr = 0.0001
I0405 13:39:55.797780 18799 solver.cpp:218] Iteration 5940 (2.29839 iter/s, 5.22105s/12 iters), loss = 5.2043
I0405 13:39:55.797832 18799 solver.cpp:237]     Train net output #0: loss = 5.2043 (* 1 = 5.2043 loss)
I0405 13:39:55.797840 18799 sgd_solver.cpp:105] Iteration 5940, lr = 0.0001
I0405 13:40:00.954836 18799 solver.cpp:218] Iteration 5952 (2.32695 iter/s, 5.15696s/12 iters), loss = 5.19486
I0405 13:40:00.954969 18799 solver.cpp:237]     Train net output #0: loss = 5.19486 (* 1 = 5.19486 loss)
I0405 13:40:00.954977 18799 sgd_solver.cpp:105] Iteration 5952, lr = 0.0001
I0405 13:40:06.391644 18799 solver.cpp:218] Iteration 5964 (2.20725 iter/s, 5.43663s/12 iters), loss = 5.19404
I0405 13:40:06.391691 18799 solver.cpp:237]     Train net output #0: loss = 5.19404 (* 1 = 5.19404 loss)
I0405 13:40:06.391698 18799 sgd_solver.cpp:105] Iteration 5964, lr = 0.0001
I0405 13:40:07.782145 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:40:11.576948 18799 solver.cpp:218] Iteration 5976 (2.31428 iter/s, 5.18521s/12 iters), loss = 5.20057
I0405 13:40:11.576990 18799 solver.cpp:237]     Train net output #0: loss = 5.20057 (* 1 = 5.20057 loss)
I0405 13:40:11.576997 18799 sgd_solver.cpp:105] Iteration 5976, lr = 0.0001
I0405 13:40:16.705384 18799 solver.cpp:218] Iteration 5988 (2.33993 iter/s, 5.12835s/12 iters), loss = 5.19696
I0405 13:40:16.705422 18799 solver.cpp:237]     Train net output #0: loss = 5.19696 (* 1 = 5.19696 loss)
I0405 13:40:16.705428 18799 sgd_solver.cpp:105] Iteration 5988, lr = 0.0001
I0405 13:40:21.966336 18799 solver.cpp:218] Iteration 6000 (2.28099 iter/s, 5.26086s/12 iters), loss = 5.14337
I0405 13:40:21.966377 18799 solver.cpp:237]     Train net output #0: loss = 5.14337 (* 1 = 5.14337 loss)
I0405 13:40:21.966384 18799 sgd_solver.cpp:105] Iteration 6000, lr = 0.0001
I0405 13:40:27.241958 18799 solver.cpp:218] Iteration 6012 (2.27465 iter/s, 5.27553s/12 iters), loss = 5.1179
I0405 13:40:27.242012 18799 solver.cpp:237]     Train net output #0: loss = 5.1179 (* 1 = 5.1179 loss)
I0405 13:40:27.242022 18799 sgd_solver.cpp:105] Iteration 6012, lr = 0.0001
I0405 13:40:29.410194 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel
I0405 13:40:32.465850 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate
I0405 13:40:36.470378 18799 solver.cpp:330] Iteration 6018, Testing net (#0)
I0405 13:40:36.470399 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:40:38.536981 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:40:41.071620 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 13:40:41.071655 18799 solver.cpp:397]     Test net output #1: loss = 5.19329 (* 1 = 5.19329 loss)
I0405 13:40:42.991427 18799 solver.cpp:218] Iteration 6024 (0.761938 iter/s, 15.7493s/12 iters), loss = 5.2322
I0405 13:40:42.991472 18799 solver.cpp:237]     Train net output #0: loss = 5.2322 (* 1 = 5.2322 loss)
I0405 13:40:42.991478 18799 sgd_solver.cpp:105] Iteration 6024, lr = 0.0001
I0405 13:40:48.375385 18799 solver.cpp:218] Iteration 6036 (2.22889 iter/s, 5.38386s/12 iters), loss = 5.18616
I0405 13:40:48.375450 18799 solver.cpp:237]     Train net output #0: loss = 5.18616 (* 1 = 5.18616 loss)
I0405 13:40:48.375459 18799 sgd_solver.cpp:105] Iteration 6036, lr = 0.0001
I0405 13:40:53.745395 18799 solver.cpp:218] Iteration 6048 (2.23468 iter/s, 5.3699s/12 iters), loss = 5.18807
I0405 13:40:53.745440 18799 solver.cpp:237]     Train net output #0: loss = 5.18807 (* 1 = 5.18807 loss)
I0405 13:40:53.745446 18799 sgd_solver.cpp:105] Iteration 6048, lr = 0.0001
I0405 13:40:58.965829 18799 solver.cpp:218] Iteration 6060 (2.2987 iter/s, 5.22034s/12 iters), loss = 5.18563
I0405 13:40:58.965885 18799 solver.cpp:237]     Train net output #0: loss = 5.18563 (* 1 = 5.18563 loss)
I0405 13:40:58.965893 18799 sgd_solver.cpp:105] Iteration 6060, lr = 0.0001
I0405 13:41:02.686190 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:41:04.121096 18799 solver.cpp:218] Iteration 6072 (2.32776 iter/s, 5.15517s/12 iters), loss = 5.17348
I0405 13:41:04.121140 18799 solver.cpp:237]     Train net output #0: loss = 5.17348 (* 1 = 5.17348 loss)
I0405 13:41:04.121145 18799 sgd_solver.cpp:105] Iteration 6072, lr = 0.0001
I0405 13:41:09.503052 18799 solver.cpp:218] Iteration 6084 (2.22971 iter/s, 5.38186s/12 iters), loss = 5.16687
I0405 13:41:09.503103 18799 solver.cpp:237]     Train net output #0: loss = 5.16687 (* 1 = 5.16687 loss)
I0405 13:41:09.503111 18799 sgd_solver.cpp:105] Iteration 6084, lr = 0.0001
I0405 13:41:14.637629 18799 solver.cpp:218] Iteration 6096 (2.33714 iter/s, 5.13448s/12 iters), loss = 5.16297
I0405 13:41:14.637683 18799 solver.cpp:237]     Train net output #0: loss = 5.16297 (* 1 = 5.16297 loss)
I0405 13:41:14.637691 18799 sgd_solver.cpp:105] Iteration 6096, lr = 0.0001
I0405 13:41:19.883432 18799 solver.cpp:218] Iteration 6108 (2.28759 iter/s, 5.2457s/12 iters), loss = 5.1431
I0405 13:41:19.883482 18799 solver.cpp:237]     Train net output #0: loss = 5.1431 (* 1 = 5.1431 loss)
I0405 13:41:19.883488 18799 sgd_solver.cpp:105] Iteration 6108, lr = 0.0001
I0405 13:41:24.534000 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel
I0405 13:41:27.518931 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate
I0405 13:41:31.604859 18799 solver.cpp:330] Iteration 6120, Testing net (#0)
I0405 13:41:31.604890 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:41:33.648151 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:41:36.178865 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00857843
I0405 13:41:36.178906 18799 solver.cpp:397]     Test net output #1: loss = 5.18204 (* 1 = 5.18204 loss)
I0405 13:41:36.308804 18799 solver.cpp:218] Iteration 6120 (0.730584 iter/s, 16.4252s/12 iters), loss = 5.19092
I0405 13:41:36.308846 18799 solver.cpp:237]     Train net output #0: loss = 5.19092 (* 1 = 5.19092 loss)
I0405 13:41:36.308852 18799 sgd_solver.cpp:105] Iteration 6120, lr = 0.0001
I0405 13:41:40.804118 18799 solver.cpp:218] Iteration 6132 (2.6695 iter/s, 4.49523s/12 iters), loss = 5.12514
I0405 13:41:40.804157 18799 solver.cpp:237]     Train net output #0: loss = 5.12514 (* 1 = 5.12514 loss)
I0405 13:41:40.804163 18799 sgd_solver.cpp:105] Iteration 6132, lr = 0.0001
I0405 13:41:46.266120 18799 solver.cpp:218] Iteration 6144 (2.19703 iter/s, 5.46191s/12 iters), loss = 5.11933
I0405 13:41:46.266172 18799 solver.cpp:237]     Train net output #0: loss = 5.11933 (* 1 = 5.11933 loss)
I0405 13:41:46.266181 18799 sgd_solver.cpp:105] Iteration 6144, lr = 0.0001
I0405 13:41:51.635890 18799 solver.cpp:218] Iteration 6156 (2.23477 iter/s, 5.36967s/12 iters), loss = 5.16838
I0405 13:41:51.635941 18799 solver.cpp:237]     Train net output #0: loss = 5.16838 (* 1 = 5.16838 loss)
I0405 13:41:51.635948 18799 sgd_solver.cpp:105] Iteration 6156, lr = 0.0001
I0405 13:41:56.786901 18799 solver.cpp:218] Iteration 6168 (2.32968 iter/s, 5.15091s/12 iters), loss = 5.17029
I0405 13:41:56.786947 18799 solver.cpp:237]     Train net output #0: loss = 5.17029 (* 1 = 5.17029 loss)
I0405 13:41:56.786953 18799 sgd_solver.cpp:105] Iteration 6168, lr = 0.0001
I0405 13:41:57.350627 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:42:02.021252 18799 solver.cpp:218] Iteration 6180 (2.29259 iter/s, 5.23426s/12 iters), loss = 5.12569
I0405 13:42:02.021291 18799 solver.cpp:237]     Train net output #0: loss = 5.12569 (* 1 = 5.12569 loss)
I0405 13:42:02.021296 18799 sgd_solver.cpp:105] Iteration 6180, lr = 0.0001
I0405 13:42:07.289222 18799 solver.cpp:218] Iteration 6192 (2.27795 iter/s, 5.26789s/12 iters), loss = 5.21726
I0405 13:42:07.289355 18799 solver.cpp:237]     Train net output #0: loss = 5.21726 (* 1 = 5.21726 loss)
I0405 13:42:07.289361 18799 sgd_solver.cpp:105] Iteration 6192, lr = 0.0001
I0405 13:42:12.317605 18799 solver.cpp:218] Iteration 6204 (2.38654 iter/s, 5.02821s/12 iters), loss = 5.14686
I0405 13:42:12.317648 18799 solver.cpp:237]     Train net output #0: loss = 5.14686 (* 1 = 5.14686 loss)
I0405 13:42:12.317654 18799 sgd_solver.cpp:105] Iteration 6204, lr = 0.0001
I0405 13:42:17.754822 18799 solver.cpp:218] Iteration 6216 (2.20705 iter/s, 5.43713s/12 iters), loss = 5.17902
I0405 13:42:17.754874 18799 solver.cpp:237]     Train net output #0: loss = 5.17902 (* 1 = 5.17902 loss)
I0405 13:42:17.754884 18799 sgd_solver.cpp:105] Iteration 6216, lr = 0.0001
I0405 13:42:19.982609 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel
I0405 13:42:22.932839 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate
I0405 13:42:26.824935 18799 solver.cpp:330] Iteration 6222, Testing net (#0)
I0405 13:42:26.824963 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:42:28.710772 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:42:30.025147 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:42:31.186900 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00796569
I0405 13:42:31.186933 18799 solver.cpp:397]     Test net output #1: loss = 5.17171 (* 1 = 5.17171 loss)
I0405 13:42:33.177397 18799 solver.cpp:218] Iteration 6228 (0.778088 iter/s, 15.4224s/12 iters), loss = 5.14507
I0405 13:42:33.177436 18799 solver.cpp:237]     Train net output #0: loss = 5.14507 (* 1 = 5.14507 loss)
I0405 13:42:33.177443 18799 sgd_solver.cpp:105] Iteration 6228, lr = 0.0001
I0405 13:42:38.313226 18799 solver.cpp:218] Iteration 6240 (2.33656 iter/s, 5.13574s/12 iters), loss = 5.1077
I0405 13:42:38.313339 18799 solver.cpp:237]     Train net output #0: loss = 5.1077 (* 1 = 5.1077 loss)
I0405 13:42:38.313354 18799 sgd_solver.cpp:105] Iteration 6240, lr = 0.0001
I0405 13:42:43.680071 18799 solver.cpp:218] Iteration 6252 (2.23602 iter/s, 5.36669s/12 iters), loss = 5.10774
I0405 13:42:43.680124 18799 solver.cpp:237]     Train net output #0: loss = 5.10774 (* 1 = 5.10774 loss)
I0405 13:42:43.680131 18799 sgd_solver.cpp:105] Iteration 6252, lr = 0.0001
I0405 13:42:48.935842 18799 solver.cpp:218] Iteration 6264 (2.28325 iter/s, 5.25567s/12 iters), loss = 5.17746
I0405 13:42:48.935886 18799 solver.cpp:237]     Train net output #0: loss = 5.17746 (* 1 = 5.17746 loss)
I0405 13:42:48.935892 18799 sgd_solver.cpp:105] Iteration 6264, lr = 0.0001
I0405 13:42:51.877111 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:42:54.362695 18799 solver.cpp:218] Iteration 6276 (2.21127 iter/s, 5.42676s/12 iters), loss = 5.14481
I0405 13:42:54.362746 18799 solver.cpp:237]     Train net output #0: loss = 5.14481 (* 1 = 5.14481 loss)
I0405 13:42:54.362756 18799 sgd_solver.cpp:105] Iteration 6276, lr = 0.0001
I0405 13:42:59.385517 18799 solver.cpp:218] Iteration 6288 (2.38914 iter/s, 5.02273s/12 iters), loss = 5.17476
I0405 13:42:59.385558 18799 solver.cpp:237]     Train net output #0: loss = 5.17476 (* 1 = 5.17476 loss)
I0405 13:42:59.385565 18799 sgd_solver.cpp:105] Iteration 6288, lr = 0.0001
I0405 13:43:04.458673 18799 solver.cpp:218] Iteration 6300 (2.36544 iter/s, 5.07306s/12 iters), loss = 5.19977
I0405 13:43:04.458734 18799 solver.cpp:237]     Train net output #0: loss = 5.19977 (* 1 = 5.19977 loss)
I0405 13:43:04.458741 18799 sgd_solver.cpp:105] Iteration 6300, lr = 0.0001
I0405 13:43:09.961762 18799 solver.cpp:218] Iteration 6312 (2.18064 iter/s, 5.50298s/12 iters), loss = 5.16257
I0405 13:43:09.961903 18799 solver.cpp:237]     Train net output #0: loss = 5.16257 (* 1 = 5.16257 loss)
I0405 13:43:09.961911 18799 sgd_solver.cpp:105] Iteration 6312, lr = 0.0001
I0405 13:43:14.818574 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel
I0405 13:43:17.865051 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate
I0405 13:43:21.808670 18799 solver.cpp:330] Iteration 6324, Testing net (#0)
I0405 13:43:21.808686 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:43:23.702605 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:43:26.303346 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00857843
I0405 13:43:26.303373 18799 solver.cpp:397]     Test net output #1: loss = 5.1633 (* 1 = 5.1633 loss)
I0405 13:43:26.445068 18799 solver.cpp:218] Iteration 6324 (0.72802 iter/s, 16.4831s/12 iters), loss = 5.18215
I0405 13:43:26.445118 18799 solver.cpp:237]     Train net output #0: loss = 5.18215 (* 1 = 5.18215 loss)
I0405 13:43:26.445123 18799 sgd_solver.cpp:105] Iteration 6324, lr = 0.0001
I0405 13:43:30.730337 18799 solver.cpp:218] Iteration 6336 (2.80035 iter/s, 4.28518s/12 iters), loss = 5.2177
I0405 13:43:30.730381 18799 solver.cpp:237]     Train net output #0: loss = 5.2177 (* 1 = 5.2177 loss)
I0405 13:43:30.730388 18799 sgd_solver.cpp:105] Iteration 6336, lr = 0.0001
I0405 13:43:36.190977 18799 solver.cpp:218] Iteration 6348 (2.19758 iter/s, 5.46055s/12 iters), loss = 5.19097
I0405 13:43:36.191030 18799 solver.cpp:237]     Train net output #0: loss = 5.19097 (* 1 = 5.19097 loss)
I0405 13:43:36.191036 18799 sgd_solver.cpp:105] Iteration 6348, lr = 0.0001
I0405 13:43:41.349242 18799 solver.cpp:218] Iteration 6360 (2.32641 iter/s, 5.15817s/12 iters), loss = 5.16867
I0405 13:43:41.349334 18799 solver.cpp:237]     Train net output #0: loss = 5.16867 (* 1 = 5.16867 loss)
I0405 13:43:41.349340 18799 sgd_solver.cpp:105] Iteration 6360, lr = 0.0001
I0405 13:43:46.560864 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:43:46.754699 18799 solver.cpp:218] Iteration 6372 (2.22004 iter/s, 5.40531s/12 iters), loss = 5.20068
I0405 13:43:46.754760 18799 solver.cpp:237]     Train net output #0: loss = 5.20068 (* 1 = 5.20068 loss)
I0405 13:43:46.754768 18799 sgd_solver.cpp:105] Iteration 6372, lr = 0.0001
I0405 13:43:52.240658 18799 solver.cpp:218] Iteration 6384 (2.18744 iter/s, 5.48585s/12 iters), loss = 5.13044
I0405 13:43:52.240700 18799 solver.cpp:237]     Train net output #0: loss = 5.13044 (* 1 = 5.13044 loss)
I0405 13:43:52.240705 18799 sgd_solver.cpp:105] Iteration 6384, lr = 0.0001
I0405 13:43:57.558068 18799 solver.cpp:218] Iteration 6396 (2.25678 iter/s, 5.31732s/12 iters), loss = 5.13172
I0405 13:43:57.558118 18799 solver.cpp:237]     Train net output #0: loss = 5.13172 (* 1 = 5.13172 loss)
I0405 13:43:57.558125 18799 sgd_solver.cpp:105] Iteration 6396, lr = 0.0001
I0405 13:44:02.691924 18799 solver.cpp:218] Iteration 6408 (2.33747 iter/s, 5.13376s/12 iters), loss = 5.18115
I0405 13:44:02.691980 18799 solver.cpp:237]     Train net output #0: loss = 5.18115 (* 1 = 5.18115 loss)
I0405 13:44:02.691988 18799 sgd_solver.cpp:105] Iteration 6408, lr = 0.0001
I0405 13:44:07.988551 18799 solver.cpp:218] Iteration 6420 (2.26564 iter/s, 5.29652s/12 iters), loss = 5.10526
I0405 13:44:07.988598 18799 solver.cpp:237]     Train net output #0: loss = 5.10526 (* 1 = 5.10526 loss)
I0405 13:44:07.988605 18799 sgd_solver.cpp:105] Iteration 6420, lr = 0.0001
I0405 13:44:10.165915 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel
I0405 13:44:13.256731 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate
I0405 13:44:17.022758 18799 solver.cpp:330] Iteration 6426, Testing net (#0)
I0405 13:44:17.022778 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:44:18.837970 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:44:21.353107 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 13:44:21.353137 18799 solver.cpp:397]     Test net output #1: loss = 5.15357 (* 1 = 5.15357 loss)
I0405 13:44:23.299930 18799 solver.cpp:218] Iteration 6432 (0.783739 iter/s, 15.3112s/12 iters), loss = 5.17449
I0405 13:44:23.299978 18799 solver.cpp:237]     Train net output #0: loss = 5.17449 (* 1 = 5.17449 loss)
I0405 13:44:23.299983 18799 sgd_solver.cpp:105] Iteration 6432, lr = 0.0001
I0405 13:44:28.647236 18799 solver.cpp:218] Iteration 6444 (2.24416 iter/s, 5.34721s/12 iters), loss = 5.08543
I0405 13:44:28.647276 18799 solver.cpp:237]     Train net output #0: loss = 5.08543 (* 1 = 5.08543 loss)
I0405 13:44:28.647282 18799 sgd_solver.cpp:105] Iteration 6444, lr = 0.0001
I0405 13:44:33.993088 18799 solver.cpp:218] Iteration 6456 (2.24477 iter/s, 5.34576s/12 iters), loss = 5.10942
I0405 13:44:33.993145 18799 solver.cpp:237]     Train net output #0: loss = 5.10942 (* 1 = 5.10942 loss)
I0405 13:44:33.993153 18799 sgd_solver.cpp:105] Iteration 6456, lr = 0.0001
I0405 13:44:39.235088 18799 solver.cpp:218] Iteration 6468 (2.28925 iter/s, 5.24189s/12 iters), loss = 5.11725
I0405 13:44:39.235142 18799 solver.cpp:237]     Train net output #0: loss = 5.11725 (* 1 = 5.11725 loss)
I0405 13:44:39.235149 18799 sgd_solver.cpp:105] Iteration 6468, lr = 0.0001
I0405 13:44:41.361132 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:44:44.515413 18799 solver.cpp:218] Iteration 6480 (2.27263 iter/s, 5.28023s/12 iters), loss = 5.19072
I0405 13:44:44.515539 18799 solver.cpp:237]     Train net output #0: loss = 5.19072 (* 1 = 5.19072 loss)
I0405 13:44:44.515547 18799 sgd_solver.cpp:105] Iteration 6480, lr = 0.0001
I0405 13:44:49.775816 18799 solver.cpp:218] Iteration 6492 (2.28127 iter/s, 5.26023s/12 iters), loss = 5.17929
I0405 13:44:49.775854 18799 solver.cpp:237]     Train net output #0: loss = 5.17929 (* 1 = 5.17929 loss)
I0405 13:44:49.775859 18799 sgd_solver.cpp:105] Iteration 6492, lr = 0.0001
I0405 13:44:55.118667 18799 solver.cpp:218] Iteration 6504 (2.24603 iter/s, 5.34277s/12 iters), loss = 5.26038
I0405 13:44:55.118710 18799 solver.cpp:237]     Train net output #0: loss = 5.26038 (* 1 = 5.26038 loss)
I0405 13:44:55.118716 18799 sgd_solver.cpp:105] Iteration 6504, lr = 0.0001
I0405 13:45:00.566336 18799 solver.cpp:218] Iteration 6516 (2.20282 iter/s, 5.44758s/12 iters), loss = 5.17768
I0405 13:45:00.566385 18799 solver.cpp:237]     Train net output #0: loss = 5.17768 (* 1 = 5.17768 loss)
I0405 13:45:00.566393 18799 sgd_solver.cpp:105] Iteration 6516, lr = 0.0001
I0405 13:45:05.355175 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel
I0405 13:45:08.516228 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate
I0405 13:45:12.753731 18799 solver.cpp:330] Iteration 6528, Testing net (#0)
I0405 13:45:12.753751 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:45:14.506906 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:45:17.105733 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00919118
I0405 13:45:17.105825 18799 solver.cpp:397]     Test net output #1: loss = 5.14786 (* 1 = 5.14786 loss)
I0405 13:45:17.237560 18799 solver.cpp:218] Iteration 6528 (0.71981 iter/s, 16.6711s/12 iters), loss = 5.1437
I0405 13:45:17.237613 18799 solver.cpp:237]     Train net output #0: loss = 5.1437 (* 1 = 5.1437 loss)
I0405 13:45:17.237620 18799 sgd_solver.cpp:105] Iteration 6528, lr = 0.0001
I0405 13:45:21.506222 18799 solver.cpp:218] Iteration 6540 (2.81125 iter/s, 4.26857s/12 iters), loss = 5.1965
I0405 13:45:21.506263 18799 solver.cpp:237]     Train net output #0: loss = 5.1965 (* 1 = 5.1965 loss)
I0405 13:45:21.506268 18799 sgd_solver.cpp:105] Iteration 6540, lr = 0.0001
I0405 13:45:26.770941 18799 solver.cpp:218] Iteration 6552 (2.27936 iter/s, 5.26464s/12 iters), loss = 5.11222
I0405 13:45:26.770979 18799 solver.cpp:237]     Train net output #0: loss = 5.11222 (* 1 = 5.11222 loss)
I0405 13:45:26.770984 18799 sgd_solver.cpp:105] Iteration 6552, lr = 0.0001
I0405 13:45:32.041146 18799 solver.cpp:218] Iteration 6564 (2.27699 iter/s, 5.27012s/12 iters), loss = 5.15799
I0405 13:45:32.041203 18799 solver.cpp:237]     Train net output #0: loss = 5.15799 (* 1 = 5.15799 loss)
I0405 13:45:32.041211 18799 sgd_solver.cpp:105] Iteration 6564, lr = 0.0001
I0405 13:45:36.293524 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:45:37.144510 18799 solver.cpp:218] Iteration 6576 (2.35144 iter/s, 5.10326s/12 iters), loss = 5.10324
I0405 13:45:37.144556 18799 solver.cpp:237]     Train net output #0: loss = 5.10324 (* 1 = 5.10324 loss)
I0405 13:45:37.144563 18799 sgd_solver.cpp:105] Iteration 6576, lr = 0.0001
I0405 13:45:42.341320 18799 solver.cpp:218] Iteration 6588 (2.30915 iter/s, 5.19672s/12 iters), loss = 5.23717
I0405 13:45:42.341359 18799 solver.cpp:237]     Train net output #0: loss = 5.23717 (* 1 = 5.23717 loss)
I0405 13:45:42.341364 18799 sgd_solver.cpp:105] Iteration 6588, lr = 0.0001
I0405 13:45:47.535058 18799 solver.cpp:218] Iteration 6600 (2.31051 iter/s, 5.19365s/12 iters), loss = 5.16625
I0405 13:45:47.535223 18799 solver.cpp:237]     Train net output #0: loss = 5.16625 (* 1 = 5.16625 loss)
I0405 13:45:47.535233 18799 sgd_solver.cpp:105] Iteration 6600, lr = 0.0001
I0405 13:45:52.870293 18799 solver.cpp:218] Iteration 6612 (2.24929 iter/s, 5.33503s/12 iters), loss = 5.10173
I0405 13:45:52.870333 18799 solver.cpp:237]     Train net output #0: loss = 5.10173 (* 1 = 5.10173 loss)
I0405 13:45:52.870339 18799 sgd_solver.cpp:105] Iteration 6612, lr = 0.0001
I0405 13:45:58.239249 18799 solver.cpp:218] Iteration 6624 (2.23511 iter/s, 5.36887s/12 iters), loss = 5.15968
I0405 13:45:58.239289 18799 solver.cpp:237]     Train net output #0: loss = 5.15968 (* 1 = 5.15968 loss)
I0405 13:45:58.239293 18799 sgd_solver.cpp:105] Iteration 6624, lr = 0.0001
I0405 13:46:00.457557 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel
I0405 13:46:03.536702 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate
I0405 13:46:08.250160 18799 solver.cpp:330] Iteration 6630, Testing net (#0)
I0405 13:46:08.250180 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:46:09.975131 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:46:12.526576 18799 solver.cpp:397]     Test net output #0: accuracy = 0.00980392
I0405 13:46:12.526612 18799 solver.cpp:397]     Test net output #1: loss = 5.13855 (* 1 = 5.13855 loss)
I0405 13:46:14.544536 18799 solver.cpp:218] Iteration 6636 (0.735964 iter/s, 16.3051s/12 iters), loss = 5.17201
I0405 13:46:14.544582 18799 solver.cpp:237]     Train net output #0: loss = 5.17201 (* 1 = 5.17201 loss)
I0405 13:46:14.544589 18799 sgd_solver.cpp:105] Iteration 6636, lr = 0.0001
I0405 13:46:19.559159 18799 solver.cpp:218] Iteration 6648 (2.39304 iter/s, 5.01453s/12 iters), loss = 5.18029
I0405 13:46:19.559249 18799 solver.cpp:237]     Train net output #0: loss = 5.18029 (* 1 = 5.18029 loss)
I0405 13:46:19.559255 18799 sgd_solver.cpp:105] Iteration 6648, lr = 0.0001
I0405 13:46:24.836385 18799 solver.cpp:218] Iteration 6660 (2.27398 iter/s, 5.27709s/12 iters), loss = 5.1844
I0405 13:46:24.836441 18799 solver.cpp:237]     Train net output #0: loss = 5.1844 (* 1 = 5.1844 loss)
I0405 13:46:24.836452 18799 sgd_solver.cpp:105] Iteration 6660, lr = 0.0001
I0405 13:46:30.108418 18799 solver.cpp:218] Iteration 6672 (2.27621 iter/s, 5.27193s/12 iters), loss = 5.1363
I0405 13:46:30.108467 18799 solver.cpp:237]     Train net output #0: loss = 5.1363 (* 1 = 5.1363 loss)
I0405 13:46:30.108474 18799 sgd_solver.cpp:105] Iteration 6672, lr = 0.0001
I0405 13:46:31.552546 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:46:35.611356 18799 solver.cpp:218] Iteration 6684 (2.18069 iter/s, 5.50283s/12 iters), loss = 5.1431
I0405 13:46:35.611413 18799 solver.cpp:237]     Train net output #0: loss = 5.1431 (* 1 = 5.1431 loss)
I0405 13:46:35.611423 18799 sgd_solver.cpp:105] Iteration 6684, lr = 0.0001
I0405 13:46:40.974421 18799 solver.cpp:218] Iteration 6696 (2.23757 iter/s, 5.36297s/12 iters), loss = 5.1643
I0405 13:46:40.974459 18799 solver.cpp:237]     Train net output #0: loss = 5.1643 (* 1 = 5.1643 loss)
I0405 13:46:40.974464 18799 sgd_solver.cpp:105] Iteration 6696, lr = 0.0001
I0405 13:46:46.037181 18799 solver.cpp:218] Iteration 6708 (2.37029 iter/s, 5.06267s/12 iters), loss = 5.15285
I0405 13:46:46.037225 18799 solver.cpp:237]     Train net output #0: loss = 5.15285 (* 1 = 5.15285 loss)
I0405 13:46:46.037231 18799 sgd_solver.cpp:105] Iteration 6708, lr = 0.0001
I0405 13:46:51.401675 18799 solver.cpp:218] Iteration 6720 (2.23697 iter/s, 5.3644s/12 iters), loss = 5.0344
I0405 13:46:51.401811 18799 solver.cpp:237]     Train net output #0: loss = 5.0344 (* 1 = 5.0344 loss)
I0405 13:46:51.401818 18799 sgd_solver.cpp:105] Iteration 6720, lr = 0.0001
I0405 13:46:56.135653 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel
I0405 13:47:00.393790 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate
I0405 13:47:04.092085 18799 solver.cpp:330] Iteration 6732, Testing net (#0)
I0405 13:47:04.092105 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:47:05.844849 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:47:08.558463 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0110294
I0405 13:47:08.558501 18799 solver.cpp:397]     Test net output #1: loss = 5.13248 (* 1 = 5.13248 loss)
I0405 13:47:08.700842 18799 solver.cpp:218] Iteration 6732 (0.693685 iter/s, 17.2989s/12 iters), loss = 5.13746
I0405 13:47:08.700911 18799 solver.cpp:237]     Train net output #0: loss = 5.13746 (* 1 = 5.13746 loss)
I0405 13:47:08.700919 18799 sgd_solver.cpp:105] Iteration 6732, lr = 0.0001
I0405 13:47:12.966914 18799 solver.cpp:218] Iteration 6744 (2.81296 iter/s, 4.26597s/12 iters), loss = 5.14456
I0405 13:47:12.966951 18799 solver.cpp:237]     Train net output #0: loss = 5.14456 (* 1 = 5.14456 loss)
I0405 13:47:12.966958 18799 sgd_solver.cpp:105] Iteration 6744, lr = 0.0001
I0405 13:47:18.330426 18799 solver.cpp:218] Iteration 6756 (2.23738 iter/s, 5.36342s/12 iters), loss = 5.12669
I0405 13:47:18.330476 18799 solver.cpp:237]     Train net output #0: loss = 5.12669 (* 1 = 5.12669 loss)
I0405 13:47:18.330483 18799 sgd_solver.cpp:105] Iteration 6756, lr = 0.0001
I0405 13:47:23.586555 18799 solver.cpp:218] Iteration 6768 (2.28309 iter/s, 5.25603s/12 iters), loss = 5.13917
I0405 13:47:23.586644 18799 solver.cpp:237]     Train net output #0: loss = 5.13917 (* 1 = 5.13917 loss)
I0405 13:47:23.586652 18799 sgd_solver.cpp:105] Iteration 6768, lr = 0.0001
I0405 13:47:27.456272 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:47:29.081566 18799 solver.cpp:218] Iteration 6780 (2.18385 iter/s, 5.49487s/12 iters), loss = 5.12162
I0405 13:47:29.081609 18799 solver.cpp:237]     Train net output #0: loss = 5.12162 (* 1 = 5.12162 loss)
I0405 13:47:29.081615 18799 sgd_solver.cpp:105] Iteration 6780, lr = 0.0001
I0405 13:47:34.235236 18799 solver.cpp:218] Iteration 6792 (2.32848 iter/s, 5.15357s/12 iters), loss = 5.08687
I0405 13:47:34.235280 18799 solver.cpp:237]     Train net output #0: loss = 5.08687 (* 1 = 5.08687 loss)
I0405 13:47:34.235285 18799 sgd_solver.cpp:105] Iteration 6792, lr = 0.0001
I0405 13:47:39.414359 18799 solver.cpp:218] Iteration 6804 (2.31704 iter/s, 5.17903s/12 iters), loss = 5.14325
I0405 13:47:39.414410 18799 solver.cpp:237]     Train net output #0: loss = 5.14325 (* 1 = 5.14325 loss)
I0405 13:47:39.414417 18799 sgd_solver.cpp:105] Iteration 6804, lr = 0.0001
I0405 13:47:44.498644 18799 solver.cpp:218] Iteration 6816 (2.36026 iter/s, 5.08418s/12 iters), loss = 5.13061
I0405 13:47:44.498703 18799 solver.cpp:237]     Train net output #0: loss = 5.13061 (* 1 = 5.13061 loss)
I0405 13:47:44.498711 18799 sgd_solver.cpp:105] Iteration 6816, lr = 0.0001
I0405 13:47:49.542824 18799 solver.cpp:218] Iteration 6828 (2.37903 iter/s, 5.04408s/12 iters), loss = 5.12119
I0405 13:47:49.542861 18799 solver.cpp:237]     Train net output #0: loss = 5.12119 (* 1 = 5.12119 loss)
I0405 13:47:49.542868 18799 sgd_solver.cpp:105] Iteration 6828, lr = 0.0001
I0405 13:47:51.627557 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel
I0405 13:47:56.448024 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate
I0405 13:48:00.249648 18799 solver.cpp:330] Iteration 6834, Testing net (#0)
I0405 13:48:00.249668 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:48:01.888871 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:48:04.523622 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0122549
I0405 13:48:04.523660 18799 solver.cpp:397]     Test net output #1: loss = 5.12859 (* 1 = 5.12859 loss)
I0405 13:48:06.511732 18799 solver.cpp:218] Iteration 6840 (0.707182 iter/s, 16.9688s/12 iters), loss = 5.05499
I0405 13:48:06.511782 18799 solver.cpp:237]     Train net output #0: loss = 5.05499 (* 1 = 5.05499 loss)
I0405 13:48:06.511790 18799 sgd_solver.cpp:105] Iteration 6840, lr = 0.0001
I0405 13:48:11.749388 18799 solver.cpp:218] Iteration 6852 (2.29114 iter/s, 5.23756s/12 iters), loss = 5.0997
I0405 13:48:11.749440 18799 solver.cpp:237]     Train net output #0: loss = 5.0997 (* 1 = 5.0997 loss)
I0405 13:48:11.749449 18799 sgd_solver.cpp:105] Iteration 6852, lr = 0.0001
I0405 13:48:17.066359 18799 solver.cpp:218] Iteration 6864 (2.25697 iter/s, 5.31687s/12 iters), loss = 5.15091
I0405 13:48:17.066406 18799 solver.cpp:237]     Train net output #0: loss = 5.15091 (* 1 = 5.15091 loss)
I0405 13:48:17.066413 18799 sgd_solver.cpp:105] Iteration 6864, lr = 0.0001
I0405 13:48:22.384754 18799 solver.cpp:218] Iteration 6876 (2.25636 iter/s, 5.31831s/12 iters), loss = 5.12366
I0405 13:48:22.384791 18799 solver.cpp:237]     Train net output #0: loss = 5.12366 (* 1 = 5.12366 loss)
I0405 13:48:22.384796 18799 sgd_solver.cpp:105] Iteration 6876, lr = 0.0001
I0405 13:48:22.892904 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:48:27.455142 18799 solver.cpp:218] Iteration 6888 (2.36672 iter/s, 5.0703s/12 iters), loss = 5.06994
I0405 13:48:27.455262 18799 solver.cpp:237]     Train net output #0: loss = 5.06994 (* 1 = 5.06994 loss)
I0405 13:48:27.455271 18799 sgd_solver.cpp:105] Iteration 6888, lr = 0.0001
I0405 13:48:32.648790 18799 solver.cpp:218] Iteration 6900 (2.31059 iter/s, 5.19348s/12 iters), loss = 5.12798
I0405 13:48:32.648846 18799 solver.cpp:237]     Train net output #0: loss = 5.12798 (* 1 = 5.12798 loss)
I0405 13:48:32.648854 18799 sgd_solver.cpp:105] Iteration 6900, lr = 0.0001
I0405 13:48:38.212648 18799 solver.cpp:218] Iteration 6912 (2.15682 iter/s, 5.56375s/12 iters), loss = 5.16206
I0405 13:48:38.212689 18799 solver.cpp:237]     Train net output #0: loss = 5.16206 (* 1 = 5.16206 loss)
I0405 13:48:38.212695 18799 sgd_solver.cpp:105] Iteration 6912, lr = 0.0001
I0405 13:48:43.403710 18799 solver.cpp:218] Iteration 6924 (2.31171 iter/s, 5.19097s/12 iters), loss = 5.09204
I0405 13:48:43.403755 18799 solver.cpp:237]     Train net output #0: loss = 5.09204 (* 1 = 5.09204 loss)
I0405 13:48:43.403760 18799 sgd_solver.cpp:105] Iteration 6924, lr = 0.0001
I0405 13:48:47.833493 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel
I0405 13:48:51.456653 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate
I0405 13:48:55.222149 18799 solver.cpp:330] Iteration 6936, Testing net (#0)
I0405 13:48:55.222172 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:48:55.800097 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:48:56.861420 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:48:59.562475 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0140931
I0405 13:48:59.562908 18799 solver.cpp:397]     Test net output #1: loss = 5.12152 (* 1 = 5.12152 loss)
I0405 13:48:59.697763 18799 solver.cpp:218] Iteration 6936 (0.736472 iter/s, 16.2939s/12 iters), loss = 5.12349
I0405 13:48:59.697811 18799 solver.cpp:237]     Train net output #0: loss = 5.12349 (* 1 = 5.12349 loss)
I0405 13:48:59.697816 18799 sgd_solver.cpp:105] Iteration 6936, lr = 0.0001
I0405 13:49:04.147200 18799 solver.cpp:218] Iteration 6948 (2.69703 iter/s, 4.44935s/12 iters), loss = 5.08548
I0405 13:49:04.147244 18799 solver.cpp:237]     Train net output #0: loss = 5.08548 (* 1 = 5.08548 loss)
I0405 13:49:04.147250 18799 sgd_solver.cpp:105] Iteration 6948, lr = 0.0001
I0405 13:49:09.447609 18799 solver.cpp:218] Iteration 6960 (2.26402 iter/s, 5.30031s/12 iters), loss = 5.13238
I0405 13:49:09.447662 18799 solver.cpp:237]     Train net output #0: loss = 5.13238 (* 1 = 5.13238 loss)
I0405 13:49:09.447671 18799 sgd_solver.cpp:105] Iteration 6960, lr = 0.0001
I0405 13:49:14.636283 18799 solver.cpp:218] Iteration 6972 (2.31277 iter/s, 5.18858s/12 iters), loss = 5.13874
I0405 13:49:14.636327 18799 solver.cpp:237]     Train net output #0: loss = 5.13874 (* 1 = 5.13874 loss)
I0405 13:49:14.636332 18799 sgd_solver.cpp:105] Iteration 6972, lr = 0.0001
I0405 13:49:17.568147 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:49:20.047765 18799 solver.cpp:218] Iteration 6984 (2.21755 iter/s, 5.41139s/12 iters), loss = 5.06274
I0405 13:49:20.047821 18799 solver.cpp:237]     Train net output #0: loss = 5.06274 (* 1 = 5.06274 loss)
I0405 13:49:20.047829 18799 sgd_solver.cpp:105] Iteration 6984, lr = 0.0001
I0405 13:49:25.254274 18799 solver.cpp:218] Iteration 6996 (2.30485 iter/s, 5.20641s/12 iters), loss = 5.11477
I0405 13:49:25.254329 18799 solver.cpp:237]     Train net output #0: loss = 5.11477 (* 1 = 5.11477 loss)
I0405 13:49:25.254338 18799 sgd_solver.cpp:105] Iteration 6996, lr = 0.0001
I0405 13:49:30.373764 18799 solver.cpp:218] Iteration 7008 (2.34403 iter/s, 5.11939s/12 iters), loss = 5.19459
I0405 13:49:30.373888 18799 solver.cpp:237]     Train net output #0: loss = 5.19459 (* 1 = 5.19459 loss)
I0405 13:49:30.374142 18799 sgd_solver.cpp:105] Iteration 7008, lr = 0.0001
I0405 13:49:35.632927 18799 solver.cpp:218] Iteration 7020 (2.28181 iter/s, 5.25899s/12 iters), loss = 5.17866
I0405 13:49:35.632982 18799 solver.cpp:237]     Train net output #0: loss = 5.17866 (* 1 = 5.17866 loss)
I0405 13:49:35.632990 18799 sgd_solver.cpp:105] Iteration 7020, lr = 0.0001
I0405 13:49:40.852430 18799 solver.cpp:218] Iteration 7032 (2.29911 iter/s, 5.21941s/12 iters), loss = 5.15137
I0405 13:49:40.852465 18799 solver.cpp:237]     Train net output #0: loss = 5.15137 (* 1 = 5.15137 loss)
I0405 13:49:40.852471 18799 sgd_solver.cpp:105] Iteration 7032, lr = 0.0001
I0405 13:49:42.841059 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel
I0405 13:49:46.750015 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate
I0405 13:49:50.471860 18799 solver.cpp:330] Iteration 7038, Testing net (#0)
I0405 13:49:50.471887 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:49:52.093294 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:49:54.938823 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0159314
I0405 13:49:54.938851 18799 solver.cpp:397]     Test net output #1: loss = 5.11664 (* 1 = 5.11664 loss)
I0405 13:49:56.863332 18799 solver.cpp:218] Iteration 7044 (0.749496 iter/s, 16.0108s/12 iters), loss = 5.18735
I0405 13:49:56.863370 18799 solver.cpp:237]     Train net output #0: loss = 5.18735 (* 1 = 5.18735 loss)
I0405 13:49:56.863376 18799 sgd_solver.cpp:105] Iteration 7044, lr = 0.0001
I0405 13:50:02.077574 18799 solver.cpp:218] Iteration 7056 (2.30143 iter/s, 5.21416s/12 iters), loss = 5.09835
I0405 13:50:02.077694 18799 solver.cpp:237]     Train net output #0: loss = 5.09835 (* 1 = 5.09835 loss)
I0405 13:50:02.077704 18799 sgd_solver.cpp:105] Iteration 7056, lr = 0.0001
I0405 13:50:07.209295 18799 solver.cpp:218] Iteration 7068 (2.33847 iter/s, 5.13155s/12 iters), loss = 5.07553
I0405 13:50:07.209347 18799 solver.cpp:237]     Train net output #0: loss = 5.07553 (* 1 = 5.07553 loss)
I0405 13:50:07.209354 18799 sgd_solver.cpp:105] Iteration 7068, lr = 0.0001
I0405 13:50:12.305300 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:50:12.473419 18799 solver.cpp:218] Iteration 7080 (2.27962 iter/s, 5.26403s/12 iters), loss = 5.18645
I0405 13:50:12.473464 18799 solver.cpp:237]     Train net output #0: loss = 5.18645 (* 1 = 5.18645 loss)
I0405 13:50:12.473470 18799 sgd_solver.cpp:105] Iteration 7080, lr = 0.0001
I0405 13:50:17.775367 18799 solver.cpp:218] Iteration 7092 (2.26336 iter/s, 5.30185s/12 iters), loss = 5.06623
I0405 13:50:17.775422 18799 solver.cpp:237]     Train net output #0: loss = 5.06623 (* 1 = 5.06623 loss)
I0405 13:50:17.775430 18799 sgd_solver.cpp:105] Iteration 7092, lr = 0.0001
I0405 13:50:23.057188 18799 solver.cpp:218] Iteration 7104 (2.27199 iter/s, 5.28172s/12 iters), loss = 5.08505
I0405 13:50:23.057243 18799 solver.cpp:237]     Train net output #0: loss = 5.08505 (* 1 = 5.08505 loss)
I0405 13:50:23.057252 18799 sgd_solver.cpp:105] Iteration 7104, lr = 0.0001
I0405 13:50:28.326288 18799 solver.cpp:218] Iteration 7116 (2.27747 iter/s, 5.269s/12 iters), loss = 5.15155
I0405 13:50:28.326329 18799 solver.cpp:237]     Train net output #0: loss = 5.15155 (* 1 = 5.15155 loss)
I0405 13:50:28.326335 18799 sgd_solver.cpp:105] Iteration 7116, lr = 0.0001
I0405 13:50:33.562516 18799 solver.cpp:218] Iteration 7128 (2.29177 iter/s, 5.23614s/12 iters), loss = 5.08264
I0405 13:50:33.562680 18799 solver.cpp:237]     Train net output #0: loss = 5.08264 (* 1 = 5.08264 loss)
I0405 13:50:33.562687 18799 sgd_solver.cpp:105] Iteration 7128, lr = 0.0001
I0405 13:50:38.405544 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel
I0405 13:50:42.562929 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate
I0405 13:50:46.293282 18799 solver.cpp:330] Iteration 7140, Testing net (#0)
I0405 13:50:46.293311 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:50:47.881956 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:50:50.632577 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0177696
I0405 13:50:50.632611 18799 solver.cpp:397]     Test net output #1: loss = 5.10967 (* 1 = 5.10967 loss)
I0405 13:50:50.764811 18799 solver.cpp:218] Iteration 7140 (0.697592 iter/s, 17.202s/12 iters), loss = 5.1158
I0405 13:50:50.766362 18799 solver.cpp:237]     Train net output #0: loss = 5.1158 (* 1 = 5.1158 loss)
I0405 13:50:50.766376 18799 sgd_solver.cpp:105] Iteration 7140, lr = 0.0001
I0405 13:50:54.884814 18799 solver.cpp:218] Iteration 7152 (2.91374 iter/s, 4.11842s/12 iters), loss = 5.08587
I0405 13:50:54.884856 18799 solver.cpp:237]     Train net output #0: loss = 5.08587 (* 1 = 5.08587 loss)
I0405 13:50:54.884862 18799 sgd_solver.cpp:105] Iteration 7152, lr = 0.0001
I0405 13:51:00.374441 18799 solver.cpp:218] Iteration 7164 (2.18598 iter/s, 5.48953s/12 iters), loss = 5.03019
I0405 13:51:00.374485 18799 solver.cpp:237]     Train net output #0: loss = 5.03019 (* 1 = 5.03019 loss)
I0405 13:51:00.374490 18799 sgd_solver.cpp:105] Iteration 7164, lr = 0.0001
I0405 13:51:05.668278 18799 solver.cpp:218] Iteration 7176 (2.26683 iter/s, 5.29374s/12 iters), loss = 5.07058
I0405 13:51:05.668390 18799 solver.cpp:237]     Train net output #0: loss = 5.07058 (* 1 = 5.07058 loss)
I0405 13:51:05.668398 18799 sgd_solver.cpp:105] Iteration 7176, lr = 0.0001
I0405 13:51:07.890988 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:51:11.000350 18799 solver.cpp:218] Iteration 7188 (2.2506 iter/s, 5.33192s/12 iters), loss = 5.15982
I0405 13:51:11.000392 18799 solver.cpp:237]     Train net output #0: loss = 5.15982 (* 1 = 5.15982 loss)
I0405 13:51:11.000398 18799 sgd_solver.cpp:105] Iteration 7188, lr = 0.0001
I0405 13:51:16.211724 18799 solver.cpp:218] Iteration 7200 (2.3027 iter/s, 5.21128s/12 iters), loss = 5.13289
I0405 13:51:16.211771 18799 solver.cpp:237]     Train net output #0: loss = 5.13289 (* 1 = 5.13289 loss)
I0405 13:51:16.211778 18799 sgd_solver.cpp:105] Iteration 7200, lr = 0.0001
I0405 13:51:21.561039 18799 solver.cpp:218] Iteration 7212 (2.24332 iter/s, 5.34922s/12 iters), loss = 5.20588
I0405 13:51:21.561080 18799 solver.cpp:237]     Train net output #0: loss = 5.20588 (* 1 = 5.20588 loss)
I0405 13:51:21.561086 18799 sgd_solver.cpp:105] Iteration 7212, lr = 0.0001
I0405 13:51:26.872403 18799 solver.cpp:218] Iteration 7224 (2.25935 iter/s, 5.31127s/12 iters), loss = 5.10096
I0405 13:51:26.872452 18799 solver.cpp:237]     Train net output #0: loss = 5.10096 (* 1 = 5.10096 loss)
I0405 13:51:26.872462 18799 sgd_solver.cpp:105] Iteration 7224, lr = 0.0001
I0405 13:51:32.242592 18799 solver.cpp:218] Iteration 7236 (2.2346 iter/s, 5.37009s/12 iters), loss = 5.09699
I0405 13:51:32.242656 18799 solver.cpp:237]     Train net output #0: loss = 5.09699 (* 1 = 5.09699 loss)
I0405 13:51:32.242666 18799 sgd_solver.cpp:105] Iteration 7236, lr = 0.0001
I0405 13:51:34.443069 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel
I0405 13:51:38.046561 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate
I0405 13:51:41.721549 18799 solver.cpp:330] Iteration 7242, Testing net (#0)
I0405 13:51:41.721570 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:51:43.203390 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:51:45.993731 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0177696
I0405 13:51:45.993767 18799 solver.cpp:397]     Test net output #1: loss = 5.10115 (* 1 = 5.10115 loss)
I0405 13:51:47.821291 18799 solver.cpp:218] Iteration 7248 (0.770291 iter/s, 15.5785s/12 iters), loss = 5.17215
I0405 13:51:47.821349 18799 solver.cpp:237]     Train net output #0: loss = 5.17215 (* 1 = 5.17215 loss)
I0405 13:51:47.821358 18799 sgd_solver.cpp:105] Iteration 7248, lr = 0.0001
I0405 13:51:53.063999 18799 solver.cpp:218] Iteration 7260 (2.28894 iter/s, 5.2426s/12 iters), loss = 5.11266
I0405 13:51:53.064040 18799 solver.cpp:237]     Train net output #0: loss = 5.11266 (* 1 = 5.11266 loss)
I0405 13:51:53.064046 18799 sgd_solver.cpp:105] Iteration 7260, lr = 0.0001
I0405 13:51:58.373010 18799 solver.cpp:218] Iteration 7272 (2.26035 iter/s, 5.30892s/12 iters), loss = 5.05845
I0405 13:51:58.373050 18799 solver.cpp:237]     Train net output #0: loss = 5.05845 (* 1 = 5.05845 loss)
I0405 13:51:58.373060 18799 sgd_solver.cpp:105] Iteration 7272, lr = 0.0001
I0405 13:52:02.954157 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:52:03.770805 18799 solver.cpp:218] Iteration 7284 (2.22317 iter/s, 5.39771s/12 iters), loss = 5.18041
I0405 13:52:03.770859 18799 solver.cpp:237]     Train net output #0: loss = 5.18041 (* 1 = 5.18041 loss)
I0405 13:52:03.770866 18799 sgd_solver.cpp:105] Iteration 7284, lr = 0.0001
I0405 13:52:09.178505 18799 solver.cpp:218] Iteration 7296 (2.2191 iter/s, 5.4076s/12 iters), loss = 5.16786
I0405 13:52:09.178627 18799 solver.cpp:237]     Train net output #0: loss = 5.16786 (* 1 = 5.16786 loss)
I0405 13:52:09.178637 18799 sgd_solver.cpp:105] Iteration 7296, lr = 0.0001
I0405 13:52:14.545408 18799 solver.cpp:218] Iteration 7308 (2.236 iter/s, 5.36674s/12 iters), loss = 5.10771
I0405 13:52:14.545464 18799 solver.cpp:237]     Train net output #0: loss = 5.10771 (* 1 = 5.10771 loss)
I0405 13:52:14.545472 18799 sgd_solver.cpp:105] Iteration 7308, lr = 0.0001
I0405 13:52:19.920040 18799 solver.cpp:218] Iteration 7320 (2.23275 iter/s, 5.37453s/12 iters), loss = 5.05571
I0405 13:52:19.920086 18799 solver.cpp:237]     Train net output #0: loss = 5.05571 (* 1 = 5.05571 loss)
I0405 13:52:19.920094 18799 sgd_solver.cpp:105] Iteration 7320, lr = 0.0001
I0405 13:52:25.315279 18799 solver.cpp:218] Iteration 7332 (2.22422 iter/s, 5.39515s/12 iters), loss = 5.16962
I0405 13:52:25.315320 18799 solver.cpp:237]     Train net output #0: loss = 5.16962 (* 1 = 5.16962 loss)
I0405 13:52:25.315327 18799 sgd_solver.cpp:105] Iteration 7332, lr = 0.0001
I0405 13:52:29.955713 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel
I0405 13:52:33.547721 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate
I0405 13:52:37.388711 18799 solver.cpp:330] Iteration 7344, Testing net (#0)
I0405 13:52:37.388736 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:52:38.999110 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:52:41.933992 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0177696
I0405 13:52:41.934137 18799 solver.cpp:397]     Test net output #1: loss = 5.09594 (* 1 = 5.09594 loss)
I0405 13:52:42.075359 18799 solver.cpp:218] Iteration 7344 (0.715993 iter/s, 16.7599s/12 iters), loss = 5.17987
I0405 13:52:42.075405 18799 solver.cpp:237]     Train net output #0: loss = 5.17987 (* 1 = 5.17987 loss)
I0405 13:52:42.075410 18799 sgd_solver.cpp:105] Iteration 7344, lr = 0.0001
I0405 13:52:46.530774 18799 solver.cpp:218] Iteration 7356 (2.6934 iter/s, 4.45533s/12 iters), loss = 5.07949
I0405 13:52:46.530813 18799 solver.cpp:237]     Train net output #0: loss = 5.07949 (* 1 = 5.07949 loss)
I0405 13:52:46.530819 18799 sgd_solver.cpp:105] Iteration 7356, lr = 0.0001
I0405 13:52:51.933809 18799 solver.cpp:218] Iteration 7368 (2.22101 iter/s, 5.40295s/12 iters), loss = 5.11106
I0405 13:52:51.933852 18799 solver.cpp:237]     Train net output #0: loss = 5.11106 (* 1 = 5.11106 loss)
I0405 13:52:51.933861 18799 sgd_solver.cpp:105] Iteration 7368, lr = 0.0001
I0405 13:52:57.328277 18799 solver.cpp:218] Iteration 7380 (2.22454 iter/s, 5.39438s/12 iters), loss = 5.10449
I0405 13:52:57.328315 18799 solver.cpp:237]     Train net output #0: loss = 5.10449 (* 1 = 5.10449 loss)
I0405 13:52:57.328321 18799 sgd_solver.cpp:105] Iteration 7380, lr = 0.0001
I0405 13:52:58.754624 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:53:02.349037 18799 solver.cpp:218] Iteration 7392 (2.39012 iter/s, 5.02068s/12 iters), loss = 5.1178
I0405 13:53:02.349077 18799 solver.cpp:237]     Train net output #0: loss = 5.1178 (* 1 = 5.1178 loss)
I0405 13:53:02.349083 18799 sgd_solver.cpp:105] Iteration 7392, lr = 0.0001
I0405 13:53:07.709923 18799 solver.cpp:218] Iteration 7404 (2.23847 iter/s, 5.3608s/12 iters), loss = 5.04109
I0405 13:53:07.709971 18799 solver.cpp:237]     Train net output #0: loss = 5.04109 (* 1 = 5.04109 loss)
I0405 13:53:07.709980 18799 sgd_solver.cpp:105] Iteration 7404, lr = 0.0001
I0405 13:53:12.964242 18799 solver.cpp:218] Iteration 7416 (2.28388 iter/s, 5.25422s/12 iters), loss = 5.03078
I0405 13:53:12.964368 18799 solver.cpp:237]     Train net output #0: loss = 5.03078 (* 1 = 5.03078 loss)
I0405 13:53:12.964376 18799 sgd_solver.cpp:105] Iteration 7416, lr = 0.0001
I0405 13:53:18.199867 18799 solver.cpp:218] Iteration 7428 (2.29207 iter/s, 5.23545s/12 iters), loss = 5.05199
I0405 13:53:18.199913 18799 solver.cpp:237]     Train net output #0: loss = 5.05199 (* 1 = 5.05199 loss)
I0405 13:53:18.199920 18799 sgd_solver.cpp:105] Iteration 7428, lr = 0.0001
I0405 13:53:23.616212 18799 solver.cpp:218] Iteration 7440 (2.21555 iter/s, 5.41625s/12 iters), loss = 5.05275
I0405 13:53:23.616255 18799 solver.cpp:237]     Train net output #0: loss = 5.05275 (* 1 = 5.05275 loss)
I0405 13:53:23.616261 18799 sgd_solver.cpp:105] Iteration 7440, lr = 0.0001
I0405 13:53:25.540395 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel
I0405 13:53:30.489919 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate
I0405 13:53:34.670367 18799 solver.cpp:330] Iteration 7446, Testing net (#0)
I0405 13:53:34.670387 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:53:36.123616 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:53:38.996752 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0220588
I0405 13:53:38.996786 18799 solver.cpp:397]     Test net output #1: loss = 5.09282 (* 1 = 5.09282 loss)
I0405 13:53:40.901038 18799 solver.cpp:218] Iteration 7452 (0.694257 iter/s, 17.2847s/12 iters), loss = 5.09867
I0405 13:53:40.901088 18799 solver.cpp:237]     Train net output #0: loss = 5.09867 (* 1 = 5.09867 loss)
I0405 13:53:40.901095 18799 sgd_solver.cpp:105] Iteration 7452, lr = 0.0001
I0405 13:53:46.048462 18799 solver.cpp:218] Iteration 7464 (2.33131 iter/s, 5.14733s/12 iters), loss = 5.11415
I0405 13:53:46.048631 18799 solver.cpp:237]     Train net output #0: loss = 5.11415 (* 1 = 5.11415 loss)
I0405 13:53:46.048645 18799 sgd_solver.cpp:105] Iteration 7464, lr = 0.0001
I0405 13:53:51.524433 18799 solver.cpp:218] Iteration 7476 (2.19148 iter/s, 5.47575s/12 iters), loss = 5.0779
I0405 13:53:51.524489 18799 solver.cpp:237]     Train net output #0: loss = 5.0779 (* 1 = 5.0779 loss)
I0405 13:53:51.524497 18799 sgd_solver.cpp:105] Iteration 7476, lr = 0.0001
I0405 13:53:55.251392 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:53:56.837253 18799 solver.cpp:218] Iteration 7488 (2.25873 iter/s, 5.31273s/12 iters), loss = 5.09947
I0405 13:53:56.837281 18799 solver.cpp:237]     Train net output #0: loss = 5.09947 (* 1 = 5.09947 loss)
I0405 13:53:56.837287 18799 sgd_solver.cpp:105] Iteration 7488, lr = 0.0001
I0405 13:54:02.256026 18799 solver.cpp:218] Iteration 7500 (2.21456 iter/s, 5.41869s/12 iters), loss = 5.0974
I0405 13:54:02.256072 18799 solver.cpp:237]     Train net output #0: loss = 5.0974 (* 1 = 5.0974 loss)
I0405 13:54:02.256078 18799 sgd_solver.cpp:105] Iteration 7500, lr = 0.0001
I0405 13:54:07.571630 18799 solver.cpp:218] Iteration 7512 (2.25755 iter/s, 5.31551s/12 iters), loss = 5.08478
I0405 13:54:07.571684 18799 solver.cpp:237]     Train net output #0: loss = 5.08478 (* 1 = 5.08478 loss)
I0405 13:54:07.571691 18799 sgd_solver.cpp:105] Iteration 7512, lr = 0.0001
I0405 13:54:13.022737 18799 solver.cpp:218] Iteration 7524 (2.20143 iter/s, 5.45101s/12 iters), loss = 5.08337
I0405 13:54:13.022780 18799 solver.cpp:237]     Train net output #0: loss = 5.08337 (* 1 = 5.08337 loss)
I0405 13:54:13.022786 18799 sgd_solver.cpp:105] Iteration 7524, lr = 0.0001
I0405 13:54:18.143563 18799 solver.cpp:218] Iteration 7536 (2.34341 iter/s, 5.12073s/12 iters), loss = 5.09296
I0405 13:54:18.143666 18799 solver.cpp:237]     Train net output #0: loss = 5.09296 (* 1 = 5.09296 loss)
I0405 13:54:18.143672 18799 sgd_solver.cpp:105] Iteration 7536, lr = 0.0001
I0405 13:54:22.910548 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel
I0405 13:54:27.985440 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate
I0405 13:54:33.365435 18799 solver.cpp:330] Iteration 7548, Testing net (#0)
I0405 13:54:33.365461 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:54:34.762682 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:54:37.830376 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0208333
I0405 13:54:37.830413 18799 solver.cpp:397]     Test net output #1: loss = 5.08588 (* 1 = 5.08588 loss)
I0405 13:54:37.972865 18799 solver.cpp:218] Iteration 7548 (0.605172 iter/s, 19.8291s/12 iters), loss = 5.0141
I0405 13:54:37.972936 18799 solver.cpp:237]     Train net output #0: loss = 5.0141 (* 1 = 5.0141 loss)
I0405 13:54:37.972945 18799 sgd_solver.cpp:105] Iteration 7548, lr = 0.0001
I0405 13:54:42.486915 18799 solver.cpp:218] Iteration 7560 (2.65843 iter/s, 4.51394s/12 iters), loss = 4.99978
I0405 13:54:42.486953 18799 solver.cpp:237]     Train net output #0: loss = 4.99978 (* 1 = 4.99978 loss)
I0405 13:54:42.486958 18799 sgd_solver.cpp:105] Iteration 7560, lr = 0.0001
I0405 13:54:47.900876 18799 solver.cpp:218] Iteration 7572 (2.21653 iter/s, 5.41388s/12 iters), loss = 5.08223
I0405 13:54:47.900923 18799 solver.cpp:237]     Train net output #0: loss = 5.08223 (* 1 = 5.08223 loss)
I0405 13:54:47.900928 18799 sgd_solver.cpp:105] Iteration 7572, lr = 0.0001
I0405 13:54:53.264463 18799 solver.cpp:218] Iteration 7584 (2.23735 iter/s, 5.36349s/12 iters), loss = 5.08648
I0405 13:54:53.264559 18799 solver.cpp:237]     Train net output #0: loss = 5.08648 (* 1 = 5.08648 loss)
I0405 13:54:53.264565 18799 sgd_solver.cpp:105] Iteration 7584, lr = 0.0001
I0405 13:54:53.852546 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:54:58.571892 18799 solver.cpp:218] Iteration 7596 (2.26104 iter/s, 5.30729s/12 iters), loss = 5.07254
I0405 13:54:58.571926 18799 solver.cpp:237]     Train net output #0: loss = 5.07254 (* 1 = 5.07254 loss)
I0405 13:54:58.571933 18799 sgd_solver.cpp:105] Iteration 7596, lr = 0.0001
I0405 13:55:04.143385 18799 solver.cpp:218] Iteration 7608 (2.15386 iter/s, 5.5714s/12 iters), loss = 5.08013
I0405 13:55:04.143440 18799 solver.cpp:237]     Train net output #0: loss = 5.08013 (* 1 = 5.08013 loss)
I0405 13:55:04.143447 18799 sgd_solver.cpp:105] Iteration 7608, lr = 0.0001
I0405 13:55:09.559424 18799 solver.cpp:218] Iteration 7620 (2.21568 iter/s, 5.41594s/12 iters), loss = 5.06462
I0405 13:55:09.559465 18799 solver.cpp:237]     Train net output #0: loss = 5.06462 (* 1 = 5.06462 loss)
I0405 13:55:09.559471 18799 sgd_solver.cpp:105] Iteration 7620, lr = 0.0001
I0405 13:55:12.161075 18799 blocking_queue.cpp:49] Waiting for data
I0405 13:55:14.579509 18799 solver.cpp:218] Iteration 7632 (2.39044 iter/s, 5.02s/12 iters), loss = 5.09482
I0405 13:55:14.579546 18799 solver.cpp:237]     Train net output #0: loss = 5.09482 (* 1 = 5.09482 loss)
I0405 13:55:14.579552 18799 sgd_solver.cpp:105] Iteration 7632, lr = 0.0001
I0405 13:55:19.893604 18799 solver.cpp:218] Iteration 7644 (2.25818 iter/s, 5.31401s/12 iters), loss = 5.04949
I0405 13:55:19.893661 18799 solver.cpp:237]     Train net output #0: loss = 5.04949 (* 1 = 5.04949 loss)
I0405 13:55:19.893668 18799 sgd_solver.cpp:105] Iteration 7644, lr = 0.0001
I0405 13:55:21.947307 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel
I0405 13:55:26.498482 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate
I0405 13:55:30.371577 18799 solver.cpp:330] Iteration 7650, Testing net (#0)
I0405 13:55:30.371598 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:55:31.809392 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:55:34.769984 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 13:55:34.770015 18799 solver.cpp:397]     Test net output #1: loss = 5.07952 (* 1 = 5.07952 loss)
I0405 13:55:36.607520 18799 solver.cpp:218] Iteration 7656 (0.717972 iter/s, 16.7138s/12 iters), loss = 4.99745
I0405 13:55:36.607573 18799 solver.cpp:237]     Train net output #0: loss = 4.99745 (* 1 = 4.99745 loss)
I0405 13:55:36.607580 18799 sgd_solver.cpp:105] Iteration 7656, lr = 0.0001
I0405 13:55:41.886852 18799 solver.cpp:218] Iteration 7668 (2.27306 iter/s, 5.27924s/12 iters), loss = 5.10733
I0405 13:55:41.886898 18799 solver.cpp:237]     Train net output #0: loss = 5.10733 (* 1 = 5.10733 loss)
I0405 13:55:41.886905 18799 sgd_solver.cpp:105] Iteration 7668, lr = 0.0001
I0405 13:55:47.160189 18799 solver.cpp:218] Iteration 7680 (2.27564 iter/s, 5.27325s/12 iters), loss = 5.06338
I0405 13:55:47.160231 18799 solver.cpp:237]     Train net output #0: loss = 5.06338 (* 1 = 5.06338 loss)
I0405 13:55:47.160238 18799 sgd_solver.cpp:105] Iteration 7680, lr = 0.0001
I0405 13:55:50.102275 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:55:52.438942 18799 solver.cpp:218] Iteration 7692 (2.2733 iter/s, 5.27866s/12 iters), loss = 5.09734
I0405 13:55:52.438985 18799 solver.cpp:237]     Train net output #0: loss = 5.09734 (* 1 = 5.09734 loss)
I0405 13:55:52.438992 18799 sgd_solver.cpp:105] Iteration 7692, lr = 0.0001
I0405 13:55:57.803342 18799 solver.cpp:218] Iteration 7704 (2.23701 iter/s, 5.36431s/12 iters), loss = 5.10552
I0405 13:55:57.803445 18799 solver.cpp:237]     Train net output #0: loss = 5.10552 (* 1 = 5.10552 loss)
I0405 13:55:57.803452 18799 sgd_solver.cpp:105] Iteration 7704, lr = 0.0001
I0405 13:56:03.061671 18799 solver.cpp:218] Iteration 7716 (2.28216 iter/s, 5.25818s/12 iters), loss = 5.17971
I0405 13:56:03.061729 18799 solver.cpp:237]     Train net output #0: loss = 5.17971 (* 1 = 5.17971 loss)
I0405 13:56:03.061738 18799 sgd_solver.cpp:105] Iteration 7716, lr = 0.0001
I0405 13:56:08.441565 18799 solver.cpp:218] Iteration 7728 (2.23057 iter/s, 5.37979s/12 iters), loss = 5.10742
I0405 13:56:08.441609 18799 solver.cpp:237]     Train net output #0: loss = 5.10742 (* 1 = 5.10742 loss)
I0405 13:56:08.441617 18799 sgd_solver.cpp:105] Iteration 7728, lr = 0.0001
I0405 13:56:13.791657 18799 solver.cpp:218] Iteration 7740 (2.24299 iter/s, 5.35s/12 iters), loss = 5.11034
I0405 13:56:13.791697 18799 solver.cpp:237]     Train net output #0: loss = 5.11034 (* 1 = 5.11034 loss)
I0405 13:56:13.791702 18799 sgd_solver.cpp:105] Iteration 7740, lr = 0.0001
I0405 13:56:18.491829 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel
I0405 13:56:22.971812 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate
I0405 13:56:26.827282 18799 solver.cpp:330] Iteration 7752, Testing net (#0)
I0405 13:56:26.827306 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:56:28.236683 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:56:31.282121 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0202206
I0405 13:56:31.282160 18799 solver.cpp:397]     Test net output #1: loss = 5.07394 (* 1 = 5.07394 loss)
I0405 13:56:31.419726 18799 solver.cpp:218] Iteration 7752 (0.680739 iter/s, 17.6279s/12 iters), loss = 5.22151
I0405 13:56:31.419785 18799 solver.cpp:237]     Train net output #0: loss = 5.22151 (* 1 = 5.22151 loss)
I0405 13:56:31.419793 18799 sgd_solver.cpp:105] Iteration 7752, lr = 0.0001
I0405 13:56:35.891135 18799 solver.cpp:218] Iteration 7764 (2.68378 iter/s, 4.47131s/12 iters), loss = 5.11447
I0405 13:56:35.891180 18799 solver.cpp:237]     Train net output #0: loss = 5.11447 (* 1 = 5.11447 loss)
I0405 13:56:35.891186 18799 sgd_solver.cpp:105] Iteration 7764, lr = 0.0001
I0405 13:56:41.145017 18799 solver.cpp:218] Iteration 7776 (2.28407 iter/s, 5.25379s/12 iters), loss = 5.05346
I0405 13:56:41.145068 18799 solver.cpp:237]     Train net output #0: loss = 5.05346 (* 1 = 5.05346 loss)
I0405 13:56:41.145076 18799 sgd_solver.cpp:105] Iteration 7776, lr = 0.0001
I0405 13:56:46.593717 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:56:46.650892 18799 solver.cpp:218] Iteration 7788 (2.17953 iter/s, 5.50577s/12 iters), loss = 5.06407
I0405 13:56:46.650943 18799 solver.cpp:237]     Train net output #0: loss = 5.06407 (* 1 = 5.06407 loss)
I0405 13:56:46.650950 18799 sgd_solver.cpp:105] Iteration 7788, lr = 0.0001
I0405 13:56:51.786571 18799 solver.cpp:218] Iteration 7800 (2.33664 iter/s, 5.13558s/12 iters), loss = 5.04968
I0405 13:56:51.786626 18799 solver.cpp:237]     Train net output #0: loss = 5.04968 (* 1 = 5.04968 loss)
I0405 13:56:51.786634 18799 sgd_solver.cpp:105] Iteration 7800, lr = 0.0001
I0405 13:56:56.984406 18799 solver.cpp:218] Iteration 7812 (2.3087 iter/s, 5.19773s/12 iters), loss = 5.06599
I0405 13:56:56.984462 18799 solver.cpp:237]     Train net output #0: loss = 5.06599 (* 1 = 5.06599 loss)
I0405 13:56:56.984469 18799 sgd_solver.cpp:105] Iteration 7812, lr = 0.0001
I0405 13:57:02.282948 18799 solver.cpp:218] Iteration 7824 (2.26482 iter/s, 5.29844s/12 iters), loss = 5.13395
I0405 13:57:02.283056 18799 solver.cpp:237]     Train net output #0: loss = 5.13395 (* 1 = 5.13395 loss)
I0405 13:57:02.283062 18799 sgd_solver.cpp:105] Iteration 7824, lr = 0.0001
I0405 13:57:07.370656 18799 solver.cpp:218] Iteration 7836 (2.3587 iter/s, 5.08755s/12 iters), loss = 5.09917
I0405 13:57:07.370716 18799 solver.cpp:237]     Train net output #0: loss = 5.09917 (* 1 = 5.09917 loss)
I0405 13:57:07.370725 18799 sgd_solver.cpp:105] Iteration 7836, lr = 0.0001
I0405 13:57:12.851516 18799 solver.cpp:218] Iteration 7848 (2.18948 iter/s, 5.48075s/12 iters), loss = 5.0386
I0405 13:57:12.851559 18799 solver.cpp:237]     Train net output #0: loss = 5.0386 (* 1 = 5.0386 loss)
I0405 13:57:12.851565 18799 sgd_solver.cpp:105] Iteration 7848, lr = 0.0001
I0405 13:57:15.029083 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel
I0405 13:57:19.210675 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate
I0405 13:57:23.103765 18799 solver.cpp:330] Iteration 7854, Testing net (#0)
I0405 13:57:23.103782 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:57:24.364610 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:57:27.521373 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0220588
I0405 13:57:27.521404 18799 solver.cpp:397]     Test net output #1: loss = 5.06922 (* 1 = 5.06922 loss)
I0405 13:57:29.491931 18799 solver.cpp:218] Iteration 7860 (0.721143 iter/s, 16.6403s/12 iters), loss = 5.08571
I0405 13:57:29.491979 18799 solver.cpp:237]     Train net output #0: loss = 5.08571 (* 1 = 5.08571 loss)
I0405 13:57:29.491987 18799 sgd_solver.cpp:105] Iteration 7860, lr = 0.0001
I0405 13:57:34.821986 18799 solver.cpp:218] Iteration 7872 (2.25143 iter/s, 5.32996s/12 iters), loss = 5.02245
I0405 13:57:34.822158 18799 solver.cpp:237]     Train net output #0: loss = 5.02245 (* 1 = 5.02245 loss)
I0405 13:57:34.822165 18799 sgd_solver.cpp:105] Iteration 7872, lr = 0.0001
I0405 13:57:40.007937 18799 solver.cpp:218] Iteration 7884 (2.31404 iter/s, 5.18574s/12 iters), loss = 4.98063
I0405 13:57:40.007979 18799 solver.cpp:237]     Train net output #0: loss = 4.98063 (* 1 = 4.98063 loss)
I0405 13:57:40.007984 18799 sgd_solver.cpp:105] Iteration 7884, lr = 0.0001
I0405 13:57:42.229993 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:57:45.386610 18799 solver.cpp:218] Iteration 7896 (2.23107 iter/s, 5.37858s/12 iters), loss = 5.09708
I0405 13:57:45.386651 18799 solver.cpp:237]     Train net output #0: loss = 5.09708 (* 1 = 5.09708 loss)
I0405 13:57:45.386657 18799 sgd_solver.cpp:105] Iteration 7896, lr = 0.0001
I0405 13:57:50.626145 18799 solver.cpp:218] Iteration 7908 (2.29032 iter/s, 5.23945s/12 iters), loss = 5.13303
I0405 13:57:50.626188 18799 solver.cpp:237]     Train net output #0: loss = 5.13303 (* 1 = 5.13303 loss)
I0405 13:57:50.626194 18799 sgd_solver.cpp:105] Iteration 7908, lr = 0.0001
I0405 13:57:55.789616 18799 solver.cpp:218] Iteration 7920 (2.32406 iter/s, 5.16338s/12 iters), loss = 5.19242
I0405 13:57:55.789659 18799 solver.cpp:237]     Train net output #0: loss = 5.19242 (* 1 = 5.19242 loss)
I0405 13:57:55.789665 18799 sgd_solver.cpp:105] Iteration 7920, lr = 0.0001
I0405 13:58:01.180229 18799 solver.cpp:218] Iteration 7932 (2.22613 iter/s, 5.39052s/12 iters), loss = 5.06623
I0405 13:58:01.180281 18799 solver.cpp:237]     Train net output #0: loss = 5.06623 (* 1 = 5.06623 loss)
I0405 13:58:01.180289 18799 sgd_solver.cpp:105] Iteration 7932, lr = 0.0001
I0405 13:58:06.621341 18799 solver.cpp:218] Iteration 7944 (2.20547 iter/s, 5.44101s/12 iters), loss = 5.07802
I0405 13:58:06.621490 18799 solver.cpp:237]     Train net output #0: loss = 5.07802 (* 1 = 5.07802 loss)
I0405 13:58:06.621498 18799 sgd_solver.cpp:105] Iteration 7944, lr = 0.0001
I0405 13:58:11.222527 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel
I0405 13:58:16.815419 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate
I0405 13:58:21.066009 18799 solver.cpp:330] Iteration 7956, Testing net (#0)
I0405 13:58:21.066030 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:58:22.522652 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:58:25.635643 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0208333
I0405 13:58:25.635675 18799 solver.cpp:397]     Test net output #1: loss = 5.0673 (* 1 = 5.0673 loss)
I0405 13:58:25.776804 18799 solver.cpp:218] Iteration 7956 (0.626462 iter/s, 19.1552s/12 iters), loss = 5.16331
I0405 13:58:25.776862 18799 solver.cpp:237]     Train net output #0: loss = 5.16331 (* 1 = 5.16331 loss)
I0405 13:58:25.776870 18799 sgd_solver.cpp:105] Iteration 7956, lr = 0.0001
I0405 13:58:30.376474 18799 solver.cpp:218] Iteration 7968 (2.60894 iter/s, 4.59956s/12 iters), loss = 5.06324
I0405 13:58:30.376528 18799 solver.cpp:237]     Train net output #0: loss = 5.06324 (* 1 = 5.06324 loss)
I0405 13:58:30.376536 18799 sgd_solver.cpp:105] Iteration 7968, lr = 0.0001
I0405 13:58:35.653576 18799 solver.cpp:218] Iteration 7980 (2.27402 iter/s, 5.277s/12 iters), loss = 5.10662
I0405 13:58:35.653617 18799 solver.cpp:237]     Train net output #0: loss = 5.10662 (* 1 = 5.10662 loss)
I0405 13:58:35.653625 18799 sgd_solver.cpp:105] Iteration 7980, lr = 0.0001
I0405 13:58:40.174679 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:58:40.965648 18799 solver.cpp:218] Iteration 7992 (2.25904 iter/s, 5.31198s/12 iters), loss = 5.08558
I0405 13:58:40.965703 18799 solver.cpp:237]     Train net output #0: loss = 5.08558 (* 1 = 5.08558 loss)
I0405 13:58:40.965713 18799 sgd_solver.cpp:105] Iteration 7992, lr = 0.0001
I0405 13:58:46.283715 18799 solver.cpp:218] Iteration 8004 (2.2565 iter/s, 5.31797s/12 iters), loss = 5.10581
I0405 13:58:46.283759 18799 solver.cpp:237]     Train net output #0: loss = 5.10581 (* 1 = 5.10581 loss)
I0405 13:58:46.283766 18799 sgd_solver.cpp:105] Iteration 8004, lr = 0.0001
I0405 13:58:51.618793 18799 solver.cpp:218] Iteration 8016 (2.2493 iter/s, 5.33499s/12 iters), loss = 5.07286
I0405 13:58:51.618832 18799 solver.cpp:237]     Train net output #0: loss = 5.07286 (* 1 = 5.07286 loss)
I0405 13:58:51.618839 18799 sgd_solver.cpp:105] Iteration 8016, lr = 0.0001
I0405 13:58:56.718070 18799 solver.cpp:218] Iteration 8028 (2.35331 iter/s, 5.09919s/12 iters), loss = 5.04702
I0405 13:58:56.718108 18799 solver.cpp:237]     Train net output #0: loss = 5.04702 (* 1 = 5.04702 loss)
I0405 13:58:56.718114 18799 sgd_solver.cpp:105] Iteration 8028, lr = 0.0001
I0405 13:59:01.934468 18799 solver.cpp:218] Iteration 8040 (2.30048 iter/s, 5.21631s/12 iters), loss = 5.09279
I0405 13:59:01.934510 18799 solver.cpp:237]     Train net output #0: loss = 5.09279 (* 1 = 5.09279 loss)
I0405 13:59:01.934515 18799 sgd_solver.cpp:105] Iteration 8040, lr = 0.0001
I0405 13:59:07.043337 18799 solver.cpp:218] Iteration 8052 (2.3489 iter/s, 5.10878s/12 iters), loss = 5.12399
I0405 13:59:07.043385 18799 solver.cpp:237]     Train net output #0: loss = 5.12399 (* 1 = 5.12399 loss)
I0405 13:59:07.043391 18799 sgd_solver.cpp:105] Iteration 8052, lr = 0.0001
I0405 13:59:09.248139 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel
I0405 13:59:13.168596 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate
I0405 13:59:17.884913 18799 solver.cpp:330] Iteration 8058, Testing net (#0)
I0405 13:59:17.884934 18799 net.cpp:676] Ignoring source layer train-data
I0405 13:59:19.084472 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:59:22.226605 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0208333
I0405 13:59:22.226656 18799 solver.cpp:397]     Test net output #1: loss = 5.0608 (* 1 = 5.0608 loss)
I0405 13:59:24.114646 18799 solver.cpp:218] Iteration 8064 (0.702941 iter/s, 17.0711s/12 iters), loss = 5.01757
I0405 13:59:24.114707 18799 solver.cpp:237]     Train net output #0: loss = 5.01757 (* 1 = 5.01757 loss)
I0405 13:59:24.114717 18799 sgd_solver.cpp:105] Iteration 8064, lr = 0.0001
I0405 13:59:29.402674 18799 solver.cpp:218] Iteration 8076 (2.26932 iter/s, 5.28792s/12 iters), loss = 5.16511
I0405 13:59:29.402714 18799 solver.cpp:237]     Train net output #0: loss = 5.16511 (* 1 = 5.16511 loss)
I0405 13:59:29.402719 18799 sgd_solver.cpp:105] Iteration 8076, lr = 0.0001
I0405 13:59:34.754462 18799 solver.cpp:218] Iteration 8088 (2.24228 iter/s, 5.3517s/12 iters), loss = 5.04992
I0405 13:59:34.754496 18799 solver.cpp:237]     Train net output #0: loss = 5.04992 (* 1 = 5.04992 loss)
I0405 13:59:34.754503 18799 sgd_solver.cpp:105] Iteration 8088, lr = 0.0001
I0405 13:59:36.280891 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:59:40.000560 18799 solver.cpp:218] Iteration 8100 (2.28745 iter/s, 5.24602s/12 iters), loss = 5.09669
I0405 13:59:40.000607 18799 solver.cpp:237]     Train net output #0: loss = 5.09669 (* 1 = 5.09669 loss)
I0405 13:59:40.000612 18799 sgd_solver.cpp:105] Iteration 8100, lr = 0.0001
I0405 13:59:45.234974 18799 solver.cpp:218] Iteration 8112 (2.29256 iter/s, 5.23432s/12 iters), loss = 5.01753
I0405 13:59:45.235095 18799 solver.cpp:237]     Train net output #0: loss = 5.01753 (* 1 = 5.01753 loss)
I0405 13:59:45.235102 18799 sgd_solver.cpp:105] Iteration 8112, lr = 0.0001
I0405 13:59:50.491256 18799 solver.cpp:218] Iteration 8124 (2.28306 iter/s, 5.25611s/12 iters), loss = 5.01951
I0405 13:59:50.491299 18799 solver.cpp:237]     Train net output #0: loss = 5.01951 (* 1 = 5.01951 loss)
I0405 13:59:50.491304 18799 sgd_solver.cpp:105] Iteration 8124, lr = 0.0001
I0405 13:59:55.874900 18799 solver.cpp:218] Iteration 8136 (2.22901 iter/s, 5.38355s/12 iters), loss = 4.98142
I0405 13:59:55.874953 18799 solver.cpp:237]     Train net output #0: loss = 4.98142 (* 1 = 4.98142 loss)
I0405 13:59:55.874960 18799 sgd_solver.cpp:105] Iteration 8136, lr = 0.0001
I0405 14:00:01.175200 18799 solver.cpp:218] Iteration 8148 (2.26407 iter/s, 5.3002s/12 iters), loss = 5.029
I0405 14:00:01.175247 18799 solver.cpp:237]     Train net output #0: loss = 5.029 (* 1 = 5.029 loss)
I0405 14:00:01.175257 18799 sgd_solver.cpp:105] Iteration 8148, lr = 0.0001
I0405 14:00:05.890303 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel
I0405 14:00:10.776522 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate
I0405 14:00:14.540170 18799 solver.cpp:330] Iteration 8160, Testing net (#0)
I0405 14:00:14.540189 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:00:15.823655 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:00:19.036702 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0220588
I0405 14:00:19.036738 18799 solver.cpp:397]     Test net output #1: loss = 5.05566 (* 1 = 5.05566 loss)
I0405 14:00:19.180711 18799 solver.cpp:218] Iteration 8160 (0.666469 iter/s, 18.0053s/12 iters), loss = 5.03946
I0405 14:00:19.182299 18799 solver.cpp:237]     Train net output #0: loss = 5.03946 (* 1 = 5.03946 loss)
I0405 14:00:19.182314 18799 sgd_solver.cpp:105] Iteration 8160, lr = 0.0001
I0405 14:00:23.688344 18799 solver.cpp:218] Iteration 8172 (2.66311 iter/s, 4.50601s/12 iters), loss = 5.00025
I0405 14:00:23.688410 18799 solver.cpp:237]     Train net output #0: loss = 5.00025 (* 1 = 5.00025 loss)
I0405 14:00:23.688419 18799 sgd_solver.cpp:105] Iteration 8172, lr = 0.0001
I0405 14:00:29.033388 18799 solver.cpp:218] Iteration 8184 (2.24511 iter/s, 5.34494s/12 iters), loss = 4.96671
I0405 14:00:29.033427 18799 solver.cpp:237]     Train net output #0: loss = 4.96671 (* 1 = 4.96671 loss)
I0405 14:00:29.033434 18799 sgd_solver.cpp:105] Iteration 8184, lr = 0.0001
I0405 14:00:32.796427 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:00:34.368229 18799 solver.cpp:218] Iteration 8196 (2.2494 iter/s, 5.33475s/12 iters), loss = 5.09662
I0405 14:00:34.368268 18799 solver.cpp:237]     Train net output #0: loss = 5.09662 (* 1 = 5.09662 loss)
I0405 14:00:34.368274 18799 sgd_solver.cpp:105] Iteration 8196, lr = 0.0001
I0405 14:00:39.655891 18799 solver.cpp:218] Iteration 8208 (2.26947 iter/s, 5.28757s/12 iters), loss = 5.03631
I0405 14:00:39.655933 18799 solver.cpp:237]     Train net output #0: loss = 5.03631 (* 1 = 5.03631 loss)
I0405 14:00:39.655939 18799 sgd_solver.cpp:105] Iteration 8208, lr = 0.0001
I0405 14:00:45.038146 18799 solver.cpp:218] Iteration 8220 (2.22959 iter/s, 5.38217s/12 iters), loss = 5.11381
I0405 14:00:45.038187 18799 solver.cpp:237]     Train net output #0: loss = 5.11381 (* 1 = 5.11381 loss)
I0405 14:00:45.038192 18799 sgd_solver.cpp:105] Iteration 8220, lr = 0.0001
I0405 14:00:50.292624 18799 solver.cpp:218] Iteration 8232 (2.28381 iter/s, 5.25439s/12 iters), loss = 5.01453
I0405 14:00:50.292755 18799 solver.cpp:237]     Train net output #0: loss = 5.01453 (* 1 = 5.01453 loss)
I0405 14:00:50.292765 18799 sgd_solver.cpp:105] Iteration 8232, lr = 0.0001
I0405 14:00:55.484959 18799 solver.cpp:218] Iteration 8244 (2.31118 iter/s, 5.19216s/12 iters), loss = 5.06335
I0405 14:00:55.485002 18799 solver.cpp:237]     Train net output #0: loss = 5.06335 (* 1 = 5.06335 loss)
I0405 14:00:55.485006 18799 sgd_solver.cpp:105] Iteration 8244, lr = 0.0001
I0405 14:01:00.543753 18799 solver.cpp:218] Iteration 8256 (2.37215 iter/s, 5.05871s/12 iters), loss = 4.99321
I0405 14:01:00.543797 18799 solver.cpp:237]     Train net output #0: loss = 4.99321 (* 1 = 4.99321 loss)
I0405 14:01:00.543802 18799 sgd_solver.cpp:105] Iteration 8256, lr = 0.0001
I0405 14:01:02.565331 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel
I0405 14:01:06.366850 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate
I0405 14:01:10.133960 18799 solver.cpp:330] Iteration 8262, Testing net (#0)
I0405 14:01:10.133980 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:01:11.268024 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:01:14.480835 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0214461
I0405 14:01:14.480870 18799 solver.cpp:397]     Test net output #1: loss = 5.05462 (* 1 = 5.05462 loss)
I0405 14:01:16.515568 18799 solver.cpp:218] Iteration 8268 (0.75133 iter/s, 15.9717s/12 iters), loss = 4.97389
I0405 14:01:16.515609 18799 solver.cpp:237]     Train net output #0: loss = 4.97389 (* 1 = 4.97389 loss)
I0405 14:01:16.515614 18799 sgd_solver.cpp:105] Iteration 8268, lr = 0.0001
I0405 14:01:21.894663 18799 solver.cpp:218] Iteration 8280 (2.23089 iter/s, 5.37901s/12 iters), loss = 5.07962
I0405 14:01:21.894789 18799 solver.cpp:237]     Train net output #0: loss = 5.07962 (* 1 = 5.07962 loss)
I0405 14:01:21.894796 18799 sgd_solver.cpp:105] Iteration 8280, lr = 0.0001
I0405 14:01:27.167358 18799 solver.cpp:218] Iteration 8292 (2.27595 iter/s, 5.27252s/12 iters), loss = 5.05061
I0405 14:01:27.167414 18799 solver.cpp:237]     Train net output #0: loss = 5.05061 (* 1 = 5.05061 loss)
I0405 14:01:27.167423 18799 sgd_solver.cpp:105] Iteration 8292, lr = 0.0001
I0405 14:01:27.782124 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:01:32.326905 18799 solver.cpp:218] Iteration 8304 (2.32583 iter/s, 5.15944s/12 iters), loss = 5.05947
I0405 14:01:32.326951 18799 solver.cpp:237]     Train net output #0: loss = 5.05947 (* 1 = 5.05947 loss)
I0405 14:01:32.326958 18799 sgd_solver.cpp:105] Iteration 8304, lr = 0.0001
I0405 14:01:35.244722 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:01:37.496471 18799 solver.cpp:218] Iteration 8316 (2.32132 iter/s, 5.16947s/12 iters), loss = 5.00594
I0405 14:01:37.496529 18799 solver.cpp:237]     Train net output #0: loss = 5.00594 (* 1 = 5.00594 loss)
I0405 14:01:37.496537 18799 sgd_solver.cpp:105] Iteration 8316, lr = 0.0001
I0405 14:01:42.865176 18799 solver.cpp:218] Iteration 8328 (2.23522 iter/s, 5.3686s/12 iters), loss = 5.1159
I0405 14:01:42.865227 18799 solver.cpp:237]     Train net output #0: loss = 5.1159 (* 1 = 5.1159 loss)
I0405 14:01:42.865236 18799 sgd_solver.cpp:105] Iteration 8328, lr = 0.0001
I0405 14:01:48.263317 18799 solver.cpp:218] Iteration 8340 (2.22303 iter/s, 5.39805s/12 iters), loss = 5.09707
I0405 14:01:48.263360 18799 solver.cpp:237]     Train net output #0: loss = 5.09707 (* 1 = 5.09707 loss)
I0405 14:01:48.263365 18799 sgd_solver.cpp:105] Iteration 8340, lr = 0.0001
I0405 14:01:53.330889 18799 solver.cpp:218] Iteration 8352 (2.36804 iter/s, 5.06748s/12 iters), loss = 5.01873
I0405 14:01:53.331010 18799 solver.cpp:237]     Train net output #0: loss = 5.01873 (* 1 = 5.01873 loss)
I0405 14:01:53.331018 18799 sgd_solver.cpp:105] Iteration 8352, lr = 0.0001
I0405 14:01:57.957041 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel
I0405 14:02:02.397809 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate
I0405 14:02:06.214229 18799 solver.cpp:330] Iteration 8364, Testing net (#0)
I0405 14:02:06.214251 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:02:07.391247 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:02:10.881085 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0220588
I0405 14:02:10.881108 18799 solver.cpp:397]     Test net output #1: loss = 5.05326 (* 1 = 5.05326 loss)
I0405 14:02:11.022852 18799 solver.cpp:218] Iteration 8364 (0.678283 iter/s, 17.6917s/12 iters), loss = 4.96084
I0405 14:02:11.022907 18799 solver.cpp:237]     Train net output #0: loss = 4.96084 (* 1 = 4.96084 loss)
I0405 14:02:11.022915 18799 sgd_solver.cpp:105] Iteration 8364, lr = 0.0001
I0405 14:02:15.359696 18799 solver.cpp:218] Iteration 8376 (2.76705 iter/s, 4.33675s/12 iters), loss = 5.05736
I0405 14:02:15.359740 18799 solver.cpp:237]     Train net output #0: loss = 5.05736 (* 1 = 5.05736 loss)
I0405 14:02:15.359746 18799 sgd_solver.cpp:105] Iteration 8376, lr = 0.0001
I0405 14:02:20.773411 18799 solver.cpp:218] Iteration 8388 (2.21663 iter/s, 5.41362s/12 iters), loss = 4.98519
I0405 14:02:20.773468 18799 solver.cpp:237]     Train net output #0: loss = 4.98519 (* 1 = 4.98519 loss)
I0405 14:02:20.773476 18799 sgd_solver.cpp:105] Iteration 8388, lr = 0.0001
I0405 14:02:23.671188 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:02:26.077196 18799 solver.cpp:218] Iteration 8400 (2.26258 iter/s, 5.30368s/12 iters), loss = 5.0483
I0405 14:02:26.077253 18799 solver.cpp:237]     Train net output #0: loss = 5.0483 (* 1 = 5.0483 loss)
I0405 14:02:26.077261 18799 sgd_solver.cpp:105] Iteration 8400, lr = 0.0001
I0405 14:02:31.188776 18799 solver.cpp:218] Iteration 8412 (2.34766 iter/s, 5.11148s/12 iters), loss = 5.10262
I0405 14:02:31.188828 18799 solver.cpp:237]     Train net output #0: loss = 5.10262 (* 1 = 5.10262 loss)
I0405 14:02:31.188836 18799 sgd_solver.cpp:105] Iteration 8412, lr = 0.0001
I0405 14:02:36.498390 18799 solver.cpp:218] Iteration 8424 (2.26009 iter/s, 5.30952s/12 iters), loss = 5.09817
I0405 14:02:36.498432 18799 solver.cpp:237]     Train net output #0: loss = 5.09817 (* 1 = 5.09817 loss)
I0405 14:02:36.498438 18799 sgd_solver.cpp:105] Iteration 8424, lr = 0.0001
I0405 14:02:41.758684 18799 solver.cpp:218] Iteration 8436 (2.28128 iter/s, 5.26021s/12 iters), loss = 5.08998
I0405 14:02:41.758720 18799 solver.cpp:237]     Train net output #0: loss = 5.08998 (* 1 = 5.08998 loss)
I0405 14:02:41.758725 18799 sgd_solver.cpp:105] Iteration 8436, lr = 0.0001
I0405 14:02:47.092056 18799 solver.cpp:218] Iteration 8448 (2.25002 iter/s, 5.33328s/12 iters), loss = 5.08689
I0405 14:02:47.092110 18799 solver.cpp:237]     Train net output #0: loss = 5.08689 (* 1 = 5.08689 loss)
I0405 14:02:47.092119 18799 sgd_solver.cpp:105] Iteration 8448, lr = 0.0001
I0405 14:02:52.367133 18799 solver.cpp:218] Iteration 8460 (2.27489 iter/s, 5.27498s/12 iters), loss = 5.17325
I0405 14:02:52.367172 18799 solver.cpp:237]     Train net output #0: loss = 5.17325 (* 1 = 5.17325 loss)
I0405 14:02:52.367177 18799 sgd_solver.cpp:105] Iteration 8460, lr = 0.0001
I0405 14:02:54.505290 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel
I0405 14:02:59.121634 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate
I0405 14:03:03.198591 18799 solver.cpp:330] Iteration 8466, Testing net (#0)
I0405 14:03:03.198611 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:03:04.271977 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:03:07.609779 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 14:03:07.609819 18799 solver.cpp:397]     Test net output #1: loss = 5.04782 (* 1 = 5.04782 loss)
I0405 14:03:09.453912 18799 solver.cpp:218] Iteration 8472 (0.702304 iter/s, 17.0866s/12 iters), loss = 5.04218
I0405 14:03:09.453958 18799 solver.cpp:237]     Train net output #0: loss = 5.04218 (* 1 = 5.04218 loss)
I0405 14:03:09.453963 18799 sgd_solver.cpp:105] Iteration 8472, lr = 0.0001
I0405 14:03:14.840749 18799 solver.cpp:218] Iteration 8484 (2.22769 iter/s, 5.38674s/12 iters), loss = 5.04333
I0405 14:03:14.840799 18799 solver.cpp:237]     Train net output #0: loss = 5.04333 (* 1 = 5.04333 loss)
I0405 14:03:14.840806 18799 sgd_solver.cpp:105] Iteration 8484, lr = 0.0001
I0405 14:03:20.239524 18799 solver.cpp:218] Iteration 8496 (2.22277 iter/s, 5.39868s/12 iters), loss = 5.08019
I0405 14:03:20.239578 18799 solver.cpp:237]     Train net output #0: loss = 5.08019 (* 1 = 5.08019 loss)
I0405 14:03:20.239586 18799 sgd_solver.cpp:105] Iteration 8496, lr = 0.0001
I0405 14:03:20.278627 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:03:25.559378 18799 solver.cpp:218] Iteration 8508 (2.25574 iter/s, 5.31975s/12 iters), loss = 5.04302
I0405 14:03:25.559533 18799 solver.cpp:237]     Train net output #0: loss = 5.04302 (* 1 = 5.04302 loss)
I0405 14:03:25.559541 18799 sgd_solver.cpp:105] Iteration 8508, lr = 0.0001
I0405 14:03:30.898205 18799 solver.cpp:218] Iteration 8520 (2.24777 iter/s, 5.33863s/12 iters), loss = 5.01636
I0405 14:03:30.898242 18799 solver.cpp:237]     Train net output #0: loss = 5.01636 (* 1 = 5.01636 loss)
I0405 14:03:30.898248 18799 sgd_solver.cpp:105] Iteration 8520, lr = 0.0001
I0405 14:03:36.082374 18799 solver.cpp:218] Iteration 8532 (2.31478 iter/s, 5.18408s/12 iters), loss = 5.03017
I0405 14:03:36.082417 18799 solver.cpp:237]     Train net output #0: loss = 5.03017 (* 1 = 5.03017 loss)
I0405 14:03:36.082423 18799 sgd_solver.cpp:105] Iteration 8532, lr = 0.0001
I0405 14:03:41.338567 18799 solver.cpp:218] Iteration 8544 (2.28306 iter/s, 5.2561s/12 iters), loss = 5.04222
I0405 14:03:41.338608 18799 solver.cpp:237]     Train net output #0: loss = 5.04222 (* 1 = 5.04222 loss)
I0405 14:03:41.338613 18799 sgd_solver.cpp:105] Iteration 8544, lr = 0.0001
I0405 14:03:46.300362 18799 solver.cpp:218] Iteration 8556 (2.41852 iter/s, 4.96171s/12 iters), loss = 5.06462
I0405 14:03:46.300410 18799 solver.cpp:237]     Train net output #0: loss = 5.06462 (* 1 = 5.06462 loss)
I0405 14:03:46.300417 18799 sgd_solver.cpp:105] Iteration 8556, lr = 0.0001
I0405 14:03:51.047607 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel
I0405 14:03:55.406575 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate
I0405 14:03:59.175689 18799 solver.cpp:330] Iteration 8568, Testing net (#0)
I0405 14:03:59.175781 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:04:00.150966 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:04:03.636965 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0232843
I0405 14:04:03.636997 18799 solver.cpp:397]     Test net output #1: loss = 5.04367 (* 1 = 5.04367 loss)
I0405 14:04:03.778980 18799 solver.cpp:218] Iteration 8568 (0.68656 iter/s, 17.4785s/12 iters), loss = 5.04696
I0405 14:04:03.779032 18799 solver.cpp:237]     Train net output #0: loss = 5.04696 (* 1 = 5.04696 loss)
I0405 14:04:03.779039 18799 sgd_solver.cpp:105] Iteration 8568, lr = 0.0001
I0405 14:04:08.125699 18799 solver.cpp:218] Iteration 8580 (2.76076 iter/s, 4.34662s/12 iters), loss = 5.00896
I0405 14:04:08.125741 18799 solver.cpp:237]     Train net output #0: loss = 5.00896 (* 1 = 5.00896 loss)
I0405 14:04:08.125746 18799 sgd_solver.cpp:105] Iteration 8580, lr = 0.0001
I0405 14:04:13.279278 18799 solver.cpp:218] Iteration 8592 (2.32852 iter/s, 5.15349s/12 iters), loss = 4.88299
I0405 14:04:13.279321 18799 solver.cpp:237]     Train net output #0: loss = 4.88299 (* 1 = 4.88299 loss)
I0405 14:04:13.279327 18799 sgd_solver.cpp:105] Iteration 8592, lr = 0.0001
I0405 14:04:15.513461 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:04:18.736344 18799 solver.cpp:218] Iteration 8604 (2.19902 iter/s, 5.45697s/12 iters), loss = 5.11587
I0405 14:04:18.736385 18799 solver.cpp:237]     Train net output #0: loss = 5.11587 (* 1 = 5.11587 loss)
I0405 14:04:18.736392 18799 sgd_solver.cpp:105] Iteration 8604, lr = 0.0001
I0405 14:04:23.983000 18799 solver.cpp:218] Iteration 8616 (2.28721 iter/s, 5.24657s/12 iters), loss = 5.14121
I0405 14:04:23.983048 18799 solver.cpp:237]     Train net output #0: loss = 5.14121 (* 1 = 5.14121 loss)
I0405 14:04:23.983053 18799 sgd_solver.cpp:105] Iteration 8616, lr = 0.0001
I0405 14:04:29.142081 18799 solver.cpp:218] Iteration 8628 (2.32604 iter/s, 5.15898s/12 iters), loss = 5.13083
I0405 14:04:29.142122 18799 solver.cpp:237]     Train net output #0: loss = 5.13083 (* 1 = 5.13083 loss)
I0405 14:04:29.142127 18799 sgd_solver.cpp:105] Iteration 8628, lr = 0.0001
I0405 14:04:34.457881 18799 solver.cpp:218] Iteration 8640 (2.25746 iter/s, 5.31571s/12 iters), loss = 5.0728
I0405 14:04:34.458055 18799 solver.cpp:237]     Train net output #0: loss = 5.0728 (* 1 = 5.0728 loss)
I0405 14:04:34.458065 18799 sgd_solver.cpp:105] Iteration 8640, lr = 0.0001
I0405 14:04:39.645269 18799 solver.cpp:218] Iteration 8652 (2.3134 iter/s, 5.18717s/12 iters), loss = 5.0446
I0405 14:04:39.645328 18799 solver.cpp:237]     Train net output #0: loss = 5.0446 (* 1 = 5.0446 loss)
I0405 14:04:39.645335 18799 sgd_solver.cpp:105] Iteration 8652, lr = 0.0001
I0405 14:04:44.942106 18799 solver.cpp:218] Iteration 8664 (2.26555 iter/s, 5.29674s/12 iters), loss = 5.1339
I0405 14:04:44.942147 18799 solver.cpp:237]     Train net output #0: loss = 5.1339 (* 1 = 5.1339 loss)
I0405 14:04:44.942152 18799 sgd_solver.cpp:105] Iteration 8664, lr = 0.0001
I0405 14:04:47.125294 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel
I0405 14:04:51.535697 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate
I0405 14:04:55.317453 18799 solver.cpp:330] Iteration 8670, Testing net (#0)
I0405 14:04:55.317474 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:04:56.269837 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:04:59.665084 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:04:59.665122 18799 solver.cpp:397]     Test net output #1: loss = 5.04158 (* 1 = 5.04158 loss)
I0405 14:05:01.517513 18799 solver.cpp:218] Iteration 8676 (0.723971 iter/s, 16.5753s/12 iters), loss = 5.00433
I0405 14:05:01.517565 18799 solver.cpp:237]     Train net output #0: loss = 5.00433 (* 1 = 5.00433 loss)
I0405 14:05:01.517573 18799 sgd_solver.cpp:105] Iteration 8676, lr = 0.0001
I0405 14:05:06.838367 18799 solver.cpp:218] Iteration 8688 (2.25532 iter/s, 5.32076s/12 iters), loss = 5.12233
I0405 14:05:06.838459 18799 solver.cpp:237]     Train net output #0: loss = 5.12233 (* 1 = 5.12233 loss)
I0405 14:05:06.838465 18799 sgd_solver.cpp:105] Iteration 8688, lr = 0.0001
I0405 14:05:11.084129 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:05:11.846552 18799 solver.cpp:218] Iteration 8700 (2.39614 iter/s, 5.00805s/12 iters), loss = 5.10606
I0405 14:05:11.846599 18799 solver.cpp:237]     Train net output #0: loss = 5.10606 (* 1 = 5.10606 loss)
I0405 14:05:11.846604 18799 sgd_solver.cpp:105] Iteration 8700, lr = 0.0001
I0405 14:05:17.068194 18799 solver.cpp:218] Iteration 8712 (2.29817 iter/s, 5.22155s/12 iters), loss = 5.01525
I0405 14:05:17.068239 18799 solver.cpp:237]     Train net output #0: loss = 5.01525 (* 1 = 5.01525 loss)
I0405 14:05:17.068245 18799 sgd_solver.cpp:105] Iteration 8712, lr = 0.0001
I0405 14:05:22.334985 18799 solver.cpp:218] Iteration 8724 (2.27847 iter/s, 5.2667s/12 iters), loss = 5.0503
I0405 14:05:22.335031 18799 solver.cpp:237]     Train net output #0: loss = 5.0503 (* 1 = 5.0503 loss)
I0405 14:05:22.335038 18799 sgd_solver.cpp:105] Iteration 8724, lr = 0.0001
I0405 14:05:27.673764 18799 solver.cpp:218] Iteration 8736 (2.24775 iter/s, 5.33868s/12 iters), loss = 4.98893
I0405 14:05:27.673820 18799 solver.cpp:237]     Train net output #0: loss = 4.98893 (* 1 = 4.98893 loss)
I0405 14:05:27.673827 18799 sgd_solver.cpp:105] Iteration 8736, lr = 0.0001
I0405 14:05:32.797619 18799 solver.cpp:218] Iteration 8748 (2.34203 iter/s, 5.12375s/12 iters), loss = 5.06434
I0405 14:05:32.797674 18799 solver.cpp:237]     Train net output #0: loss = 5.06434 (* 1 = 5.06434 loss)
I0405 14:05:32.797683 18799 sgd_solver.cpp:105] Iteration 8748, lr = 0.0001
I0405 14:05:38.066817 18799 solver.cpp:218] Iteration 8760 (2.27743 iter/s, 5.26909s/12 iters), loss = 5.13208
I0405 14:05:38.066910 18799 solver.cpp:237]     Train net output #0: loss = 5.13208 (* 1 = 5.13208 loss)
I0405 14:05:38.066917 18799 sgd_solver.cpp:105] Iteration 8760, lr = 0.0001
I0405 14:05:42.702585 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel
I0405 14:05:46.589618 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate
I0405 14:05:50.353940 18799 solver.cpp:330] Iteration 8772, Testing net (#0)
I0405 14:05:50.353957 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:05:51.295529 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:05:54.758656 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0214461
I0405 14:05:54.758692 18799 solver.cpp:397]     Test net output #1: loss = 5.03591 (* 1 = 5.03591 loss)
I0405 14:05:54.895854 18799 solver.cpp:218] Iteration 8772 (0.713062 iter/s, 16.8288s/12 iters), loss = 4.99103
I0405 14:05:54.895896 18799 solver.cpp:237]     Train net output #0: loss = 4.99103 (* 1 = 4.99103 loss)
I0405 14:05:54.895902 18799 sgd_solver.cpp:105] Iteration 8772, lr = 0.0001
I0405 14:05:59.092545 18799 solver.cpp:218] Iteration 8784 (2.85945 iter/s, 4.19661s/12 iters), loss = 5.16057
I0405 14:05:59.092589 18799 solver.cpp:237]     Train net output #0: loss = 5.16057 (* 1 = 5.16057 loss)
I0405 14:05:59.092594 18799 sgd_solver.cpp:105] Iteration 8784, lr = 0.0001
I0405 14:06:04.610641 18799 solver.cpp:218] Iteration 8796 (2.1747 iter/s, 5.51801s/12 iters), loss = 5.05234
I0405 14:06:04.610682 18799 solver.cpp:237]     Train net output #0: loss = 5.05234 (* 1 = 5.05234 loss)
I0405 14:06:04.610688 18799 sgd_solver.cpp:105] Iteration 8796, lr = 0.0001
I0405 14:06:06.115976 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:06:09.810678 18799 solver.cpp:218] Iteration 8808 (2.30771 iter/s, 5.19995s/12 iters), loss = 5.05547
I0405 14:06:09.810806 18799 solver.cpp:237]     Train net output #0: loss = 5.05547 (* 1 = 5.05547 loss)
I0405 14:06:09.810813 18799 sgd_solver.cpp:105] Iteration 8808, lr = 0.0001
I0405 14:06:15.077510 18799 solver.cpp:218] Iteration 8820 (2.27848 iter/s, 5.26666s/12 iters), loss = 4.91265
I0405 14:06:15.077553 18799 solver.cpp:237]     Train net output #0: loss = 4.91265 (* 1 = 4.91265 loss)
I0405 14:06:15.077558 18799 sgd_solver.cpp:105] Iteration 8820, lr = 0.0001
I0405 14:06:20.065951 18799 solver.cpp:218] Iteration 8832 (2.40561 iter/s, 4.98835s/12 iters), loss = 5.00664
I0405 14:06:20.066004 18799 solver.cpp:237]     Train net output #0: loss = 5.00664 (* 1 = 5.00664 loss)
I0405 14:06:20.066011 18799 sgd_solver.cpp:105] Iteration 8832, lr = 0.0001
I0405 14:06:25.406075 18799 solver.cpp:218] Iteration 8844 (2.24718 iter/s, 5.34003s/12 iters), loss = 4.99454
I0405 14:06:25.406118 18799 solver.cpp:237]     Train net output #0: loss = 4.99454 (* 1 = 4.99454 loss)
I0405 14:06:25.406124 18799 sgd_solver.cpp:105] Iteration 8844, lr = 0.0001
I0405 14:06:30.670893 18799 solver.cpp:218] Iteration 8856 (2.27932 iter/s, 5.26473s/12 iters), loss = 4.96579
I0405 14:06:30.670930 18799 solver.cpp:237]     Train net output #0: loss = 4.96579 (* 1 = 4.96579 loss)
I0405 14:06:30.670935 18799 sgd_solver.cpp:105] Iteration 8856, lr = 0.0001
I0405 14:06:35.933276 18799 solver.cpp:218] Iteration 8868 (2.28038 iter/s, 5.26229s/12 iters), loss = 5.04479
I0405 14:06:35.933339 18799 solver.cpp:237]     Train net output #0: loss = 5.04479 (* 1 = 5.04479 loss)
I0405 14:06:35.933352 18799 sgd_solver.cpp:105] Iteration 8868, lr = 0.0001
I0405 14:06:38.080044 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel
I0405 14:06:41.893244 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate
I0405 14:06:45.568753 18799 solver.cpp:330] Iteration 8874, Testing net (#0)
I0405 14:06:45.568774 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:06:46.428115 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:06:49.909323 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:06:49.909371 18799 solver.cpp:397]     Test net output #1: loss = 5.03642 (* 1 = 5.03642 loss)
I0405 14:06:51.946045 18799 solver.cpp:218] Iteration 8880 (0.74941 iter/s, 16.0126s/12 iters), loss = 4.99046
I0405 14:06:51.946099 18799 solver.cpp:237]     Train net output #0: loss = 4.99046 (* 1 = 4.99046 loss)
I0405 14:06:51.946105 18799 sgd_solver.cpp:105] Iteration 8880, lr = 0.0001
I0405 14:06:57.033674 18799 solver.cpp:218] Iteration 8892 (2.35871 iter/s, 5.08753s/12 iters), loss = 4.96802
I0405 14:06:57.033725 18799 solver.cpp:237]     Train net output #0: loss = 4.96802 (* 1 = 4.96802 loss)
I0405 14:06:57.033733 18799 sgd_solver.cpp:105] Iteration 8892, lr = 0.0001
I0405 14:07:00.850528 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:07:02.425693 18799 solver.cpp:218] Iteration 8904 (2.22555 iter/s, 5.39192s/12 iters), loss = 5.12431
I0405 14:07:02.425734 18799 solver.cpp:237]     Train net output #0: loss = 5.12431 (* 1 = 5.12431 loss)
I0405 14:07:02.425740 18799 sgd_solver.cpp:105] Iteration 8904, lr = 0.0001
I0405 14:07:07.591842 18799 solver.cpp:218] Iteration 8916 (2.32285 iter/s, 5.16606s/12 iters), loss = 4.98705
I0405 14:07:07.591892 18799 solver.cpp:237]     Train net output #0: loss = 4.98705 (* 1 = 4.98705 loss)
I0405 14:07:07.591899 18799 sgd_solver.cpp:105] Iteration 8916, lr = 0.0001
I0405 14:07:12.975807 18799 solver.cpp:218] Iteration 8928 (2.22888 iter/s, 5.38387s/12 iters), loss = 5.1227
I0405 14:07:12.975953 18799 solver.cpp:237]     Train net output #0: loss = 5.1227 (* 1 = 5.1227 loss)
I0405 14:07:12.975962 18799 sgd_solver.cpp:105] Iteration 8928, lr = 0.0001
I0405 14:07:18.384258 18799 solver.cpp:218] Iteration 8940 (2.21883 iter/s, 5.40826s/12 iters), loss = 4.99719
I0405 14:07:18.384313 18799 solver.cpp:237]     Train net output #0: loss = 4.99719 (* 1 = 4.99719 loss)
I0405 14:07:18.384321 18799 sgd_solver.cpp:105] Iteration 8940, lr = 0.0001
I0405 14:07:23.744252 18799 solver.cpp:218] Iteration 8952 (2.23885 iter/s, 5.3599s/12 iters), loss = 5.03922
I0405 14:07:23.744294 18799 solver.cpp:237]     Train net output #0: loss = 5.03922 (* 1 = 5.03922 loss)
I0405 14:07:23.744300 18799 sgd_solver.cpp:105] Iteration 8952, lr = 0.0001
I0405 14:07:29.006806 18799 solver.cpp:218] Iteration 8964 (2.2803 iter/s, 5.26247s/12 iters), loss = 4.91215
I0405 14:07:29.006845 18799 solver.cpp:237]     Train net output #0: loss = 4.91215 (* 1 = 4.91215 loss)
I0405 14:07:29.006851 18799 sgd_solver.cpp:105] Iteration 8964, lr = 0.0001
I0405 14:07:33.567611 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel
I0405 14:07:36.700500 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate
I0405 14:07:40.431622 18799 solver.cpp:330] Iteration 8976, Testing net (#0)
I0405 14:07:40.431638 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:07:41.274791 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:07:44.718472 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0269608
I0405 14:07:44.718571 18799 solver.cpp:397]     Test net output #1: loss = 5.03322 (* 1 = 5.03322 loss)
I0405 14:07:44.860581 18799 solver.cpp:218] Iteration 8976 (0.756924 iter/s, 15.8536s/12 iters), loss = 4.94364
I0405 14:07:44.860641 18799 solver.cpp:237]     Train net output #0: loss = 4.94364 (* 1 = 4.94364 loss)
I0405 14:07:44.860647 18799 sgd_solver.cpp:105] Iteration 8976, lr = 0.0001
I0405 14:07:49.386449 18799 solver.cpp:218] Iteration 8988 (2.65149 iter/s, 4.52576s/12 iters), loss = 5.05138
I0405 14:07:49.386492 18799 solver.cpp:237]     Train net output #0: loss = 5.05138 (* 1 = 5.05138 loss)
I0405 14:07:49.386498 18799 sgd_solver.cpp:105] Iteration 8988, lr = 0.0001
I0405 14:07:52.754160 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:07:54.535058 18799 solver.cpp:218] Iteration 9000 (2.33077 iter/s, 5.14852s/12 iters), loss = 5.04066
I0405 14:07:54.535102 18799 solver.cpp:237]     Train net output #0: loss = 5.04066 (* 1 = 5.04066 loss)
I0405 14:07:54.535109 18799 sgd_solver.cpp:105] Iteration 9000, lr = 0.0001
I0405 14:07:55.278105 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:08:00.000773 18799 solver.cpp:218] Iteration 9012 (2.19554 iter/s, 5.46563s/12 iters), loss = 4.98897
I0405 14:08:00.000814 18799 solver.cpp:237]     Train net output #0: loss = 4.98897 (* 1 = 4.98897 loss)
I0405 14:08:00.000820 18799 sgd_solver.cpp:105] Iteration 9012, lr = 0.0001
I0405 14:08:05.196341 18799 solver.cpp:218] Iteration 9024 (2.3097 iter/s, 5.19548s/12 iters), loss = 4.97611
I0405 14:08:05.196379 18799 solver.cpp:237]     Train net output #0: loss = 4.97611 (* 1 = 4.97611 loss)
I0405 14:08:05.196385 18799 sgd_solver.cpp:105] Iteration 9024, lr = 0.0001
I0405 14:08:10.459237 18799 solver.cpp:218] Iteration 9036 (2.28015 iter/s, 5.26281s/12 iters), loss = 5.07433
I0405 14:08:10.459282 18799 solver.cpp:237]     Train net output #0: loss = 5.07433 (* 1 = 5.07433 loss)
I0405 14:08:10.459290 18799 sgd_solver.cpp:105] Iteration 9036, lr = 0.0001
I0405 14:08:15.918442 18799 solver.cpp:218] Iteration 9048 (2.19816 iter/s, 5.45911s/12 iters), loss = 5.10371
I0405 14:08:15.918591 18799 solver.cpp:237]     Train net output #0: loss = 5.10371 (* 1 = 5.10371 loss)
I0405 14:08:15.918599 18799 sgd_solver.cpp:105] Iteration 9048, lr = 0.0001
I0405 14:08:21.298993 18799 solver.cpp:218] Iteration 9060 (2.23033 iter/s, 5.38036s/12 iters), loss = 5.03196
I0405 14:08:21.299031 18799 solver.cpp:237]     Train net output #0: loss = 5.03196 (* 1 = 5.03196 loss)
I0405 14:08:21.299036 18799 sgd_solver.cpp:105] Iteration 9060, lr = 0.0001
I0405 14:08:26.567416 18799 solver.cpp:218] Iteration 9072 (2.27776 iter/s, 5.26834s/12 iters), loss = 4.93087
I0405 14:08:26.567459 18799 solver.cpp:237]     Train net output #0: loss = 4.93087 (* 1 = 4.93087 loss)
I0405 14:08:26.567464 18799 sgd_solver.cpp:105] Iteration 9072, lr = 0.0001
I0405 14:08:28.548911 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel
I0405 14:08:31.800428 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate
I0405 14:08:35.623706 18799 solver.cpp:330] Iteration 9078, Testing net (#0)
I0405 14:08:35.623726 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:08:36.423363 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:08:39.965994 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:08:39.966027 18799 solver.cpp:397]     Test net output #1: loss = 5.02988 (* 1 = 5.02988 loss)
I0405 14:08:41.752133 18799 solver.cpp:218] Iteration 9084 (0.790276 iter/s, 15.1846s/12 iters), loss = 5.04932
I0405 14:08:41.752171 18799 solver.cpp:237]     Train net output #0: loss = 5.04932 (* 1 = 5.04932 loss)
I0405 14:08:41.752177 18799 sgd_solver.cpp:105] Iteration 9084, lr = 0.0001
I0405 14:08:47.084817 18799 solver.cpp:218] Iteration 9096 (2.25031 iter/s, 5.3326s/12 iters), loss = 5.03879
I0405 14:08:47.084939 18799 solver.cpp:237]     Train net output #0: loss = 5.03879 (* 1 = 5.03879 loss)
I0405 14:08:47.084949 18799 sgd_solver.cpp:105] Iteration 9096, lr = 0.0001
I0405 14:08:49.976224 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:08:52.312332 18799 solver.cpp:218] Iteration 9108 (2.29562 iter/s, 5.22735s/12 iters), loss = 5.00092
I0405 14:08:52.312378 18799 solver.cpp:237]     Train net output #0: loss = 5.00092 (* 1 = 5.00092 loss)
I0405 14:08:52.312384 18799 sgd_solver.cpp:105] Iteration 9108, lr = 0.0001
I0405 14:08:57.742563 18799 solver.cpp:218] Iteration 9120 (2.20989 iter/s, 5.43014s/12 iters), loss = 5.01697
I0405 14:08:57.742610 18799 solver.cpp:237]     Train net output #0: loss = 5.01697 (* 1 = 5.01697 loss)
I0405 14:08:57.742619 18799 sgd_solver.cpp:105] Iteration 9120, lr = 0.0001
I0405 14:09:03.122612 18799 solver.cpp:218] Iteration 9132 (2.2305 iter/s, 5.37995s/12 iters), loss = 5.04913
I0405 14:09:03.122673 18799 solver.cpp:237]     Train net output #0: loss = 5.04913 (* 1 = 5.04913 loss)
I0405 14:09:03.122681 18799 sgd_solver.cpp:105] Iteration 9132, lr = 0.0001
I0405 14:09:08.501940 18799 solver.cpp:218] Iteration 9144 (2.23081 iter/s, 5.37922s/12 iters), loss = 5.09092
I0405 14:09:08.501996 18799 solver.cpp:237]     Train net output #0: loss = 5.09092 (* 1 = 5.09092 loss)
I0405 14:09:08.502004 18799 sgd_solver.cpp:105] Iteration 9144, lr = 0.0001
I0405 14:09:13.695061 18799 solver.cpp:218] Iteration 9156 (2.31079 iter/s, 5.19302s/12 iters), loss = 5.03211
I0405 14:09:13.695101 18799 solver.cpp:237]     Train net output #0: loss = 5.03211 (* 1 = 5.03211 loss)
I0405 14:09:13.695107 18799 sgd_solver.cpp:105] Iteration 9156, lr = 0.0001
I0405 14:09:18.876693 18799 solver.cpp:218] Iteration 9168 (2.31591 iter/s, 5.18155s/12 iters), loss = 5.10486
I0405 14:09:18.876857 18799 solver.cpp:237]     Train net output #0: loss = 5.10486 (* 1 = 5.10486 loss)
I0405 14:09:18.876864 18799 sgd_solver.cpp:105] Iteration 9168, lr = 0.0001
I0405 14:09:23.614187 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel
I0405 14:09:26.691071 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate
I0405 14:09:30.519229 18799 solver.cpp:330] Iteration 9180, Testing net (#0)
I0405 14:09:30.519249 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:09:31.294939 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:09:34.939112 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 14:09:34.939146 18799 solver.cpp:397]     Test net output #1: loss = 5.02905 (* 1 = 5.02905 loss)
I0405 14:09:35.080888 18799 solver.cpp:218] Iteration 9180 (0.740561 iter/s, 16.2039s/12 iters), loss = 5.02605
I0405 14:09:35.080930 18799 solver.cpp:237]     Train net output #0: loss = 5.02605 (* 1 = 5.02605 loss)
I0405 14:09:35.080936 18799 sgd_solver.cpp:105] Iteration 9180, lr = 0.0001
I0405 14:09:39.415021 18799 solver.cpp:218] Iteration 9192 (2.76877 iter/s, 4.33405s/12 iters), loss = 4.97588
I0405 14:09:39.415066 18799 solver.cpp:237]     Train net output #0: loss = 4.97588 (* 1 = 4.97588 loss)
I0405 14:09:39.415071 18799 sgd_solver.cpp:105] Iteration 9192, lr = 0.0001
I0405 14:09:44.664796 18799 solver.cpp:218] Iteration 9204 (2.28585 iter/s, 5.24969s/12 iters), loss = 5.08291
I0405 14:09:44.664842 18799 solver.cpp:237]     Train net output #0: loss = 5.08291 (* 1 = 5.08291 loss)
I0405 14:09:44.664849 18799 sgd_solver.cpp:105] Iteration 9204, lr = 0.0001
I0405 14:09:44.696260 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:09:49.836252 18799 solver.cpp:218] Iteration 9216 (2.32047 iter/s, 5.17136s/12 iters), loss = 5.05551
I0405 14:09:49.836344 18799 solver.cpp:237]     Train net output #0: loss = 5.05551 (* 1 = 5.05551 loss)
I0405 14:09:49.836351 18799 sgd_solver.cpp:105] Iteration 9216, lr = 0.0001
I0405 14:09:55.241029 18799 solver.cpp:218] Iteration 9228 (2.22032 iter/s, 5.40464s/12 iters), loss = 5.05682
I0405 14:09:55.241083 18799 solver.cpp:237]     Train net output #0: loss = 5.05682 (* 1 = 5.05682 loss)
I0405 14:09:55.241098 18799 sgd_solver.cpp:105] Iteration 9228, lr = 0.0001
I0405 14:10:00.545495 18799 solver.cpp:218] Iteration 9240 (2.26229 iter/s, 5.30437s/12 iters), loss = 5.08379
I0405 14:10:00.545544 18799 solver.cpp:237]     Train net output #0: loss = 5.08379 (* 1 = 5.08379 loss)
I0405 14:10:00.545552 18799 sgd_solver.cpp:105] Iteration 9240, lr = 0.0001
I0405 14:10:05.920284 18799 solver.cpp:218] Iteration 9252 (2.23268 iter/s, 5.3747s/12 iters), loss = 5.08544
I0405 14:10:05.920337 18799 solver.cpp:237]     Train net output #0: loss = 5.08544 (* 1 = 5.08544 loss)
I0405 14:10:05.920346 18799 sgd_solver.cpp:105] Iteration 9252, lr = 0.0001
I0405 14:10:11.222586 18799 solver.cpp:218] Iteration 9264 (2.26321 iter/s, 5.3022s/12 iters), loss = 4.98156
I0405 14:10:11.222628 18799 solver.cpp:237]     Train net output #0: loss = 4.98156 (* 1 = 4.98156 loss)
I0405 14:10:11.222635 18799 sgd_solver.cpp:105] Iteration 9264, lr = 0.0001
I0405 14:10:16.400377 18799 solver.cpp:218] Iteration 9276 (2.31763 iter/s, 5.1777s/12 iters), loss = 5.01431
I0405 14:10:16.400422 18799 solver.cpp:237]     Train net output #0: loss = 5.01431 (* 1 = 5.01431 loss)
I0405 14:10:16.400429 18799 sgd_solver.cpp:105] Iteration 9276, lr = 0.0001
I0405 14:10:18.585940 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel
I0405 14:10:21.581974 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate
I0405 14:10:25.372429 18799 solver.cpp:330] Iteration 9282, Testing net (#0)
I0405 14:10:25.372450 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:10:26.112473 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:10:29.731036 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0238971
I0405 14:10:29.731073 18799 solver.cpp:397]     Test net output #1: loss = 5.02734 (* 1 = 5.02734 loss)
I0405 14:10:31.787286 18799 solver.cpp:218] Iteration 9288 (0.779891 iter/s, 15.3868s/12 iters), loss = 5.02139
I0405 14:10:31.793495 18799 solver.cpp:237]     Train net output #0: loss = 5.02139 (* 1 = 5.02139 loss)
I0405 14:10:31.793515 18799 sgd_solver.cpp:105] Iteration 9288, lr = 0.0001
I0405 14:10:36.992568 18799 solver.cpp:218] Iteration 9300 (2.30812 iter/s, 5.19905s/12 iters), loss = 4.93252
I0405 14:10:36.992610 18799 solver.cpp:237]     Train net output #0: loss = 4.93252 (* 1 = 4.93252 loss)
I0405 14:10:36.992616 18799 sgd_solver.cpp:105] Iteration 9300, lr = 0.0001
I0405 14:10:39.596686 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:10:42.508751 18799 solver.cpp:218] Iteration 9312 (2.17545 iter/s, 5.51609s/12 iters), loss = 4.96068
I0405 14:10:42.508792 18799 solver.cpp:237]     Train net output #0: loss = 4.96068 (* 1 = 4.96068 loss)
I0405 14:10:42.508798 18799 sgd_solver.cpp:105] Iteration 9312, lr = 0.0001
I0405 14:10:47.952584 18799 solver.cpp:218] Iteration 9324 (2.20437 iter/s, 5.44374s/12 iters), loss = 5.00806
I0405 14:10:47.952644 18799 solver.cpp:237]     Train net output #0: loss = 5.00806 (* 1 = 5.00806 loss)
I0405 14:10:47.952653 18799 sgd_solver.cpp:105] Iteration 9324, lr = 0.0001
I0405 14:10:53.157917 18799 solver.cpp:218] Iteration 9336 (2.30537 iter/s, 5.20523s/12 iters), loss = 5.07235
I0405 14:10:53.158025 18799 solver.cpp:237]     Train net output #0: loss = 5.07235 (* 1 = 5.07235 loss)
I0405 14:10:53.158033 18799 sgd_solver.cpp:105] Iteration 9336, lr = 0.0001
I0405 14:10:58.346447 18799 solver.cpp:218] Iteration 9348 (2.31286 iter/s, 5.18838s/12 iters), loss = 5.05027
I0405 14:10:58.346493 18799 solver.cpp:237]     Train net output #0: loss = 5.05027 (* 1 = 5.05027 loss)
I0405 14:10:58.346501 18799 sgd_solver.cpp:105] Iteration 9348, lr = 0.0001
I0405 14:11:03.606076 18799 solver.cpp:218] Iteration 9360 (2.28157 iter/s, 5.25954s/12 iters), loss = 5.05236
I0405 14:11:03.606120 18799 solver.cpp:237]     Train net output #0: loss = 5.05236 (* 1 = 5.05236 loss)
I0405 14:11:03.606127 18799 sgd_solver.cpp:105] Iteration 9360, lr = 0.0001
I0405 14:11:09.004035 18799 solver.cpp:218] Iteration 9372 (2.2231 iter/s, 5.39787s/12 iters), loss = 5.13974
I0405 14:11:09.004076 18799 solver.cpp:237]     Train net output #0: loss = 5.13974 (* 1 = 5.13974 loss)
I0405 14:11:09.004082 18799 sgd_solver.cpp:105] Iteration 9372, lr = 0.0001
I0405 14:11:13.653148 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel
I0405 14:11:17.498777 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate
I0405 14:11:21.196593 18799 solver.cpp:330] Iteration 9384, Testing net (#0)
I0405 14:11:21.196614 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:11:21.949335 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:11:25.575990 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0220588
I0405 14:11:25.576110 18799 solver.cpp:397]     Test net output #1: loss = 5.02132 (* 1 = 5.02132 loss)
I0405 14:11:25.714848 18799 solver.cpp:218] Iteration 9384 (0.718104 iter/s, 16.7107s/12 iters), loss = 4.99052
I0405 14:11:25.714895 18799 solver.cpp:237]     Train net output #0: loss = 4.99052 (* 1 = 4.99052 loss)
I0405 14:11:25.714900 18799 sgd_solver.cpp:105] Iteration 9384, lr = 0.0001
I0405 14:11:30.104667 18799 solver.cpp:218] Iteration 9396 (2.73365 iter/s, 4.38973s/12 iters), loss = 5.02456
I0405 14:11:30.104712 18799 solver.cpp:237]     Train net output #0: loss = 5.02456 (* 1 = 5.02456 loss)
I0405 14:11:30.104717 18799 sgd_solver.cpp:105] Iteration 9396, lr = 0.0001
I0405 14:11:34.715584 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:11:35.451304 18799 solver.cpp:218] Iteration 9408 (2.24444 iter/s, 5.34654s/12 iters), loss = 5.05902
I0405 14:11:35.451359 18799 solver.cpp:237]     Train net output #0: loss = 5.05902 (* 1 = 5.05902 loss)
I0405 14:11:35.451367 18799 sgd_solver.cpp:105] Iteration 9408, lr = 0.0001
I0405 14:11:40.707401 18799 solver.cpp:218] Iteration 9420 (2.28311 iter/s, 5.256s/12 iters), loss = 5.07158
I0405 14:11:40.707444 18799 solver.cpp:237]     Train net output #0: loss = 5.07158 (* 1 = 5.07158 loss)
I0405 14:11:40.707450 18799 sgd_solver.cpp:105] Iteration 9420, lr = 0.0001
I0405 14:11:46.124917 18799 solver.cpp:218] Iteration 9432 (2.21507 iter/s, 5.41743s/12 iters), loss = 4.99211
I0405 14:11:46.124960 18799 solver.cpp:237]     Train net output #0: loss = 4.99211 (* 1 = 4.99211 loss)
I0405 14:11:46.124969 18799 sgd_solver.cpp:105] Iteration 9432, lr = 0.0001
I0405 14:11:51.218204 18799 solver.cpp:218] Iteration 9444 (2.35608 iter/s, 5.0932s/12 iters), loss = 4.93314
I0405 14:11:51.218245 18799 solver.cpp:237]     Train net output #0: loss = 4.93314 (* 1 = 4.93314 loss)
I0405 14:11:51.218250 18799 sgd_solver.cpp:105] Iteration 9444, lr = 0.0001
I0405 14:11:56.463016 18799 solver.cpp:218] Iteration 9456 (2.28801 iter/s, 5.24473s/12 iters), loss = 5.03206
I0405 14:11:56.463150 18799 solver.cpp:237]     Train net output #0: loss = 5.03206 (* 1 = 5.03206 loss)
I0405 14:11:56.463157 18799 sgd_solver.cpp:105] Iteration 9456, lr = 0.0001
I0405 14:12:01.801931 18799 solver.cpp:218] Iteration 9468 (2.24772 iter/s, 5.33873s/12 iters), loss = 5.05832
I0405 14:12:01.801978 18799 solver.cpp:237]     Train net output #0: loss = 5.05832 (* 1 = 5.05832 loss)
I0405 14:12:01.801985 18799 sgd_solver.cpp:105] Iteration 9468, lr = 0.0001
I0405 14:12:06.889043 18799 solver.cpp:218] Iteration 9480 (2.35894 iter/s, 5.08702s/12 iters), loss = 4.99759
I0405 14:12:06.889089 18799 solver.cpp:237]     Train net output #0: loss = 4.99759 (* 1 = 4.99759 loss)
I0405 14:12:06.889097 18799 sgd_solver.cpp:105] Iteration 9480, lr = 0.0001
I0405 14:12:08.968247 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel
I0405 14:12:12.174932 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate
I0405 14:12:15.941915 18799 solver.cpp:330] Iteration 9486, Testing net (#0)
I0405 14:12:15.941936 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:12:16.630931 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:12:20.456537 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:12:20.456573 18799 solver.cpp:397]     Test net output #1: loss = 5.02025 (* 1 = 5.02025 loss)
I0405 14:12:22.471010 18799 solver.cpp:218] Iteration 9492 (0.770128 iter/s, 15.5818s/12 iters), loss = 5.10642
I0405 14:12:22.471058 18799 solver.cpp:237]     Train net output #0: loss = 5.10642 (* 1 = 5.10642 loss)
I0405 14:12:22.471066 18799 sgd_solver.cpp:105] Iteration 9492, lr = 0.0001
I0405 14:12:27.756645 18799 solver.cpp:218] Iteration 9504 (2.27034 iter/s, 5.28554s/12 iters), loss = 4.97316
I0405 14:12:27.756755 18799 solver.cpp:237]     Train net output #0: loss = 4.97316 (* 1 = 4.97316 loss)
I0405 14:12:27.756763 18799 sgd_solver.cpp:105] Iteration 9504, lr = 0.0001
I0405 14:12:29.332690 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:12:33.155560 18799 solver.cpp:218] Iteration 9516 (2.22273 iter/s, 5.39876s/12 iters), loss = 4.96534
I0405 14:12:33.155611 18799 solver.cpp:237]     Train net output #0: loss = 4.96534 (* 1 = 4.96534 loss)
I0405 14:12:33.155618 18799 sgd_solver.cpp:105] Iteration 9516, lr = 0.0001
I0405 14:12:38.504725 18799 solver.cpp:218] Iteration 9528 (2.24338 iter/s, 5.34907s/12 iters), loss = 4.99901
I0405 14:12:38.504776 18799 solver.cpp:237]     Train net output #0: loss = 4.99901 (* 1 = 4.99901 loss)
I0405 14:12:38.504786 18799 sgd_solver.cpp:105] Iteration 9528, lr = 0.0001
I0405 14:12:43.884770 18799 solver.cpp:218] Iteration 9540 (2.23051 iter/s, 5.37995s/12 iters), loss = 4.93587
I0405 14:12:43.884832 18799 solver.cpp:237]     Train net output #0: loss = 4.93587 (* 1 = 4.93587 loss)
I0405 14:12:43.884841 18799 sgd_solver.cpp:105] Iteration 9540, lr = 0.0001
I0405 14:12:49.189007 18799 solver.cpp:218] Iteration 9552 (2.26239 iter/s, 5.30414s/12 iters), loss = 4.95922
I0405 14:12:49.189047 18799 solver.cpp:237]     Train net output #0: loss = 4.95922 (* 1 = 4.95922 loss)
I0405 14:12:49.189052 18799 sgd_solver.cpp:105] Iteration 9552, lr = 0.0001
I0405 14:12:54.497370 18799 solver.cpp:218] Iteration 9564 (2.26062 iter/s, 5.30828s/12 iters), loss = 5.03433
I0405 14:12:54.497414 18799 solver.cpp:237]     Train net output #0: loss = 5.03433 (* 1 = 5.03433 loss)
I0405 14:12:54.497421 18799 sgd_solver.cpp:105] Iteration 9564, lr = 0.0001
I0405 14:13:00.189633 18799 solver.cpp:218] Iteration 9576 (2.10816 iter/s, 5.69217s/12 iters), loss = 5.03149
I0405 14:13:00.189757 18799 solver.cpp:237]     Train net output #0: loss = 5.03149 (* 1 = 5.03149 loss)
I0405 14:13:00.189764 18799 sgd_solver.cpp:105] Iteration 9576, lr = 0.0001
I0405 14:13:05.012956 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel
I0405 14:13:09.786720 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate
I0405 14:13:14.667415 18799 solver.cpp:330] Iteration 9588, Testing net (#0)
I0405 14:13:14.667436 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:13:15.310144 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:13:19.009692 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:13:19.009732 18799 solver.cpp:397]     Test net output #1: loss = 5.02055 (* 1 = 5.02055 loss)
I0405 14:13:19.145046 18799 solver.cpp:218] Iteration 9588 (0.633072 iter/s, 18.9552s/12 iters), loss = 4.99982
I0405 14:13:19.145089 18799 solver.cpp:237]     Train net output #0: loss = 4.99982 (* 1 = 4.99982 loss)
I0405 14:13:19.145095 18799 sgd_solver.cpp:105] Iteration 9588, lr = 0.0001
I0405 14:13:23.429805 18799 solver.cpp:218] Iteration 9600 (2.80068 iter/s, 4.28467s/12 iters), loss = 4.96126
I0405 14:13:23.429848 18799 solver.cpp:237]     Train net output #0: loss = 4.96126 (* 1 = 4.96126 loss)
I0405 14:13:23.429854 18799 sgd_solver.cpp:105] Iteration 9600, lr = 0.0001
I0405 14:13:27.186220 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:13:28.624871 18799 solver.cpp:218] Iteration 9612 (2.30992 iter/s, 5.19498s/12 iters), loss = 5.0037
I0405 14:13:28.624917 18799 solver.cpp:237]     Train net output #0: loss = 5.0037 (* 1 = 5.0037 loss)
I0405 14:13:28.624923 18799 sgd_solver.cpp:105] Iteration 9612, lr = 0.0001
I0405 14:13:33.935864 18799 solver.cpp:218] Iteration 9624 (2.2595 iter/s, 5.31091s/12 iters), loss = 5.05404
I0405 14:13:33.935951 18799 solver.cpp:237]     Train net output #0: loss = 5.05404 (* 1 = 5.05404 loss)
I0405 14:13:33.935958 18799 sgd_solver.cpp:105] Iteration 9624, lr = 0.0001
I0405 14:13:39.336730 18799 solver.cpp:218] Iteration 9636 (2.22192 iter/s, 5.40073s/12 iters), loss = 5.05728
I0405 14:13:39.336778 18799 solver.cpp:237]     Train net output #0: loss = 5.05728 (* 1 = 5.05728 loss)
I0405 14:13:39.336788 18799 sgd_solver.cpp:105] Iteration 9636, lr = 0.0001
I0405 14:13:44.406544 18799 solver.cpp:218] Iteration 9648 (2.36699 iter/s, 5.06973s/12 iters), loss = 4.95802
I0405 14:13:44.406582 18799 solver.cpp:237]     Train net output #0: loss = 4.95802 (* 1 = 4.95802 loss)
I0405 14:13:44.406589 18799 sgd_solver.cpp:105] Iteration 9648, lr = 0.0001
I0405 14:13:49.612272 18799 solver.cpp:218] Iteration 9660 (2.30519 iter/s, 5.20564s/12 iters), loss = 4.94761
I0405 14:13:49.612316 18799 solver.cpp:237]     Train net output #0: loss = 4.94761 (* 1 = 4.94761 loss)
I0405 14:13:49.612321 18799 sgd_solver.cpp:105] Iteration 9660, lr = 0.0001
I0405 14:13:54.967442 18799 solver.cpp:218] Iteration 9672 (2.24086 iter/s, 5.35508s/12 iters), loss = 4.92807
I0405 14:13:54.967499 18799 solver.cpp:237]     Train net output #0: loss = 4.92807 (* 1 = 4.92807 loss)
I0405 14:13:54.967507 18799 sgd_solver.cpp:105] Iteration 9672, lr = 0.0001
I0405 14:14:00.305526 18799 solver.cpp:218] Iteration 9684 (2.24804 iter/s, 5.33798s/12 iters), loss = 5.00107
I0405 14:14:00.305577 18799 solver.cpp:237]     Train net output #0: loss = 5.00107 (* 1 = 5.00107 loss)
I0405 14:14:00.305584 18799 sgd_solver.cpp:105] Iteration 9684, lr = 0.0001
I0405 14:14:02.547178 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel
I0405 14:14:08.379283 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate
I0405 14:14:13.818323 18799 solver.cpp:330] Iteration 9690, Testing net (#0)
I0405 14:14:13.818343 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:14:14.386319 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:14:17.248438 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:14:18.221730 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0232843
I0405 14:14:18.221758 18799 solver.cpp:397]     Test net output #1: loss = 5.01707 (* 1 = 5.01707 loss)
I0405 14:14:20.183199 18799 solver.cpp:218] Iteration 9696 (0.603698 iter/s, 19.8775s/12 iters), loss = 4.9677
I0405 14:14:20.183260 18799 solver.cpp:237]     Train net output #0: loss = 4.9677 (* 1 = 4.9677 loss)
I0405 14:14:20.183269 18799 sgd_solver.cpp:105] Iteration 9696, lr = 0.0001
I0405 14:14:25.509544 18799 solver.cpp:218] Iteration 9708 (2.253 iter/s, 5.32624s/12 iters), loss = 4.98769
I0405 14:14:25.509596 18799 solver.cpp:237]     Train net output #0: loss = 4.98769 (* 1 = 4.98769 loss)
I0405 14:14:25.509605 18799 sgd_solver.cpp:105] Iteration 9708, lr = 0.0001
I0405 14:14:26.257755 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:14:30.842325 18799 solver.cpp:218] Iteration 9720 (2.25027 iter/s, 5.33269s/12 iters), loss = 4.96608
I0405 14:14:30.842372 18799 solver.cpp:237]     Train net output #0: loss = 4.96608 (* 1 = 4.96608 loss)
I0405 14:14:30.842379 18799 sgd_solver.cpp:105] Iteration 9720, lr = 0.0001
I0405 14:14:36.282307 18799 solver.cpp:218] Iteration 9732 (2.20593 iter/s, 5.43989s/12 iters), loss = 4.93937
I0405 14:14:36.282352 18799 solver.cpp:237]     Train net output #0: loss = 4.93937 (* 1 = 4.93937 loss)
I0405 14:14:36.282358 18799 sgd_solver.cpp:105] Iteration 9732, lr = 0.0001
I0405 14:14:41.518182 18799 solver.cpp:218] Iteration 9744 (2.29192 iter/s, 5.23578s/12 iters), loss = 5.04498
I0405 14:14:41.518272 18799 solver.cpp:237]     Train net output #0: loss = 5.04498 (* 1 = 5.04498 loss)
I0405 14:14:41.518278 18799 sgd_solver.cpp:105] Iteration 9744, lr = 0.0001
I0405 14:14:47.069480 18799 solver.cpp:218] Iteration 9756 (2.16171 iter/s, 5.55117s/12 iters), loss = 5.04216
I0405 14:14:47.069520 18799 solver.cpp:237]     Train net output #0: loss = 5.04216 (* 1 = 5.04216 loss)
I0405 14:14:47.069526 18799 sgd_solver.cpp:105] Iteration 9756, lr = 0.0001
I0405 14:14:52.527943 18799 solver.cpp:218] Iteration 9768 (2.19846 iter/s, 5.45837s/12 iters), loss = 5.03274
I0405 14:14:52.527992 18799 solver.cpp:237]     Train net output #0: loss = 5.03274 (* 1 = 5.03274 loss)
I0405 14:14:52.527999 18799 sgd_solver.cpp:105] Iteration 9768, lr = 0.0001
I0405 14:14:57.574615 18799 solver.cpp:218] Iteration 9780 (2.37785 iter/s, 5.04658s/12 iters), loss = 4.89289
I0405 14:14:57.574666 18799 solver.cpp:237]     Train net output #0: loss = 4.89289 (* 1 = 4.89289 loss)
I0405 14:14:57.574676 18799 sgd_solver.cpp:105] Iteration 9780, lr = 0.0001
I0405 14:15:02.461021 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel
I0405 14:15:06.905166 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate
I0405 14:15:09.937348 18799 solver.cpp:330] Iteration 9792, Testing net (#0)
I0405 14:15:09.937366 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:15:10.470743 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:15:14.437968 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 14:15:14.438120 18799 solver.cpp:397]     Test net output #1: loss = 5.01229 (* 1 = 5.01229 loss)
I0405 14:15:14.579947 18799 solver.cpp:218] Iteration 9792 (0.705667 iter/s, 17.0052s/12 iters), loss = 4.99855
I0405 14:15:14.580019 18799 solver.cpp:237]     Train net output #0: loss = 4.99855 (* 1 = 4.99855 loss)
I0405 14:15:14.580029 18799 sgd_solver.cpp:105] Iteration 9792, lr = 0.0001
I0405 14:15:18.636801 18799 solver.cpp:218] Iteration 9804 (2.95804 iter/s, 4.05674s/12 iters), loss = 5.04709
I0405 14:15:18.636860 18799 solver.cpp:237]     Train net output #0: loss = 5.04709 (* 1 = 5.04709 loss)
I0405 14:15:18.636869 18799 sgd_solver.cpp:105] Iteration 9804, lr = 0.0001
I0405 14:15:21.834636 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:15:23.931304 18799 solver.cpp:218] Iteration 9816 (2.26655 iter/s, 5.2944s/12 iters), loss = 4.9325
I0405 14:15:23.931363 18799 solver.cpp:237]     Train net output #0: loss = 4.9325 (* 1 = 4.9325 loss)
I0405 14:15:23.931373 18799 sgd_solver.cpp:105] Iteration 9816, lr = 0.0001
I0405 14:15:29.231925 18799 solver.cpp:218] Iteration 9828 (2.26393 iter/s, 5.30052s/12 iters), loss = 4.98738
I0405 14:15:29.231968 18799 solver.cpp:237]     Train net output #0: loss = 4.98738 (* 1 = 4.98738 loss)
I0405 14:15:29.231973 18799 sgd_solver.cpp:105] Iteration 9828, lr = 0.0001
I0405 14:15:34.585669 18799 solver.cpp:218] Iteration 9840 (2.24146 iter/s, 5.35366s/12 iters), loss = 5.03054
I0405 14:15:34.585702 18799 solver.cpp:237]     Train net output #0: loss = 5.03054 (* 1 = 5.03054 loss)
I0405 14:15:34.585708 18799 sgd_solver.cpp:105] Iteration 9840, lr = 0.0001
I0405 14:15:40.062660 18799 solver.cpp:218] Iteration 9852 (2.19102 iter/s, 5.47691s/12 iters), loss = 5.04043
I0405 14:15:40.062708 18799 solver.cpp:237]     Train net output #0: loss = 5.04043 (* 1 = 5.04043 loss)
I0405 14:15:40.062716 18799 sgd_solver.cpp:105] Iteration 9852, lr = 0.0001
I0405 14:15:45.125517 18799 solver.cpp:218] Iteration 9864 (2.37025 iter/s, 5.06277s/12 iters), loss = 5.01683
I0405 14:15:45.125627 18799 solver.cpp:237]     Train net output #0: loss = 5.01683 (* 1 = 5.01683 loss)
I0405 14:15:45.125636 18799 sgd_solver.cpp:105] Iteration 9864, lr = 0.0001
I0405 14:15:50.320053 18799 solver.cpp:218] Iteration 9876 (2.31019 iter/s, 5.19439s/12 iters), loss = 5.07344
I0405 14:15:50.320087 18799 solver.cpp:237]     Train net output #0: loss = 5.07344 (* 1 = 5.07344 loss)
I0405 14:15:50.320093 18799 sgd_solver.cpp:105] Iteration 9876, lr = 0.0001
I0405 14:15:55.599264 18799 solver.cpp:218] Iteration 9888 (2.2731 iter/s, 5.27913s/12 iters), loss = 4.97429
I0405 14:15:55.599321 18799 solver.cpp:237]     Train net output #0: loss = 4.97429 (* 1 = 4.97429 loss)
I0405 14:15:55.599329 18799 sgd_solver.cpp:105] Iteration 9888, lr = 0.0001
I0405 14:15:57.828795 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel
I0405 14:16:02.142159 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate
I0405 14:16:05.289748 18799 solver.cpp:330] Iteration 9894, Testing net (#0)
I0405 14:16:05.289767 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:16:05.779259 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:16:09.628602 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0257353
I0405 14:16:09.628651 18799 solver.cpp:397]     Test net output #1: loss = 5.01089 (* 1 = 5.01089 loss)
I0405 14:16:11.462158 18799 solver.cpp:218] Iteration 9900 (0.75649 iter/s, 15.8627s/12 iters), loss = 5.0682
I0405 14:16:11.462213 18799 solver.cpp:237]     Train net output #0: loss = 5.0682 (* 1 = 5.0682 loss)
I0405 14:16:11.462219 18799 sgd_solver.cpp:105] Iteration 9900, lr = 0.0001
I0405 14:16:16.807694 18799 solver.cpp:218] Iteration 9912 (2.24491 iter/s, 5.34543s/12 iters), loss = 5.05424
I0405 14:16:16.807875 18799 solver.cpp:237]     Train net output #0: loss = 5.05424 (* 1 = 5.05424 loss)
I0405 14:16:16.807884 18799 sgd_solver.cpp:105] Iteration 9912, lr = 0.0001
I0405 14:16:16.901098 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:16:22.170956 18799 solver.cpp:218] Iteration 9924 (2.23754 iter/s, 5.36304s/12 iters), loss = 5.09978
I0405 14:16:22.170994 18799 solver.cpp:237]     Train net output #0: loss = 5.09978 (* 1 = 5.09978 loss)
I0405 14:16:22.171000 18799 sgd_solver.cpp:105] Iteration 9924, lr = 0.0001
I0405 14:16:27.532016 18799 solver.cpp:218] Iteration 9936 (2.2384 iter/s, 5.36097s/12 iters), loss = 4.98343
I0405 14:16:27.532075 18799 solver.cpp:237]     Train net output #0: loss = 4.98343 (* 1 = 4.98343 loss)
I0405 14:16:27.532084 18799 sgd_solver.cpp:105] Iteration 9936, lr = 0.0001
I0405 14:16:32.853188 18799 solver.cpp:218] Iteration 9948 (2.25518 iter/s, 5.32107s/12 iters), loss = 4.98024
I0405 14:16:32.853229 18799 solver.cpp:237]     Train net output #0: loss = 4.98024 (* 1 = 4.98024 loss)
I0405 14:16:32.853235 18799 sgd_solver.cpp:105] Iteration 9948, lr = 0.0001
I0405 14:16:37.964340 18799 solver.cpp:218] Iteration 9960 (2.34785 iter/s, 5.11107s/12 iters), loss = 5.02468
I0405 14:16:37.964380 18799 solver.cpp:237]     Train net output #0: loss = 5.02468 (* 1 = 5.02468 loss)
I0405 14:16:37.964385 18799 sgd_solver.cpp:105] Iteration 9960, lr = 0.0001
I0405 14:16:43.259035 18799 solver.cpp:218] Iteration 9972 (2.26645 iter/s, 5.29461s/12 iters), loss = 4.98018
I0405 14:16:43.259078 18799 solver.cpp:237]     Train net output #0: loss = 4.98018 (* 1 = 4.98018 loss)
I0405 14:16:43.259083 18799 sgd_solver.cpp:105] Iteration 9972, lr = 0.0001
I0405 14:16:48.412559 18799 solver.cpp:218] Iteration 9984 (2.32854 iter/s, 5.15343s/12 iters), loss = 5.04222
I0405 14:16:48.412660 18799 solver.cpp:237]     Train net output #0: loss = 5.04222 (* 1 = 5.04222 loss)
I0405 14:16:48.412667 18799 sgd_solver.cpp:105] Iteration 9984, lr = 0.0001
I0405 14:16:53.199815 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel
I0405 14:16:57.532955 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate
I0405 14:17:01.152582 18799 solver.cpp:330] Iteration 9996, Testing net (#0)
I0405 14:17:01.152606 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:17:01.632274 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:17:05.517396 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0269608
I0405 14:17:05.517434 18799 solver.cpp:397]     Test net output #1: loss = 5.00828 (* 1 = 5.00828 loss)
I0405 14:17:05.659277 18799 solver.cpp:218] Iteration 9996 (0.695793 iter/s, 17.2465s/12 iters), loss = 5.03319
I0405 14:17:05.659319 18799 solver.cpp:237]     Train net output #0: loss = 5.03319 (* 1 = 5.03319 loss)
I0405 14:17:05.659325 18799 sgd_solver.cpp:105] Iteration 9996, lr = 0.0001
I0405 14:17:10.009377 18799 solver.cpp:218] Iteration 10008 (2.75861 iter/s, 4.35001s/12 iters), loss = 4.83465
I0405 14:17:10.009428 18799 solver.cpp:237]     Train net output #0: loss = 4.83465 (* 1 = 4.83465 loss)
I0405 14:17:10.009434 18799 sgd_solver.cpp:105] Iteration 10008, lr = 0.0001
I0405 14:17:12.317045 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:17:15.398195 18799 solver.cpp:218] Iteration 10020 (2.22687 iter/s, 5.38872s/12 iters), loss = 5.01296
I0405 14:17:15.398253 18799 solver.cpp:237]     Train net output #0: loss = 5.01296 (* 1 = 5.01296 loss)
I0405 14:17:15.398262 18799 sgd_solver.cpp:105] Iteration 10020, lr = 0.0001
I0405 14:17:20.683679 18799 solver.cpp:218] Iteration 10032 (2.27041 iter/s, 5.28539s/12 iters), loss = 5.03301
I0405 14:17:20.683794 18799 solver.cpp:237]     Train net output #0: loss = 5.03301 (* 1 = 5.03301 loss)
I0405 14:17:20.683800 18799 sgd_solver.cpp:105] Iteration 10032, lr = 0.0001
I0405 14:17:25.798774 18799 solver.cpp:218] Iteration 10044 (2.34607 iter/s, 5.11494s/12 iters), loss = 5.05814
I0405 14:17:25.798810 18799 solver.cpp:237]     Train net output #0: loss = 5.05814 (* 1 = 5.05814 loss)
I0405 14:17:25.798816 18799 sgd_solver.cpp:105] Iteration 10044, lr = 0.0001
I0405 14:17:31.067214 18799 solver.cpp:218] Iteration 10056 (2.27775 iter/s, 5.26835s/12 iters), loss = 5.03526
I0405 14:17:31.067274 18799 solver.cpp:237]     Train net output #0: loss = 5.03526 (* 1 = 5.03526 loss)
I0405 14:17:31.067283 18799 sgd_solver.cpp:105] Iteration 10056, lr = 0.0001
I0405 14:17:36.485172 18799 solver.cpp:218] Iteration 10068 (2.2149 iter/s, 5.41785s/12 iters), loss = 5.04416
I0405 14:17:36.485226 18799 solver.cpp:237]     Train net output #0: loss = 5.04416 (* 1 = 5.04416 loss)
I0405 14:17:36.485235 18799 sgd_solver.cpp:105] Iteration 10068, lr = 0.0001
I0405 14:17:41.704931 18799 solver.cpp:218] Iteration 10080 (2.299 iter/s, 5.21966s/12 iters), loss = 5.07439
I0405 14:17:41.704982 18799 solver.cpp:237]     Train net output #0: loss = 5.07439 (* 1 = 5.07439 loss)
I0405 14:17:41.704989 18799 sgd_solver.cpp:105] Iteration 10080, lr = 0.0001
I0405 14:17:47.052207 18799 solver.cpp:218] Iteration 10092 (2.24417 iter/s, 5.34718s/12 iters), loss = 5.02527
I0405 14:17:47.052251 18799 solver.cpp:237]     Train net output #0: loss = 5.02527 (* 1 = 5.02527 loss)
I0405 14:17:47.052258 18799 sgd_solver.cpp:105] Iteration 10092, lr = 0.0001
I0405 14:17:49.282822 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel
I0405 14:17:54.008065 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate
I0405 14:17:57.462163 18799 solver.cpp:330] Iteration 10098, Testing net (#0)
I0405 14:17:57.462183 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:17:57.898855 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:02.070371 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0405 14:18:02.070399 18799 solver.cpp:397]     Test net output #1: loss = 5.00543 (* 1 = 5.00543 loss)
I0405 14:18:03.955464 18799 solver.cpp:218] Iteration 10104 (0.709929 iter/s, 16.9031s/12 iters), loss = 4.9864
I0405 14:18:03.955505 18799 solver.cpp:237]     Train net output #0: loss = 4.9864 (* 1 = 4.9864 loss)
I0405 14:18:03.955511 18799 sgd_solver.cpp:105] Iteration 10104, lr = 0.0001
I0405 14:18:08.580191 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:09.289580 18799 solver.cpp:218] Iteration 10116 (2.24971 iter/s, 5.33402s/12 iters), loss = 5.03151
I0405 14:18:09.289628 18799 solver.cpp:237]     Train net output #0: loss = 5.03151 (* 1 = 5.03151 loss)
I0405 14:18:09.289633 18799 sgd_solver.cpp:105] Iteration 10116, lr = 0.0001
I0405 14:18:14.572150 18799 solver.cpp:218] Iteration 10128 (2.27166 iter/s, 5.28248s/12 iters), loss = 4.97393
I0405 14:18:14.572206 18799 solver.cpp:237]     Train net output #0: loss = 4.97393 (* 1 = 4.97393 loss)
I0405 14:18:14.572216 18799 sgd_solver.cpp:105] Iteration 10128, lr = 0.0001
I0405 14:18:19.964654 18799 solver.cpp:218] Iteration 10140 (2.22535 iter/s, 5.3924s/12 iters), loss = 4.87164
I0405 14:18:19.964704 18799 solver.cpp:237]     Train net output #0: loss = 4.87164 (* 1 = 4.87164 loss)
I0405 14:18:19.964712 18799 sgd_solver.cpp:105] Iteration 10140, lr = 0.0001
I0405 14:18:25.324400 18799 solver.cpp:218] Iteration 10152 (2.23895 iter/s, 5.35965s/12 iters), loss = 4.81948
I0405 14:18:25.324525 18799 solver.cpp:237]     Train net output #0: loss = 4.81948 (* 1 = 4.81948 loss)
I0405 14:18:25.324534 18799 sgd_solver.cpp:105] Iteration 10152, lr = 0.0001
I0405 14:18:30.630812 18799 solver.cpp:218] Iteration 10164 (2.26149 iter/s, 5.30624s/12 iters), loss = 4.99115
I0405 14:18:30.630862 18799 solver.cpp:237]     Train net output #0: loss = 4.99115 (* 1 = 4.99115 loss)
I0405 14:18:30.630869 18799 sgd_solver.cpp:105] Iteration 10164, lr = 0.0001
I0405 14:18:36.016386 18799 solver.cpp:218] Iteration 10176 (2.22822 iter/s, 5.38548s/12 iters), loss = 5.05366
I0405 14:18:36.016446 18799 solver.cpp:237]     Train net output #0: loss = 5.05366 (* 1 = 5.05366 loss)
I0405 14:18:36.016455 18799 sgd_solver.cpp:105] Iteration 10176, lr = 0.0001
I0405 14:18:41.326812 18799 solver.cpp:218] Iteration 10188 (2.25975 iter/s, 5.31032s/12 iters), loss = 5.02202
I0405 14:18:41.326870 18799 solver.cpp:237]     Train net output #0: loss = 5.02202 (* 1 = 5.02202 loss)
I0405 14:18:41.326879 18799 sgd_solver.cpp:105] Iteration 10188, lr = 0.0001
I0405 14:18:46.173463 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel
I0405 14:18:50.784992 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate
I0405 14:18:53.163749 18799 solver.cpp:330] Iteration 10200, Testing net (#0)
I0405 14:18:53.163769 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:18:53.531941 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:57.588918 18799 solver.cpp:397]     Test net output #0: accuracy = 0.026348
I0405 14:18:57.589054 18799 solver.cpp:397]     Test net output #1: loss = 5.00205 (* 1 = 5.00205 loss)
I0405 14:18:57.731103 18799 solver.cpp:218] Iteration 10200 (0.731523 iter/s, 16.4041s/12 iters), loss = 5.15515
I0405 14:18:57.731168 18799 solver.cpp:237]     Train net output #0: loss = 5.15515 (* 1 = 5.15515 loss)
I0405 14:18:57.731175 18799 sgd_solver.cpp:105] Iteration 10200, lr = 0.0001
I0405 14:19:02.038728 18799 solver.cpp:218] Iteration 10212 (2.78583 iter/s, 4.30752s/12 iters), loss = 4.92494
I0405 14:19:02.038769 18799 solver.cpp:237]     Train net output #0: loss = 4.92494 (* 1 = 4.92494 loss)
I0405 14:19:02.038775 18799 sgd_solver.cpp:105] Iteration 10212, lr = 0.0001
I0405 14:19:03.564817 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:19:07.277755 18799 solver.cpp:218] Iteration 10224 (2.29054 iter/s, 5.23894s/12 iters), loss = 5.00498
I0405 14:19:07.277794 18799 solver.cpp:237]     Train net output #0: loss = 5.00498 (* 1 = 5.00498 loss)
I0405 14:19:07.277801 18799 sgd_solver.cpp:105] Iteration 10224, lr = 0.0001
I0405 14:19:12.738461 18799 solver.cpp:218] Iteration 10236 (2.19755 iter/s, 5.46062s/12 iters), loss = 4.99226
I0405 14:19:12.738503 18799 solver.cpp:237]     Train net output #0: loss = 4.99226 (* 1 = 4.99226 loss)
I0405 14:19:12.738509 18799 sgd_solver.cpp:105] Iteration 10236, lr = 0.0001
I0405 14:19:18.193935 18799 solver.cpp:218] Iteration 10248 (2.19966 iter/s, 5.45539s/12 iters), loss = 4.89483
I0405 14:19:18.193974 18799 solver.cpp:237]     Train net output #0: loss = 4.89483 (* 1 = 4.89483 loss)
I0405 14:19:18.193979 18799 sgd_solver.cpp:105] Iteration 10248, lr = 0.0001
I0405 14:19:23.458891 18799 solver.cpp:218] Iteration 10260 (2.27926 iter/s, 5.26487s/12 iters), loss = 4.89104
I0405 14:19:23.458933 18799 solver.cpp:237]     Train net output #0: loss = 4.89104 (* 1 = 4.89104 loss)
I0405 14:19:23.458940 18799 sgd_solver.cpp:105] Iteration 10260, lr = 0.0001
I0405 14:19:28.648996 18799 solver.cpp:218] Iteration 10272 (2.31213 iter/s, 5.19001s/12 iters), loss = 4.94656
I0405 14:19:28.649122 18799 solver.cpp:237]     Train net output #0: loss = 4.94656 (* 1 = 4.94656 loss)
I0405 14:19:28.649132 18799 sgd_solver.cpp:105] Iteration 10272, lr = 0.0001
I0405 14:19:34.038736 18799 solver.cpp:218] Iteration 10284 (2.22652 iter/s, 5.38957s/12 iters), loss = 5.02644
I0405 14:19:34.038791 18799 solver.cpp:237]     Train net output #0: loss = 5.02644 (* 1 = 5.02644 loss)
I0405 14:19:34.038800 18799 sgd_solver.cpp:105] Iteration 10284, lr = 0.0001
I0405 14:19:39.055440 18799 solver.cpp:218] Iteration 10296 (2.39206 iter/s, 5.0166s/12 iters), loss = 4.91471
I0405 14:19:39.055497 18799 solver.cpp:237]     Train net output #0: loss = 4.91471 (* 1 = 4.91471 loss)
I0405 14:19:39.055506 18799 sgd_solver.cpp:105] Iteration 10296, lr = 0.0001
I0405 14:19:41.222163 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10302.caffemodel
I0405 14:19:45.772193 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10302.solverstate
I0405 14:19:48.185395 18799 solver.cpp:330] Iteration 10302, Testing net (#0)
I0405 14:19:48.185420 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:19:48.571301 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:19:52.698002 18799 solver.cpp:397]     Test net output #0: accuracy = 0.026348
I0405 14:19:52.698041 18799 solver.cpp:397]     Test net output #1: loss = 5.00235 (* 1 = 5.00235 loss)
I0405 14:19:54.597570 18799 solver.cpp:218] Iteration 10308 (0.772103 iter/s, 15.542s/12 iters), loss = 4.91916
I0405 14:19:54.597611 18799 solver.cpp:237]     Train net output #0: loss = 4.91916 (* 1 = 4.91916 loss)
I0405 14:19:54.597616 18799 sgd_solver.cpp:105] Iteration 10308, lr = 0.0001
I0405 14:19:58.482270 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:19:59.987016 18799 solver.cpp:218] Iteration 10320 (2.22661 iter/s, 5.38935s/12 iters), loss = 5.04907
I0405 14:19:59.987176 18799 solver.cpp:237]     Train net output #0: loss = 5.04907 (* 1 = 5.04907 loss)
I0405 14:19:59.987186 18799 sgd_solver.cpp:105] Iteration 10320, lr = 0.0001
I0405 14:20:05.394147 18799 solver.cpp:218] Iteration 10332 (2.21937 iter/s, 5.40693s/12 iters), loss = 5.00003
I0405 14:20:05.394191 18799 solver.cpp:237]     Train net output #0: loss = 5.00003 (* 1 = 5.00003 loss)
I0405 14:20:05.394197 18799 sgd_solver.cpp:105] Iteration 10332, lr = 0.0001
I0405 14:20:10.617432 18799 solver.cpp:218] Iteration 10344 (2.29744 iter/s, 5.2232s/12 iters), loss = 4.96597
I0405 14:20:10.617480 18799 solver.cpp:237]     Train net output #0: loss = 4.96597 (* 1 = 4.96597 loss)
I0405 14:20:10.617487 18799 sgd_solver.cpp:105] Iteration 10344, lr = 0.0001
I0405 14:20:16.113615 18799 solver.cpp:218] Iteration 10356 (2.18337 iter/s, 5.49609s/12 iters), loss = 4.96419
I0405 14:20:16.113662 18799 solver.cpp:237]     Train net output #0: loss = 4.96419 (* 1 = 4.96419 loss)
I0405 14:20:16.113668 18799 sgd_solver.cpp:105] Iteration 10356, lr = 0.0001
I0405 14:20:21.590883 18799 solver.cpp:218] Iteration 10368 (2.19091 iter/s, 5.47717s/12 iters), loss = 4.98149
I0405 14:20:21.590927 18799 solver.cpp:237]     Train net output #0: loss = 4.98149 (* 1 = 4.98149 loss)
I0405 14:20:21.590934 18799 sgd_solver.cpp:105] Iteration 10368, lr = 0.0001
I0405 14:20:26.848500 18799 solver.cpp:218] Iteration 10380 (2.28244 iter/s, 5.25753s/12 iters), loss = 4.79294
I0405 14:20:26.848541 18799 solver.cpp:237]     Train net output #0: loss = 4.79294 (* 1 = 4.79294 loss)
I0405 14:20:26.848546 18799 sgd_solver.cpp:105] Iteration 10380, lr = 0.0001
I0405 14:20:32.212850 18799 solver.cpp:218] Iteration 10392 (2.23703 iter/s, 5.36426s/12 iters), loss = 4.89761
I0405 14:20:32.212975 18799 solver.cpp:237]     Train net output #0: loss = 4.89761 (* 1 = 4.89761 loss)
I0405 14:20:32.212985 18799 sgd_solver.cpp:105] Iteration 10392, lr = 0.0001
I0405 14:20:36.917979 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10404.caffemodel
I0405 14:20:41.215757 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10404.solverstate
I0405 14:20:43.527325 18799 solver.cpp:330] Iteration 10404, Testing net (#0)
I0405 14:20:43.527344 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:20:43.894028 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:20:44.380165 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:20:48.158071 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0275735
I0405 14:20:48.158105 18799 solver.cpp:397]     Test net output #1: loss = 4.99612 (* 1 = 4.99612 loss)
I0405 14:20:48.299907 18799 solver.cpp:218] Iteration 10404 (0.745952 iter/s, 16.0868s/12 iters), loss = 4.90833
I0405 14:20:48.299957 18799 solver.cpp:237]     Train net output #0: loss = 4.90833 (* 1 = 4.90833 loss)
I0405 14:20:48.299964 18799 sgd_solver.cpp:105] Iteration 10404, lr = 0.0001
I0405 14:20:52.644282 18799 solver.cpp:218] Iteration 10416 (2.76225 iter/s, 4.34428s/12 iters), loss = 4.93749
I0405 14:20:52.644325 18799 solver.cpp:237]     Train net output #0: loss = 4.93749 (* 1 = 4.93749 loss)
I0405 14:20:52.644330 18799 sgd_solver.cpp:105] Iteration 10416, lr = 0.0001
I0405 14:20:53.508529 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:20:57.800734 18799 solver.cpp:218] Iteration 10428 (2.32722 iter/s, 5.15636s/12 iters), loss = 4.98445
I0405 14:20:57.800782 18799 solver.cpp:237]     Train net output #0: loss = 4.98445 (* 1 = 4.98445 loss)
I0405 14:20:57.800789 18799 sgd_solver.cpp:105] Iteration 10428, lr = 0.0001
I0405 14:21:02.956439 18799 solver.cpp:218] Iteration 10440 (2.32756 iter/s, 5.15561s/12 iters), loss = 4.9624
I0405 14:21:02.956557 18799 solver.cpp:237]     Train net output #0: loss = 4.9624 (* 1 = 4.9624 loss)
I0405 14:21:02.956564 18799 sgd_solver.cpp:105] Iteration 10440, lr = 0.0001
I0405 14:21:08.305485 18799 solver.cpp:218] Iteration 10452 (2.24346 iter/s, 5.34888s/12 iters), loss = 5.02162
I0405 14:21:08.305526 18799 solver.cpp:237]     Train net output #0: loss = 5.02162 (* 1 = 5.02162 loss)
I0405 14:21:08.305532 18799 sgd_solver.cpp:105] Iteration 10452, lr = 0.0001
I0405 14:21:13.555577 18799 solver.cpp:218] Iteration 10464 (2.28571 iter/s, 5.25s/12 iters), loss = 4.99338
I0405 14:21:13.555632 18799 solver.cpp:237]     Train net output #0: loss = 4.99338 (* 1 = 4.99338 loss)
I0405 14:21:13.555642 18799 sgd_solver.cpp:105] Iteration 10464, lr = 0.0001
I0405 14:21:18.833530 18799 solver.cpp:218] Iteration 10476 (2.27365 iter/s, 5.27786s/12 iters), loss = 5.01537
I0405 14:21:18.833567 18799 solver.cpp:237]     Train net output #0: loss = 5.01537 (* 1 = 5.01537 loss)
I0405 14:21:18.833573 18799 sgd_solver.cpp:105] Iteration 10476, lr = 0.0001
I0405 14:21:24.151417 18799 solver.cpp:218] Iteration 10488 (2.25657 iter/s, 5.3178s/12 iters), loss = 4.86689
I0405 14:21:24.151458 18799 solver.cpp:237]     Train net output #0: loss = 4.86689 (* 1 = 4.86689 loss)
I0405 14:21:24.151463 18799 sgd_solver.cpp:105] Iteration 10488, lr = 0.0001
I0405 14:21:29.522902 18799 solver.cpp:218] Iteration 10500 (2.23406 iter/s, 5.3714s/12 iters), loss = 4.99015
I0405 14:21:29.522961 18799 solver.cpp:237]     Train net output #0: loss = 4.99015 (* 1 = 4.99015 loss)
I0405 14:21:29.522970 18799 sgd_solver.cpp:105] Iteration 10500, lr = 0.0001
I0405 14:21:31.836757 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10506.caffemodel
I0405 14:21:36.427246 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10506.solverstate
I0405 14:21:38.807839 18799 solver.cpp:330] Iteration 10506, Testing net (#0)
I0405 14:21:38.807857 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:21:39.048768 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:21:43.082314 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0281863
I0405 14:21:43.082348 18799 solver.cpp:397]     Test net output #1: loss = 4.99516 (* 1 = 4.99516 loss)
I0405 14:21:45.077741 18799 solver.cpp:218] Iteration 10512 (0.771472 iter/s, 15.5547s/12 iters), loss = 4.96988
I0405 14:21:45.077795 18799 solver.cpp:237]     Train net output #0: loss = 4.96988 (* 1 = 4.96988 loss)
I0405 14:21:45.077803 18799 sgd_solver.cpp:105] Iteration 10512, lr = 0.0001
I0405 14:21:48.275743 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:21:50.417516 18799 solver.cpp:218] Iteration 10524 (2.24733 iter/s, 5.33968s/12 iters), loss = 4.91
I0405 14:21:50.417560 18799 solver.cpp:237]     Train net output #0: loss = 4.91 (* 1 = 4.91 loss)
I0405 14:21:50.417567 18799 sgd_solver.cpp:105] Iteration 10524, lr = 0.0001
I0405 14:21:55.719646 18799 solver.cpp:218] Iteration 10536 (2.26328 iter/s, 5.30204s/12 iters), loss = 4.96255
I0405 14:21:55.719691 18799 solver.cpp:237]     Train net output #0: loss = 4.96255 (* 1 = 4.96255 loss)
I0405 14:21:55.719697 18799 sgd_solver.cpp:105] Iteration 10536, lr = 0.0001
I0405 14:22:01.232601 18799 solver.cpp:218] Iteration 10548 (2.17673 iter/s, 5.51286s/12 iters), loss = 4.98797
I0405 14:22:01.232656 18799 solver.cpp:237]     Train net output #0: loss = 4.98797 (* 1 = 4.98797 loss)
I0405 14:22:01.232666 18799 sgd_solver.cpp:105] Iteration 10548, lr = 0.0001
I0405 14:22:06.624524 18799 solver.cpp:218] Iteration 10560 (2.22559 iter/s, 5.39182s/12 iters), loss = 4.98321
I0405 14:22:06.624663 18799 solver.cpp:237]     Train net output #0: loss = 4.98321 (* 1 = 4.98321 loss)
I0405 14:22:06.624670 18799 sgd_solver.cpp:105] Iteration 10560, lr = 0.0001
I0405 14:22:11.948172 18799 solver.cpp:218] Iteration 10572 (2.25417 iter/s, 5.32347s/12 iters), loss = 4.9945
I0405 14:22:11.948210 18799 solver.cpp:237]     Train net output #0: loss = 4.9945 (* 1 = 4.9945 loss)
I0405 14:22:11.948216 18799 sgd_solver.cpp:105] Iteration 10572, lr = 0.0001
I0405 14:22:17.166821 18799 solver.cpp:218] Iteration 10584 (2.29949 iter/s, 5.21856s/12 iters), loss = 5.08989
I0405 14:22:17.166874 18799 solver.cpp:237]     Train net output #0: loss = 5.08989 (* 1 = 5.08989 loss)
I0405 14:22:17.166882 18799 sgd_solver.cpp:105] Iteration 10584, lr = 0.0001
I0405 14:22:22.654619 18799 solver.cpp:218] Iteration 10596 (2.18671 iter/s, 5.4877s/12 iters), loss = 4.96263
I0405 14:22:22.654664 18799 solver.cpp:237]     Train net output #0: loss = 4.96263 (* 1 = 4.96263 loss)
I0405 14:22:22.654670 18799 sgd_solver.cpp:105] Iteration 10596, lr = 0.0001
I0405 14:22:27.544657 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10608.caffemodel
I0405 14:22:30.931280 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10608.solverstate
I0405 14:22:33.253156 18799 solver.cpp:330] Iteration 10608, Testing net (#0)
I0405 14:22:33.253185 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:22:33.489542 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:22:37.598142 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0275735
I0405 14:22:37.598217 18799 solver.cpp:397]     Test net output #1: loss = 4.99306 (* 1 = 4.99306 loss)
I0405 14:22:37.736780 18799 solver.cpp:218] Iteration 10608 (0.79565 iter/s, 15.082s/12 iters), loss = 4.96018
I0405 14:22:37.736827 18799 solver.cpp:237]     Train net output #0: loss = 4.96018 (* 1 = 4.96018 loss)
I0405 14:22:37.736832 18799 sgd_solver.cpp:105] Iteration 10608, lr = 0.0001
I0405 14:22:42.059267 18799 solver.cpp:218] Iteration 10620 (2.77624 iter/s, 4.3224s/12 iters), loss = 5.05335
I0405 14:22:42.059310 18799 solver.cpp:237]     Train net output #0: loss = 5.05335 (* 1 = 5.05335 loss)
I0405 14:22:42.059315 18799 sgd_solver.cpp:105] Iteration 10620, lr = 0.0001
I0405 14:22:42.176563 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:22:47.464069 18799 solver.cpp:218] Iteration 10632 (2.22028 iter/s, 5.40471s/12 iters), loss = 5.07235
I0405 14:22:47.464121 18799 solver.cpp:237]     Train net output #0: loss = 5.07235 (* 1 = 5.07235 loss)
I0405 14:22:47.464129 18799 sgd_solver.cpp:105] Iteration 10632, lr = 0.0001
I0405 14:22:52.644469 18799 solver.cpp:218] Iteration 10644 (2.31647 iter/s, 5.1803s/12 iters), loss = 4.99742
I0405 14:22:52.644526 18799 solver.cpp:237]     Train net output #0: loss = 4.99742 (* 1 = 4.99742 loss)
I0405 14:22:52.644536 18799 sgd_solver.cpp:105] Iteration 10644, lr = 0.0001
I0405 14:22:57.974448 18799 solver.cpp:218] Iteration 10656 (2.25146 iter/s, 5.32988s/12 iters), loss = 4.96088
I0405 14:22:57.974493 18799 solver.cpp:237]     Train net output #0: loss = 4.96088 (* 1 = 4.96088 loss)
I0405 14:22:57.974498 18799 sgd_solver.cpp:105] Iteration 10656, lr = 0.0001
I0405 14:23:03.340561 18799 solver.cpp:218] Iteration 10668 (2.2363 iter/s, 5.36602s/12 iters), loss = 4.99085
I0405 14:23:03.340607 18799 solver.cpp:237]     Train net output #0: loss = 4.99085 (* 1 = 4.99085 loss)
I0405 14:23:03.340613 18799 sgd_solver.cpp:105] Iteration 10668, lr = 0.0001
I0405 14:23:08.700076 18799 solver.cpp:218] Iteration 10680 (2.23905 iter/s, 5.35942s/12 iters), loss = 4.88286
I0405 14:23:08.700191 18799 solver.cpp:237]     Train net output #0: loss = 4.88286 (* 1 = 4.88286 loss)
I0405 14:23:08.700201 18799 sgd_solver.cpp:105] Iteration 10680, lr = 0.0001
I0405 14:23:14.240520 18799 solver.cpp:218] Iteration 10692 (2.16595 iter/s, 5.54028s/12 iters), loss = 5.00719
I0405 14:23:14.240561 18799 solver.cpp:237]     Train net output #0: loss = 5.00719 (* 1 = 5.00719 loss)
I0405 14:23:14.240566 18799 sgd_solver.cpp:105] Iteration 10692, lr = 0.0001
I0405 14:23:19.587847 18799 solver.cpp:218] Iteration 10704 (2.24415 iter/s, 5.34724s/12 iters), loss = 4.93821
I0405 14:23:19.587904 18799 solver.cpp:237]     Train net output #0: loss = 4.93821 (* 1 = 4.93821 loss)
I0405 14:23:19.587914 18799 sgd_solver.cpp:105] Iteration 10704, lr = 0.0001
I0405 14:23:21.720326 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10710.caffemodel
I0405 14:23:24.753270 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10710.solverstate
I0405 14:23:27.071236 18799 solver.cpp:330] Iteration 10710, Testing net (#0)
I0405 14:23:27.071255 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:23:27.250425 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:23:31.456382 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0257353
I0405 14:23:31.456418 18799 solver.cpp:397]     Test net output #1: loss = 4.98652 (* 1 = 4.98652 loss)
I0405 14:23:33.270910 18799 solver.cpp:218] Iteration 10716 (0.877006 iter/s, 13.6829s/12 iters), loss = 4.83826
I0405 14:23:33.270951 18799 solver.cpp:237]     Train net output #0: loss = 4.83826 (* 1 = 4.83826 loss)
I0405 14:23:33.270956 18799 sgd_solver.cpp:105] Iteration 10716, lr = 0.0001
I0405 14:23:35.611629 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:23:38.573134 18799 solver.cpp:218] Iteration 10728 (2.26324 iter/s, 5.30214s/12 iters), loss = 4.94941
I0405 14:23:38.573174 18799 solver.cpp:237]     Train net output #0: loss = 4.94941 (* 1 = 4.94941 loss)
I0405 14:23:38.573180 18799 sgd_solver.cpp:105] Iteration 10728, lr = 0.0001
I0405 14:23:43.883641 18799 solver.cpp:218] Iteration 10740 (2.25971 iter/s, 5.31041s/12 iters), loss = 4.98746
I0405 14:23:43.883800 18799 solver.cpp:237]     Train net output #0: loss = 4.98746 (* 1 = 4.98746 loss)
I0405 14:23:43.883810 18799 sgd_solver.cpp:105] Iteration 10740, lr = 0.0001
I0405 14:23:49.227145 18799 solver.cpp:218] Iteration 10752 (2.2458 iter/s, 5.3433s/12 iters), loss = 4.99493
I0405 14:23:49.227190 18799 solver.cpp:237]     Train net output #0: loss = 4.99493 (* 1 = 4.99493 loss)
I0405 14:23:49.227195 18799 sgd_solver.cpp:105] Iteration 10752, lr = 0.0001
I0405 14:23:54.785015 18799 solver.cpp:218] Iteration 10764 (2.15913 iter/s, 5.55778s/12 iters), loss = 5.00577
I0405 14:23:54.785054 18799 solver.cpp:237]     Train net output #0: loss = 5.00577 (* 1 = 5.00577 loss)
I0405 14:23:54.785059 18799 sgd_solver.cpp:105] Iteration 10764, lr = 0.0001
I0405 14:24:00.045568 18799 solver.cpp:218] Iteration 10776 (2.28117 iter/s, 5.26046s/12 iters), loss = 4.95515
I0405 14:24:00.045629 18799 solver.cpp:237]     Train net output #0: loss = 4.95515 (* 1 = 4.95515 loss)
I0405 14:24:00.045636 18799 sgd_solver.cpp:105] Iteration 10776, lr = 0.0001
I0405 14:24:05.427580 18799 solver.cpp:218] Iteration 10788 (2.22969 iter/s, 5.3819s/12 iters), loss = 4.95589
I0405 14:24:05.427632 18799 solver.cpp:237]     Train net output #0: loss = 4.95589 (* 1 = 4.95589 loss)
I0405 14:24:05.427640 18799 sgd_solver.cpp:105] Iteration 10788, lr = 0.0001
I0405 14:24:10.742027 18799 solver.cpp:218] Iteration 10800 (2.25804 iter/s, 5.31434s/12 iters), loss = 4.85906
I0405 14:24:10.742086 18799 solver.cpp:237]     Train net output #0: loss = 4.85906 (* 1 = 4.85906 loss)
I0405 14:24:10.742095 18799 sgd_solver.cpp:105] Iteration 10800, lr = 0.0001
I0405 14:24:15.577600 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10812.caffemodel
I0405 14:24:18.622198 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10812.solverstate
I0405 14:24:20.926371 18799 solver.cpp:330] Iteration 10812, Testing net (#0)
I0405 14:24:20.926390 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:24:21.066603 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:24:25.326905 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0269608
I0405 14:24:25.326932 18799 solver.cpp:397]     Test net output #1: loss = 4.98527 (* 1 = 4.98527 loss)
I0405 14:24:25.464851 18799 solver.cpp:218] Iteration 10812 (0.81507 iter/s, 14.7227s/12 iters), loss = 4.92948
I0405 14:24:25.464898 18799 solver.cpp:237]     Train net output #0: loss = 4.92948 (* 1 = 4.92948 loss)
I0405 14:24:25.464905 18799 sgd_solver.cpp:105] Iteration 10812, lr = 0.0001
I0405 14:24:29.272665 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:24:29.956312 18799 solver.cpp:218] Iteration 10824 (2.67183 iter/s, 4.4913s/12 iters), loss = 5.01727
I0405 14:24:29.956358 18799 solver.cpp:237]     Train net output #0: loss = 5.01727 (* 1 = 5.01727 loss)
I0405 14:24:29.956367 18799 sgd_solver.cpp:105] Iteration 10824, lr = 0.0001
I0405 14:24:35.038448 18799 solver.cpp:218] Iteration 10836 (2.36125 iter/s, 5.08205s/12 iters), loss = 5.0071
I0405 14:24:35.038483 18799 solver.cpp:237]     Train net output #0: loss = 5.0071 (* 1 = 5.0071 loss)
I0405 14:24:35.038489 18799 sgd_solver.cpp:105] Iteration 10836, lr = 0.0001
I0405 14:24:40.388641 18799 solver.cpp:218] Iteration 10848 (2.24295 iter/s, 5.35011s/12 iters), loss = 4.87099
I0405 14:24:40.388695 18799 solver.cpp:237]     Train net output #0: loss = 4.87099 (* 1 = 4.87099 loss)
I0405 14:24:40.388702 18799 sgd_solver.cpp:105] Iteration 10848, lr = 0.0001
I0405 14:24:45.708469 18799 solver.cpp:218] Iteration 10860 (2.25576 iter/s, 5.31973s/12 iters), loss = 4.85075
I0405 14:24:45.708609 18799 solver.cpp:237]     Train net output #0: loss = 4.85075 (* 1 = 4.85075 loss)
I0405 14:24:45.708616 18799 sgd_solver.cpp:105] Iteration 10860, lr = 0.0001
I0405 14:24:50.729530 18799 solver.cpp:218] Iteration 10872 (2.39002 iter/s, 5.02088s/12 iters), loss = 4.90969
I0405 14:24:50.729569 18799 solver.cpp:237]     Train net output #0: loss = 4.90969 (* 1 = 4.90969 loss)
I0405 14:24:50.729574 18799 sgd_solver.cpp:105] Iteration 10872, lr = 0.0001
I0405 14:24:56.110749 18799 solver.cpp:218] Iteration 10884 (2.23002 iter/s, 5.38113s/12 iters), loss = 5.02297
I0405 14:24:56.110788 18799 solver.cpp:237]     Train net output #0: loss = 5.02297 (* 1 = 5.02297 loss)
I0405 14:24:56.110793 18799 sgd_solver.cpp:105] Iteration 10884, lr = 0.0001
I0405 14:25:01.293253 18799 solver.cpp:218] Iteration 10896 (2.31552 iter/s, 5.18242s/12 iters), loss = 4.98128
I0405 14:25:01.293301 18799 solver.cpp:237]     Train net output #0: loss = 4.98128 (* 1 = 4.98128 loss)
I0405 14:25:01.293308 18799 sgd_solver.cpp:105] Iteration 10896, lr = 0.0001
I0405 14:25:06.544509 18799 solver.cpp:218] Iteration 10908 (2.28521 iter/s, 5.25117s/12 iters), loss = 5.08583
I0405 14:25:06.544553 18799 solver.cpp:237]     Train net output #0: loss = 5.08583 (* 1 = 5.08583 loss)
I0405 14:25:06.544559 18799 sgd_solver.cpp:105] Iteration 10908, lr = 0.0001
I0405 14:25:08.700713 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10914.caffemodel
I0405 14:25:11.765646 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10914.solverstate
I0405 14:25:14.105124 18799 solver.cpp:330] Iteration 10914, Testing net (#0)
I0405 14:25:14.105144 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:25:14.193001 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:25:18.521946 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0269608
I0405 14:25:18.522054 18799 solver.cpp:397]     Test net output #1: loss = 4.98344 (* 1 = 4.98344 loss)
I0405 14:25:20.502269 18799 solver.cpp:218] Iteration 10920 (0.859746 iter/s, 13.9576s/12 iters), loss = 4.92965
I0405 14:25:20.502323 18799 solver.cpp:237]     Train net output #0: loss = 4.92965 (* 1 = 4.92965 loss)
I0405 14:25:20.502331 18799 sgd_solver.cpp:105] Iteration 10920, lr = 0.0001
I0405 14:25:22.081022 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:25:25.802034 18799 solver.cpp:218] Iteration 10932 (2.26429 iter/s, 5.29967s/12 iters), loss = 4.94506
I0405 14:25:25.802078 18799 solver.cpp:237]     Train net output #0: loss = 4.94506 (* 1 = 4.94506 loss)
I0405 14:25:25.802083 18799 sgd_solver.cpp:105] Iteration 10932, lr = 0.0001
I0405 14:25:31.113881 18799 solver.cpp:218] Iteration 10944 (2.25914 iter/s, 5.31175s/12 iters), loss = 4.97868
I0405 14:25:31.113943 18799 solver.cpp:237]     Train net output #0: loss = 4.97868 (* 1 = 4.97868 loss)
I0405 14:25:31.113953 18799 sgd_solver.cpp:105] Iteration 10944, lr = 0.0001
I0405 14:25:36.441946 18799 solver.cpp:218] Iteration 10956 (2.25227 iter/s, 5.32796s/12 iters), loss = 4.9178
I0405 14:25:36.441987 18799 solver.cpp:237]     Train net output #0: loss = 4.9178 (* 1 = 4.9178 loss)
I0405 14:25:36.441992 18799 sgd_solver.cpp:105] Iteration 10956, lr = 0.0001
I0405 14:25:41.825470 18799 solver.cpp:218] Iteration 10968 (2.22906 iter/s, 5.38344s/12 iters), loss = 4.82081
I0405 14:25:41.825512 18799 solver.cpp:237]     Train net output #0: loss = 4.82081 (* 1 = 4.82081 loss)
I0405 14:25:41.825518 18799 sgd_solver.cpp:105] Iteration 10968, lr = 0.0001
I0405 14:25:47.030009 18799 solver.cpp:218] Iteration 10980 (2.30572 iter/s, 5.20445s/12 iters), loss = 4.92867
I0405 14:25:47.030047 18799 solver.cpp:237]     Train net output #0: loss = 4.92867 (* 1 = 4.92867 loss)
I0405 14:25:47.030053 18799 sgd_solver.cpp:105] Iteration 10980, lr = 0.0001
I0405 14:25:52.412294 18799 solver.cpp:218] Iteration 10992 (2.22957 iter/s, 5.38219s/12 iters), loss = 5.0008
I0405 14:25:52.412441 18799 solver.cpp:237]     Train net output #0: loss = 5.0008 (* 1 = 5.0008 loss)
I0405 14:25:52.412448 18799 sgd_solver.cpp:105] Iteration 10992, lr = 0.0001
I0405 14:25:57.835405 18799 solver.cpp:218] Iteration 11004 (2.21283 iter/s, 5.42292s/12 iters), loss = 4.98687
I0405 14:25:57.835445 18799 solver.cpp:237]     Train net output #0: loss = 4.98687 (* 1 = 4.98687 loss)
I0405 14:25:57.835451 18799 sgd_solver.cpp:105] Iteration 11004, lr = 0.0001
I0405 14:26:02.445474 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11016.caffemodel
I0405 14:26:05.469461 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11016.solverstate
I0405 14:26:07.799264 18799 solver.cpp:330] Iteration 11016, Testing net (#0)
I0405 14:26:07.799288 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:26:07.858021 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:12.259891 18799 solver.cpp:397]     Test net output #0: accuracy = 0.026348
I0405 14:26:12.259919 18799 solver.cpp:397]     Test net output #1: loss = 4.98316 (* 1 = 4.98316 loss)
I0405 14:26:12.402981 18799 solver.cpp:218] Iteration 11016 (0.823755 iter/s, 14.5674s/12 iters), loss = 4.89445
I0405 14:26:12.404580 18799 solver.cpp:237]     Train net output #0: loss = 4.89445 (* 1 = 4.89445 loss)
I0405 14:26:12.404589 18799 sgd_solver.cpp:105] Iteration 11016, lr = 0.0001
I0405 14:26:12.756743 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:15.309785 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:16.658748 18799 solver.cpp:218] Iteration 11028 (2.82079 iter/s, 4.25413s/12 iters), loss = 5.06163
I0405 14:26:16.658792 18799 solver.cpp:237]     Train net output #0: loss = 5.06163 (* 1 = 5.06163 loss)
I0405 14:26:16.658797 18799 sgd_solver.cpp:105] Iteration 11028, lr = 0.0001
I0405 14:26:21.986790 18799 solver.cpp:218] Iteration 11040 (2.25227 iter/s, 5.32795s/12 iters), loss = 4.88927
I0405 14:26:21.986829 18799 solver.cpp:237]     Train net output #0: loss = 4.88927 (* 1 = 4.88927 loss)
I0405 14:26:21.986835 18799 sgd_solver.cpp:105] Iteration 11040, lr = 0.0001
I0405 14:26:27.213883 18799 solver.cpp:218] Iteration 11052 (2.29577 iter/s, 5.227s/12 iters), loss = 4.95674
I0405 14:26:27.213989 18799 solver.cpp:237]     Train net output #0: loss = 4.95674 (* 1 = 4.95674 loss)
I0405 14:26:27.213995 18799 sgd_solver.cpp:105] Iteration 11052, lr = 0.0001
I0405 14:26:32.506600 18799 solver.cpp:218] Iteration 11064 (2.26733 iter/s, 5.29256s/12 iters), loss = 4.89396
I0405 14:26:32.506659 18799 solver.cpp:237]     Train net output #0: loss = 4.89396 (* 1 = 4.89396 loss)
I0405 14:26:32.506669 18799 sgd_solver.cpp:105] Iteration 11064, lr = 0.0001
I0405 14:26:37.772017 18799 solver.cpp:218] Iteration 11076 (2.27907 iter/s, 5.26531s/12 iters), loss = 4.96347
I0405 14:26:37.772060 18799 solver.cpp:237]     Train net output #0: loss = 4.96347 (* 1 = 4.96347 loss)
I0405 14:26:37.772065 18799 sgd_solver.cpp:105] Iteration 11076, lr = 0.0001
I0405 14:26:43.119985 18799 solver.cpp:218] Iteration 11088 (2.24388 iter/s, 5.34788s/12 iters), loss = 4.82966
I0405 14:26:43.120030 18799 solver.cpp:237]     Train net output #0: loss = 4.82966 (* 1 = 4.82966 loss)
I0405 14:26:43.120038 18799 sgd_solver.cpp:105] Iteration 11088, lr = 0.0001
I0405 14:26:46.574661 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:26:48.253068 18799 solver.cpp:218] Iteration 11100 (2.33782 iter/s, 5.13298s/12 iters), loss = 4.87428
I0405 14:26:48.253121 18799 solver.cpp:237]     Train net output #0: loss = 4.87428 (* 1 = 4.87428 loss)
I0405 14:26:48.253129 18799 sgd_solver.cpp:105] Iteration 11100, lr = 0.0001
I0405 14:26:53.237274 18799 solver.cpp:218] Iteration 11112 (2.40765 iter/s, 4.98411s/12 iters), loss = 4.88636
I0405 14:26:53.237330 18799 solver.cpp:237]     Train net output #0: loss = 4.88636 (* 1 = 4.88636 loss)
I0405 14:26:53.237339 18799 sgd_solver.cpp:105] Iteration 11112, lr = 0.0001
I0405 14:26:55.346362 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11118.caffemodel
I0405 14:26:58.465493 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11118.solverstate
I0405 14:27:00.790642 18799 solver.cpp:330] Iteration 11118, Testing net (#0)
I0405 14:27:00.790665 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:27:05.121104 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0281863
I0405 14:27:05.121140 18799 solver.cpp:397]     Test net output #1: loss = 4.97396 (* 1 = 4.97396 loss)
I0405 14:27:05.605576 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:27:06.966691 18799 solver.cpp:218] Iteration 11124 (0.874046 iter/s, 13.7293s/12 iters), loss = 4.93448
I0405 14:27:06.966739 18799 solver.cpp:237]     Train net output #0: loss = 4.93448 (* 1 = 4.93448 loss)
I0405 14:27:06.966745 18799 sgd_solver.cpp:105] Iteration 11124, lr = 0.0001
I0405 14:27:07.837399 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:27:12.181639 18799 solver.cpp:218] Iteration 11136 (2.30112 iter/s, 5.21485s/12 iters), loss = 4.96337
I0405 14:27:12.181684 18799 solver.cpp:237]     Train net output #0: loss = 4.96337 (* 1 = 4.96337 loss)
I0405 14:27:12.181689 18799 sgd_solver.cpp:105] Iteration 11136, lr = 0.0001
I0405 14:27:17.602087 18799 solver.cpp:218] Iteration 11148 (2.21388 iter/s, 5.42035s/12 iters), loss = 5.00433
I0405 14:27:17.602133 18799 solver.cpp:237]     Train net output #0: loss = 5.00433 (* 1 = 5.00433 loss)
I0405 14:27:17.602140 18799 sgd_solver.cpp:105] Iteration 11148, lr = 0.0001
I0405 14:27:22.922997 18799 solver.cpp:218] Iteration 11160 (2.25529 iter/s, 5.32081s/12 iters), loss = 4.96391
I0405 14:27:22.923046 18799 solver.cpp:237]     Train net output #0: loss = 4.96391 (* 1 = 4.96391 loss)
I0405 14:27:22.923054 18799 sgd_solver.cpp:105] Iteration 11160, lr = 0.0001
I0405 14:27:28.410732 18799 solver.cpp:218] Iteration 11172 (2.18673 iter/s, 5.48764s/12 iters), loss = 4.95544
I0405 14:27:28.410773 18799 solver.cpp:237]     Train net output #0: loss = 4.95544 (* 1 = 4.95544 loss)
I0405 14:27:28.410779 18799 sgd_solver.cpp:105] Iteration 11172, lr = 0.0001
I0405 14:27:33.588474 18799 solver.cpp:218] Iteration 11184 (2.31765 iter/s, 5.17766s/12 iters), loss = 4.99329
I0405 14:27:33.588564 18799 solver.cpp:237]     Train net output #0: loss = 4.99329 (* 1 = 4.99329 loss)
I0405 14:27:33.588572 18799 sgd_solver.cpp:105] Iteration 11184, lr = 0.0001
I0405 14:27:38.469380 18799 solver.cpp:218] Iteration 11196 (2.45863 iter/s, 4.88077s/12 iters), loss = 4.90048
I0405 14:27:38.469422 18799 solver.cpp:237]     Train net output #0: loss = 4.90048 (* 1 = 4.90048 loss)
I0405 14:27:38.469427 18799 sgd_solver.cpp:105] Iteration 11196, lr = 0.0001
I0405 14:27:43.863036 18799 solver.cpp:218] Iteration 11208 (2.22487 iter/s, 5.39357s/12 iters), loss = 4.86828
I0405 14:27:43.863122 18799 solver.cpp:237]     Train net output #0: loss = 4.86828 (* 1 = 4.86828 loss)
I0405 14:27:43.863129 18799 sgd_solver.cpp:105] Iteration 11208, lr = 0.0001
I0405 14:27:48.741410 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11220.caffemodel
I0405 14:27:51.789322 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11220.solverstate
I0405 14:27:54.101650 18799 solver.cpp:330] Iteration 11220, Testing net (#0)
I0405 14:27:54.101672 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:27:58.757927 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0281863
I0405 14:27:58.757961 18799 solver.cpp:397]     Test net output #1: loss = 4.97312 (* 1 = 4.97312 loss)
I0405 14:27:58.900907 18799 solver.cpp:218] Iteration 11220 (0.798261 iter/s, 15.0327s/12 iters), loss = 4.99921
I0405 14:27:58.900952 18799 solver.cpp:237]     Train net output #0: loss = 4.99921 (* 1 = 4.99921 loss)
I0405 14:27:58.900959 18799 sgd_solver.cpp:105] Iteration 11220, lr = 0.0001
I0405 14:27:59.006006 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:01.315923 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:03.626220 18799 solver.cpp:218] Iteration 11232 (2.53956 iter/s, 4.72522s/12 iters), loss = 4.94758
I0405 14:28:03.626374 18799 solver.cpp:237]     Train net output #0: loss = 4.94758 (* 1 = 4.94758 loss)
I0405 14:28:03.626382 18799 sgd_solver.cpp:105] Iteration 11232, lr = 0.0001
I0405 14:28:09.244293 18799 solver.cpp:218] Iteration 11244 (2.13604 iter/s, 5.61788s/12 iters), loss = 4.9948
I0405 14:28:09.244324 18799 solver.cpp:237]     Train net output #0: loss = 4.9948 (* 1 = 4.9948 loss)
I0405 14:28:09.244329 18799 sgd_solver.cpp:105] Iteration 11244, lr = 0.0001
I0405 14:28:14.543877 18799 solver.cpp:218] Iteration 11256 (2.26436 iter/s, 5.2995s/12 iters), loss = 4.97194
I0405 14:28:14.543920 18799 solver.cpp:237]     Train net output #0: loss = 4.97194 (* 1 = 4.97194 loss)
I0405 14:28:14.543926 18799 sgd_solver.cpp:105] Iteration 11256, lr = 0.0001
I0405 14:28:19.865780 18799 solver.cpp:218] Iteration 11268 (2.25487 iter/s, 5.32181s/12 iters), loss = 4.94355
I0405 14:28:19.865829 18799 solver.cpp:237]     Train net output #0: loss = 4.94355 (* 1 = 4.94355 loss)
I0405 14:28:19.865837 18799 sgd_solver.cpp:105] Iteration 11268, lr = 0.0001
I0405 14:28:24.956336 18799 solver.cpp:218] Iteration 11280 (2.35735 iter/s, 5.09046s/12 iters), loss = 4.99729
I0405 14:28:24.956378 18799 solver.cpp:237]     Train net output #0: loss = 4.99729 (* 1 = 4.99729 loss)
I0405 14:28:24.956388 18799 sgd_solver.cpp:105] Iteration 11280, lr = 0.0001
I0405 14:28:30.222357 18799 solver.cpp:218] Iteration 11292 (2.2788 iter/s, 5.26593s/12 iters), loss = 4.94738
I0405 14:28:30.222410 18799 solver.cpp:237]     Train net output #0: loss = 4.94738 (* 1 = 4.94738 loss)
I0405 14:28:30.222419 18799 sgd_solver.cpp:105] Iteration 11292, lr = 0.0001
I0405 14:28:35.571256 18799 solver.cpp:218] Iteration 11304 (2.24349 iter/s, 5.3488s/12 iters), loss = 4.98589
I0405 14:28:35.571377 18799 solver.cpp:237]     Train net output #0: loss = 4.98589 (* 1 = 4.98589 loss)
I0405 14:28:35.571386 18799 sgd_solver.cpp:105] Iteration 11304, lr = 0.0001
I0405 14:28:40.847522 18799 solver.cpp:218] Iteration 11316 (2.27441 iter/s, 5.27609s/12 iters), loss = 4.91853
I0405 14:28:40.847579 18799 solver.cpp:237]     Train net output #0: loss = 4.91853 (* 1 = 4.91853 loss)
I0405 14:28:40.847587 18799 sgd_solver.cpp:105] Iteration 11316, lr = 0.0001
I0405 14:28:43.084875 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11322.caffemodel
I0405 14:28:46.044921 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11322.solverstate
I0405 14:28:48.365237 18799 solver.cpp:330] Iteration 11322, Testing net (#0)
I0405 14:28:48.365259 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:28:52.748745 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0269608
I0405 14:28:52.748780 18799 solver.cpp:397]     Test net output #1: loss = 4.97298 (* 1 = 4.97298 loss)
I0405 14:28:53.119006 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:54.621506 18799 solver.cpp:218] Iteration 11328 (0.871217 iter/s, 13.7738s/12 iters), loss = 4.92743
I0405 14:28:54.621544 18799 solver.cpp:237]     Train net output #0: loss = 4.92743 (* 1 = 4.92743 loss)
I0405 14:28:54.621551 18799 sgd_solver.cpp:105] Iteration 11328, lr = 0.0001
I0405 14:28:54.742918 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:59.782397 18799 solver.cpp:218] Iteration 11340 (2.32522 iter/s, 5.1608s/12 iters), loss = 5.00732
I0405 14:28:59.782439 18799 solver.cpp:237]     Train net output #0: loss = 5.00732 (* 1 = 5.00732 loss)
I0405 14:28:59.782445 18799 sgd_solver.cpp:105] Iteration 11340, lr = 0.0001
I0405 14:29:05.144848 18799 solver.cpp:218] Iteration 11352 (2.23782 iter/s, 5.36236s/12 iters), loss = 5.00827
I0405 14:29:05.144892 18799 solver.cpp:237]     Train net output #0: loss = 5.00827 (* 1 = 5.00827 loss)
I0405 14:29:05.144898 18799 sgd_solver.cpp:105] Iteration 11352, lr = 0.0001
I0405 14:29:10.525457 18799 solver.cpp:218] Iteration 11364 (2.23027 iter/s, 5.38052s/12 iters), loss = 4.89177
I0405 14:29:10.525568 18799 solver.cpp:237]     Train net output #0: loss = 4.89177 (* 1 = 4.89177 loss)
I0405 14:29:10.525574 18799 sgd_solver.cpp:105] Iteration 11364, lr = 0.0001
I0405 14:29:15.907147 18799 solver.cpp:218] Iteration 11376 (2.22985 iter/s, 5.38153s/12 iters), loss = 5.0511
I0405 14:29:15.907207 18799 solver.cpp:237]     Train net output #0: loss = 5.0511 (* 1 = 5.0511 loss)
I0405 14:29:15.907217 18799 sgd_solver.cpp:105] Iteration 11376, lr = 0.0001
I0405 14:29:21.246994 18799 solver.cpp:218] Iteration 11388 (2.2473 iter/s, 5.33974s/12 iters), loss = 4.83978
I0405 14:29:21.247038 18799 solver.cpp:237]     Train net output #0: loss = 4.83978 (* 1 = 4.83978 loss)
I0405 14:29:21.247043 18799 sgd_solver.cpp:105] Iteration 11388, lr = 0.0001
I0405 14:29:26.615365 18799 solver.cpp:218] Iteration 11400 (2.23535 iter/s, 5.36828s/12 iters), loss = 4.86852
I0405 14:29:26.615411 18799 solver.cpp:237]     Train net output #0: loss = 4.86852 (* 1 = 4.86852 loss)
I0405 14:29:26.615417 18799 sgd_solver.cpp:105] Iteration 11400, lr = 0.0001
I0405 14:29:31.943359 18799 solver.cpp:218] Iteration 11412 (2.2523 iter/s, 5.3279s/12 iters), loss = 5.03971
I0405 14:29:31.943410 18799 solver.cpp:237]     Train net output #0: loss = 5.03971 (* 1 = 5.03971 loss)
I0405 14:29:31.943418 18799 sgd_solver.cpp:105] Iteration 11412, lr = 0.0001
I0405 14:29:36.886395 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11424.caffemodel
I0405 14:29:39.943027 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11424.solverstate
I0405 14:29:42.288103 18799 solver.cpp:330] Iteration 11424, Testing net (#0)
I0405 14:29:42.288163 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:29:46.808749 18799 solver.cpp:397]     Test net output #0: accuracy = 0.028799
I0405 14:29:46.808787 18799 solver.cpp:397]     Test net output #1: loss = 4.96762 (* 1 = 4.96762 loss)
I0405 14:29:46.946348 18799 solver.cpp:218] Iteration 11424 (0.799849 iter/s, 15.0028s/12 iters), loss = 4.94316
I0405 14:29:46.947952 18799 solver.cpp:237]     Train net output #0: loss = 4.94316 (* 1 = 4.94316 loss)
I0405 14:29:46.947964 18799 sgd_solver.cpp:105] Iteration 11424, lr = 0.0001
I0405 14:29:47.006642 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:29:48.428495 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:29:51.302925 18799 solver.cpp:218] Iteration 11436 (2.7555 iter/s, 4.35493s/12 iters), loss = 4.99624
I0405 14:29:51.302981 18799 solver.cpp:237]     Train net output #0: loss = 4.99624 (* 1 = 4.99624 loss)
I0405 14:29:51.302989 18799 sgd_solver.cpp:105] Iteration 11436, lr = 0.0001
I0405 14:29:56.569141 18799 solver.cpp:218] Iteration 11448 (2.27872 iter/s, 5.26611s/12 iters), loss = 4.86689
I0405 14:29:56.569187 18799 solver.cpp:237]     Train net output #0: loss = 4.86689 (* 1 = 4.86689 loss)
I0405 14:29:56.569195 18799 sgd_solver.cpp:105] Iteration 11448, lr = 0.0001
I0405 14:30:01.844375 18799 solver.cpp:218] Iteration 11460 (2.27482 iter/s, 5.27514s/12 iters), loss = 4.97171
I0405 14:30:01.844436 18799 solver.cpp:237]     Train net output #0: loss = 4.97171 (* 1 = 4.97171 loss)
I0405 14:30:01.844449 18799 sgd_solver.cpp:105] Iteration 11460, lr = 0.0001
I0405 14:30:07.209806 18799 solver.cpp:218] Iteration 11472 (2.23658 iter/s, 5.36533s/12 iters), loss = 4.9799
I0405 14:30:07.209849 18799 solver.cpp:237]     Train net output #0: loss = 4.9799 (* 1 = 4.9799 loss)
I0405 14:30:07.209856 18799 sgd_solver.cpp:105] Iteration 11472, lr = 0.0001
I0405 14:30:12.480926 18799 solver.cpp:218] Iteration 11484 (2.2766 iter/s, 5.27103s/12 iters), loss = 4.93275
I0405 14:30:12.481050 18799 solver.cpp:237]     Train net output #0: loss = 4.93275 (* 1 = 4.93275 loss)
I0405 14:30:12.481058 18799 sgd_solver.cpp:105] Iteration 11484, lr = 0.0001
I0405 14:30:17.671994 18799 solver.cpp:218] Iteration 11496 (2.31174 iter/s, 5.1909s/12 iters), loss = 4.91351
I0405 14:30:17.672034 18799 solver.cpp:237]     Train net output #0: loss = 4.91351 (* 1 = 4.91351 loss)
I0405 14:30:17.672039 18799 sgd_solver.cpp:105] Iteration 11496, lr = 0.0001
I0405 14:30:23.050215 18799 solver.cpp:218] Iteration 11508 (2.23126 iter/s, 5.37813s/12 iters), loss = 4.85357
I0405 14:30:23.050254 18799 solver.cpp:237]     Train net output #0: loss = 4.85357 (* 1 = 4.85357 loss)
I0405 14:30:23.050261 18799 sgd_solver.cpp:105] Iteration 11508, lr = 0.0001
I0405 14:30:28.436524 18799 solver.cpp:218] Iteration 11520 (2.22791 iter/s, 5.38622s/12 iters), loss = 4.84992
I0405 14:30:28.436566 18799 solver.cpp:237]     Train net output #0: loss = 4.84992 (* 1 = 4.84992 loss)
I0405 14:30:28.436573 18799 sgd_solver.cpp:105] Iteration 11520, lr = 0.0001
I0405 14:30:30.614817 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11526.caffemodel
I0405 14:30:33.594417 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11526.solverstate
I0405 14:30:35.891048 18799 solver.cpp:330] Iteration 11526, Testing net (#0)
I0405 14:30:35.891069 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:30:40.380935 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:30:40.380970 18799 solver.cpp:397]     Test net output #1: loss = 4.96392 (* 1 = 4.96392 loss)
I0405 14:30:40.483289 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:30:41.643224 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:30:42.269076 18799 solver.cpp:218] Iteration 11532 (0.867528 iter/s, 13.8324s/12 iters), loss = 4.95256
I0405 14:30:42.269124 18799 solver.cpp:237]     Train net output #0: loss = 4.95256 (* 1 = 4.95256 loss)
I0405 14:30:42.269131 18799 sgd_solver.cpp:105] Iteration 11532, lr = 0.0001
I0405 14:30:47.343217 18799 solver.cpp:218] Iteration 11544 (2.36498 iter/s, 5.07404s/12 iters), loss = 4.92984
I0405 14:30:47.343318 18799 solver.cpp:237]     Train net output #0: loss = 4.92984 (* 1 = 4.92984 loss)
I0405 14:30:47.343328 18799 sgd_solver.cpp:105] Iteration 11544, lr = 0.0001
I0405 14:30:52.530350 18799 solver.cpp:218] Iteration 11556 (2.31348 iter/s, 5.18698s/12 iters), loss = 4.82804
I0405 14:30:52.530409 18799 solver.cpp:237]     Train net output #0: loss = 4.82804 (* 1 = 4.82804 loss)
I0405 14:30:52.530417 18799 sgd_solver.cpp:105] Iteration 11556, lr = 0.0001
I0405 14:30:57.810931 18799 solver.cpp:218] Iteration 11568 (2.27252 iter/s, 5.28047s/12 iters), loss = 4.87097
I0405 14:30:57.810986 18799 solver.cpp:237]     Train net output #0: loss = 4.87097 (* 1 = 4.87097 loss)
I0405 14:30:57.810995 18799 sgd_solver.cpp:105] Iteration 11568, lr = 0.0001
I0405 14:31:03.163836 18799 solver.cpp:218] Iteration 11580 (2.24182 iter/s, 5.3528s/12 iters), loss = 4.93456
I0405 14:31:03.163893 18799 solver.cpp:237]     Train net output #0: loss = 4.93456 (* 1 = 4.93456 loss)
I0405 14:31:03.163902 18799 sgd_solver.cpp:105] Iteration 11580, lr = 0.0001
I0405 14:31:08.450189 18799 solver.cpp:218] Iteration 11592 (2.27004 iter/s, 5.28625s/12 iters), loss = 4.93379
I0405 14:31:08.450235 18799 solver.cpp:237]     Train net output #0: loss = 4.93379 (* 1 = 4.93379 loss)
I0405 14:31:08.450243 18799 sgd_solver.cpp:105] Iteration 11592, lr = 0.0001
I0405 14:31:13.682592 18799 solver.cpp:218] Iteration 11604 (2.29344 iter/s, 5.23231s/12 iters), loss = 4.93048
I0405 14:31:13.682647 18799 solver.cpp:237]     Train net output #0: loss = 4.93048 (* 1 = 4.93048 loss)
I0405 14:31:13.682657 18799 sgd_solver.cpp:105] Iteration 11604, lr = 0.0001
I0405 14:31:19.039149 18799 solver.cpp:218] Iteration 11616 (2.24029 iter/s, 5.35646s/12 iters), loss = 5.05102
I0405 14:31:19.039301 18799 solver.cpp:237]     Train net output #0: loss = 5.05102 (* 1 = 5.05102 loss)
I0405 14:31:19.039307 18799 sgd_solver.cpp:105] Iteration 11616, lr = 0.0001
I0405 14:31:23.912276 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11628.caffemodel
I0405 14:31:27.649212 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11628.solverstate
I0405 14:31:30.717217 18799 solver.cpp:330] Iteration 11628, Testing net (#0)
I0405 14:31:30.717238 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:31:35.118932 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:31:35.118966 18799 solver.cpp:397]     Test net output #1: loss = 4.96075 (* 1 = 4.96075 loss)
I0405 14:31:35.187883 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:31:35.261143 18799 solver.cpp:218] Iteration 11628 (0.739748 iter/s, 16.2217s/12 iters), loss = 4.84799
I0405 14:31:35.261193 18799 solver.cpp:237]     Train net output #0: loss = 4.84799 (* 1 = 4.84799 loss)
I0405 14:31:35.261198 18799 sgd_solver.cpp:105] Iteration 11628, lr = 0.0001
I0405 14:31:36.085961 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:31:39.773447 18799 solver.cpp:218] Iteration 11640 (2.65946 iter/s, 4.5122s/12 iters), loss = 4.90634
I0405 14:31:39.773504 18799 solver.cpp:237]     Train net output #0: loss = 4.90634 (* 1 = 4.90634 loss)
I0405 14:31:39.773512 18799 sgd_solver.cpp:105] Iteration 11640, lr = 0.0001
I0405 14:31:44.972604 18799 solver.cpp:218] Iteration 11652 (2.30811 iter/s, 5.19905s/12 iters), loss = 4.92083
I0405 14:31:44.972661 18799 solver.cpp:237]     Train net output #0: loss = 4.92083 (* 1 = 4.92083 loss)
I0405 14:31:44.972669 18799 sgd_solver.cpp:105] Iteration 11652, lr = 0.0001
I0405 14:31:50.187850 18799 solver.cpp:218] Iteration 11664 (2.30099 iter/s, 5.21515s/12 iters), loss = 4.86652
I0405 14:31:50.187943 18799 solver.cpp:237]     Train net output #0: loss = 4.86652 (* 1 = 4.86652 loss)
I0405 14:31:50.187950 18799 sgd_solver.cpp:105] Iteration 11664, lr = 0.0001
I0405 14:31:55.648432 18799 solver.cpp:218] Iteration 11676 (2.19763 iter/s, 5.46044s/12 iters), loss = 4.76056
I0405 14:31:55.648486 18799 solver.cpp:237]     Train net output #0: loss = 4.76056 (* 1 = 4.76056 loss)
I0405 14:31:55.648494 18799 sgd_solver.cpp:105] Iteration 11676, lr = 0.0001
I0405 14:32:00.960413 18799 solver.cpp:218] Iteration 11688 (2.25909 iter/s, 5.31188s/12 iters), loss = 4.83489
I0405 14:32:00.960458 18799 solver.cpp:237]     Train net output #0: loss = 4.83489 (* 1 = 4.83489 loss)
I0405 14:32:00.960464 18799 sgd_solver.cpp:105] Iteration 11688, lr = 0.0001
I0405 14:32:06.168331 18799 solver.cpp:218] Iteration 11700 (2.30422 iter/s, 5.20783s/12 iters), loss = 4.94813
I0405 14:32:06.168372 18799 solver.cpp:237]     Train net output #0: loss = 4.94813 (* 1 = 4.94813 loss)
I0405 14:32:06.168377 18799 sgd_solver.cpp:105] Iteration 11700, lr = 0.0001
I0405 14:32:11.601593 18799 solver.cpp:218] Iteration 11712 (2.20866 iter/s, 5.43317s/12 iters), loss = 4.95587
I0405 14:32:11.601634 18799 solver.cpp:237]     Train net output #0: loss = 4.95587 (* 1 = 4.95587 loss)
I0405 14:32:11.601640 18799 sgd_solver.cpp:105] Iteration 11712, lr = 0.0001
I0405 14:32:16.990995 18799 solver.cpp:218] Iteration 11724 (2.22663 iter/s, 5.38931s/12 iters), loss = 4.94379
I0405 14:32:16.991046 18799 solver.cpp:237]     Train net output #0: loss = 4.94379 (* 1 = 4.94379 loss)
I0405 14:32:16.991055 18799 sgd_solver.cpp:105] Iteration 11724, lr = 0.0001
I0405 14:32:19.321594 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11730.caffemodel
I0405 14:32:22.755915 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11730.solverstate
I0405 14:32:25.173794 18799 solver.cpp:330] Iteration 11730, Testing net (#0)
I0405 14:32:25.173820 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:32:29.545506 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:32:29.576050 18799 solver.cpp:397]     Test net output #0: accuracy = 0.028799
I0405 14:32:29.576078 18799 solver.cpp:397]     Test net output #1: loss = 4.95848 (* 1 = 4.95848 loss)
I0405 14:32:30.196738 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:32:31.486155 18799 solver.cpp:218] Iteration 11736 (0.827871 iter/s, 14.495s/12 iters), loss = 5.02756
I0405 14:32:31.486198 18799 solver.cpp:237]     Train net output #0: loss = 5.02756 (* 1 = 5.02756 loss)
I0405 14:32:31.486204 18799 sgd_solver.cpp:105] Iteration 11736, lr = 0.0001
I0405 14:32:36.788913 18799 solver.cpp:218] Iteration 11748 (2.26301 iter/s, 5.30266s/12 iters), loss = 4.99343
I0405 14:32:36.788954 18799 solver.cpp:237]     Train net output #0: loss = 4.99343 (* 1 = 4.99343 loss)
I0405 14:32:36.788959 18799 sgd_solver.cpp:105] Iteration 11748, lr = 0.0001
I0405 14:32:42.085919 18799 solver.cpp:218] Iteration 11760 (2.26547 iter/s, 5.29692s/12 iters), loss = 4.8077
I0405 14:32:42.085955 18799 solver.cpp:237]     Train net output #0: loss = 4.8077 (* 1 = 4.8077 loss)
I0405 14:32:42.085960 18799 sgd_solver.cpp:105] Iteration 11760, lr = 0.0001
I0405 14:32:47.456212 18799 solver.cpp:218] Iteration 11772 (2.23455 iter/s, 5.37021s/12 iters), loss = 4.89223
I0405 14:32:47.456251 18799 solver.cpp:237]     Train net output #0: loss = 4.89223 (* 1 = 4.89223 loss)
I0405 14:32:47.456257 18799 sgd_solver.cpp:105] Iteration 11772, lr = 0.0001
I0405 14:32:51.379468 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:32:52.814733 18799 solver.cpp:218] Iteration 11784 (2.23946 iter/s, 5.35843s/12 iters), loss = 4.89203
I0405 14:32:52.814842 18799 solver.cpp:237]     Train net output #0: loss = 4.89203 (* 1 = 4.89203 loss)
I0405 14:32:52.814849 18799 sgd_solver.cpp:105] Iteration 11784, lr = 0.0001
I0405 14:32:58.141543 18799 solver.cpp:218] Iteration 11796 (2.25286 iter/s, 5.32657s/12 iters), loss = 4.74832
I0405 14:32:58.141598 18799 solver.cpp:237]     Train net output #0: loss = 4.74832 (* 1 = 4.74832 loss)
I0405 14:32:58.141606 18799 sgd_solver.cpp:105] Iteration 11796, lr = 0.0001
I0405 14:33:03.316200 18799 solver.cpp:218] Iteration 11808 (2.31904 iter/s, 5.17455s/12 iters), loss = 4.85017
I0405 14:33:03.316260 18799 solver.cpp:237]     Train net output #0: loss = 4.85017 (* 1 = 4.85017 loss)
I0405 14:33:03.316268 18799 sgd_solver.cpp:105] Iteration 11808, lr = 0.0001
I0405 14:33:08.701655 18799 solver.cpp:218] Iteration 11820 (2.22827 iter/s, 5.38535s/12 iters), loss = 4.89781
I0405 14:33:08.701705 18799 solver.cpp:237]     Train net output #0: loss = 4.89781 (* 1 = 4.89781 loss)
I0405 14:33:08.701714 18799 sgd_solver.cpp:105] Iteration 11820, lr = 0.0001
I0405 14:33:13.539090 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11832.caffemodel
I0405 14:33:16.997480 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11832.solverstate
I0405 14:33:19.296854 18799 solver.cpp:330] Iteration 11832, Testing net (#0)
I0405 14:33:19.296875 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:33:23.545533 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:33:23.607877 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:33:23.607914 18799 solver.cpp:397]     Test net output #1: loss = 4.95141 (* 1 = 4.95141 loss)
I0405 14:33:23.739061 18799 solver.cpp:218] Iteration 11832 (0.798019 iter/s, 15.0372s/12 iters), loss = 4.85145
I0405 14:33:23.739125 18799 solver.cpp:237]     Train net output #0: loss = 4.85145 (* 1 = 4.85145 loss)
I0405 14:33:23.739132 18799 sgd_solver.cpp:105] Iteration 11832, lr = 0.0001
I0405 14:33:23.827338 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:33:27.986248 18799 solver.cpp:218] Iteration 11844 (2.82547 iter/s, 4.24708s/12 iters), loss = 4.93174
I0405 14:33:27.986302 18799 solver.cpp:237]     Train net output #0: loss = 4.93174 (* 1 = 4.93174 loss)
I0405 14:33:27.986311 18799 sgd_solver.cpp:105] Iteration 11844, lr = 0.0001
I0405 14:33:33.357101 18799 solver.cpp:218] Iteration 11856 (2.23432 iter/s, 5.37075s/12 iters), loss = 4.88969
I0405 14:33:33.357143 18799 solver.cpp:237]     Train net output #0: loss = 4.88969 (* 1 = 4.88969 loss)
I0405 14:33:33.357148 18799 sgd_solver.cpp:105] Iteration 11856, lr = 0.0001
I0405 14:33:38.574342 18799 solver.cpp:218] Iteration 11868 (2.30011 iter/s, 5.21715s/12 iters), loss = 4.92582
I0405 14:33:38.574381 18799 solver.cpp:237]     Train net output #0: loss = 4.92582 (* 1 = 4.92582 loss)
I0405 14:33:38.574386 18799 sgd_solver.cpp:105] Iteration 11868, lr = 0.0001
I0405 14:33:43.957351 18799 solver.cpp:218] Iteration 11880 (2.22927 iter/s, 5.38292s/12 iters), loss = 4.86257
I0405 14:33:43.957397 18799 solver.cpp:237]     Train net output #0: loss = 4.86257 (* 1 = 4.86257 loss)
I0405 14:33:43.957407 18799 sgd_solver.cpp:105] Iteration 11880, lr = 0.0001
I0405 14:33:49.156714 18799 solver.cpp:218] Iteration 11892 (2.30802 iter/s, 5.19927s/12 iters), loss = 4.9709
I0405 14:33:49.156764 18799 solver.cpp:237]     Train net output #0: loss = 4.9709 (* 1 = 4.9709 loss)
I0405 14:33:49.156771 18799 sgd_solver.cpp:105] Iteration 11892, lr = 0.0001
I0405 14:33:54.508404 18799 solver.cpp:218] Iteration 11904 (2.24232 iter/s, 5.3516s/12 iters), loss = 4.94415
I0405 14:33:54.508467 18799 solver.cpp:237]     Train net output #0: loss = 4.94415 (* 1 = 4.94415 loss)
I0405 14:33:54.508473 18799 sgd_solver.cpp:105] Iteration 11904, lr = 0.0001
I0405 14:33:59.928563 18799 solver.cpp:218] Iteration 11916 (2.214 iter/s, 5.42005s/12 iters), loss = 4.99495
I0405 14:33:59.928601 18799 solver.cpp:237]     Train net output #0: loss = 4.99495 (* 1 = 4.99495 loss)
I0405 14:33:59.928606 18799 sgd_solver.cpp:105] Iteration 11916, lr = 0.0001
I0405 14:34:05.207039 18799 solver.cpp:218] Iteration 11928 (2.27342 iter/s, 5.27839s/12 iters), loss = 4.94069
I0405 14:34:05.207093 18799 solver.cpp:237]     Train net output #0: loss = 4.94069 (* 1 = 4.94069 loss)
I0405 14:34:05.207100 18799 sgd_solver.cpp:105] Iteration 11928, lr = 0.0001
I0405 14:34:07.376282 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11934.caffemodel
I0405 14:34:08.408109 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:34:10.450969 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11934.solverstate
I0405 14:34:12.756636 18799 solver.cpp:330] Iteration 11934, Testing net (#0)
I0405 14:34:12.756659 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:34:17.048446 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:34:17.154278 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0294118
I0405 14:34:17.154314 18799 solver.cpp:397]     Test net output #1: loss = 4.95412 (* 1 = 4.95412 loss)
I0405 14:34:18.912927 18799 solver.cpp:218] Iteration 11940 (0.875546 iter/s, 13.7057s/12 iters), loss = 4.91204
I0405 14:34:18.912972 18799 solver.cpp:237]     Train net output #0: loss = 4.91204 (* 1 = 4.91204 loss)
I0405 14:34:18.912978 18799 sgd_solver.cpp:105] Iteration 11940, lr = 0.0001
I0405 14:34:24.170537 18799 solver.cpp:218] Iteration 11952 (2.28245 iter/s, 5.25751s/12 iters), loss = 4.90882
I0405 14:34:24.170595 18799 solver.cpp:237]     Train net output #0: loss = 4.90882 (* 1 = 4.90882 loss)
I0405 14:34:24.170605 18799 sgd_solver.cpp:105] Iteration 11952, lr = 0.0001
I0405 14:34:29.586256 18799 solver.cpp:218] Iteration 11964 (2.21582 iter/s, 5.41561s/12 iters), loss = 5.03844
I0405 14:34:29.586437 18799 solver.cpp:237]     Train net output #0: loss = 5.03844 (* 1 = 5.03844 loss)
I0405 14:34:29.586447 18799 sgd_solver.cpp:105] Iteration 11964, lr = 0.0001
I0405 14:34:34.963951 18799 solver.cpp:218] Iteration 11976 (2.23153 iter/s, 5.37747s/12 iters), loss = 4.93369
I0405 14:34:34.964006 18799 solver.cpp:237]     Train net output #0: loss = 4.93369 (* 1 = 4.93369 loss)
I0405 14:34:34.964015 18799 sgd_solver.cpp:105] Iteration 11976, lr = 0.0001
I0405 14:34:40.334585 18799 solver.cpp:218] Iteration 11988 (2.23442 iter/s, 5.37053s/12 iters), loss = 5.01478
I0405 14:34:40.334635 18799 solver.cpp:237]     Train net output #0: loss = 5.01478 (* 1 = 5.01478 loss)
I0405 14:34:40.334643 18799 sgd_solver.cpp:105] Iteration 11988, lr = 0.0001
I0405 14:34:45.653991 18799 solver.cpp:218] Iteration 12000 (2.25593 iter/s, 5.3193s/12 iters), loss = 4.99666
I0405 14:34:45.654038 18799 solver.cpp:237]     Train net output #0: loss = 4.99666 (* 1 = 4.99666 loss)
I0405 14:34:45.654045 18799 sgd_solver.cpp:105] Iteration 12000, lr = 0.0001
I0405 14:34:50.993144 18799 solver.cpp:218] Iteration 12012 (2.24759 iter/s, 5.33906s/12 iters), loss = 4.99149
I0405 14:34:50.993180 18799 solver.cpp:237]     Train net output #0: loss = 4.99149 (* 1 = 4.99149 loss)
I0405 14:34:50.993185 18799 sgd_solver.cpp:105] Iteration 12012, lr = 0.0001
I0405 14:34:56.485832 18799 solver.cpp:218] Iteration 12024 (2.18476 iter/s, 5.49261s/12 iters), loss = 4.94925
I0405 14:34:56.485872 18799 solver.cpp:237]     Train net output #0: loss = 4.94925 (* 1 = 4.94925 loss)
I0405 14:34:56.485877 18799 sgd_solver.cpp:105] Iteration 12024, lr = 0.0001
I0405 14:35:01.299145 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12036.caffemodel
I0405 14:35:01.885991 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:35:04.320403 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12036.solverstate
I0405 14:35:07.774749 18799 solver.cpp:330] Iteration 12036, Testing net (#0)
I0405 14:35:07.774775 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:35:11.915205 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:35:12.052973 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0294118
I0405 14:35:12.053012 18799 solver.cpp:397]     Test net output #1: loss = 4.9507 (* 1 = 4.9507 loss)
I0405 14:35:12.195191 18799 solver.cpp:218] Iteration 12036 (0.763883 iter/s, 15.7092s/12 iters), loss = 4.92999
I0405 14:35:12.195238 18799 solver.cpp:237]     Train net output #0: loss = 4.92999 (* 1 = 4.92999 loss)
I0405 14:35:12.195245 18799 sgd_solver.cpp:105] Iteration 12036, lr = 0.0001
I0405 14:35:16.613130 18799 solver.cpp:218] Iteration 12048 (2.71626 iter/s, 4.41785s/12 iters), loss = 5.01506
I0405 14:35:16.613188 18799 solver.cpp:237]     Train net output #0: loss = 5.01506 (* 1 = 5.01506 loss)
I0405 14:35:16.613196 18799 sgd_solver.cpp:105] Iteration 12048, lr = 0.0001
I0405 14:35:21.981000 18799 solver.cpp:218] Iteration 12060 (2.23557 iter/s, 5.36776s/12 iters), loss = 5.03785
I0405 14:35:21.981056 18799 solver.cpp:237]     Train net output #0: loss = 5.03785 (* 1 = 5.03785 loss)
I0405 14:35:21.981065 18799 sgd_solver.cpp:105] Iteration 12060, lr = 0.0001
I0405 14:35:27.440861 18799 solver.cpp:218] Iteration 12072 (2.1979 iter/s, 5.45976s/12 iters), loss = 4.85379
I0405 14:35:27.440928 18799 solver.cpp:237]     Train net output #0: loss = 4.85379 (* 1 = 4.85379 loss)
I0405 14:35:27.440937 18799 sgd_solver.cpp:105] Iteration 12072, lr = 0.0001
I0405 14:35:32.809193 18799 solver.cpp:218] Iteration 12084 (2.23538 iter/s, 5.36821s/12 iters), loss = 4.97718
I0405 14:35:32.809324 18799 solver.cpp:237]     Train net output #0: loss = 4.97718 (* 1 = 4.97718 loss)
I0405 14:35:32.809332 18799 sgd_solver.cpp:105] Iteration 12084, lr = 0.0001
I0405 14:35:38.049734 18799 solver.cpp:218] Iteration 12096 (2.28992 iter/s, 5.24037s/12 iters), loss = 4.79126
I0405 14:35:38.049772 18799 solver.cpp:237]     Train net output #0: loss = 4.79126 (* 1 = 4.79126 loss)
I0405 14:35:38.049777 18799 sgd_solver.cpp:105] Iteration 12096, lr = 0.0001
I0405 14:35:43.687958 18799 solver.cpp:218] Iteration 12108 (2.12836 iter/s, 5.63814s/12 iters), loss = 4.83591
I0405 14:35:43.688004 18799 solver.cpp:237]     Train net output #0: loss = 4.83591 (* 1 = 4.83591 loss)
I0405 14:35:43.688009 18799 sgd_solver.cpp:105] Iteration 12108, lr = 0.0001
I0405 14:35:48.998291 18799 solver.cpp:218] Iteration 12120 (2.25979 iter/s, 5.31024s/12 iters), loss = 4.94727
I0405 14:35:48.998335 18799 solver.cpp:237]     Train net output #0: loss = 4.94727 (* 1 = 4.94727 loss)
I0405 14:35:48.998342 18799 sgd_solver.cpp:105] Iteration 12120, lr = 0.0001
I0405 14:35:54.258898 18799 solver.cpp:218] Iteration 12132 (2.28115 iter/s, 5.26051s/12 iters), loss = 4.91438
I0405 14:35:54.258955 18799 solver.cpp:237]     Train net output #0: loss = 4.91438 (* 1 = 4.91438 loss)
I0405 14:35:54.258963 18799 sgd_solver.cpp:105] Iteration 12132, lr = 0.0001
I0405 14:35:56.434787 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12138.caffemodel
I0405 14:35:56.826839 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:35:59.482728 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12138.solverstate
I0405 14:36:01.814874 18799 solver.cpp:330] Iteration 12138, Testing net (#0)
I0405 14:36:01.814894 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:36:06.024173 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:36:06.195261 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0281863
I0405 14:36:06.195297 18799 solver.cpp:397]     Test net output #1: loss = 4.94808 (* 1 = 4.94808 loss)
I0405 14:36:08.123234 18799 solver.cpp:218] Iteration 12144 (0.86554 iter/s, 13.8642s/12 iters), loss = 4.92622
I0405 14:36:08.123278 18799 solver.cpp:237]     Train net output #0: loss = 4.92622 (* 1 = 4.92622 loss)
I0405 14:36:08.123284 18799 sgd_solver.cpp:105] Iteration 12144, lr = 0.0001
I0405 14:36:13.583874 18799 solver.cpp:218] Iteration 12156 (2.19758 iter/s, 5.46054s/12 iters), loss = 4.85669
I0405 14:36:13.583918 18799 solver.cpp:237]     Train net output #0: loss = 4.85669 (* 1 = 4.85669 loss)
I0405 14:36:13.583925 18799 sgd_solver.cpp:105] Iteration 12156, lr = 0.0001
I0405 14:36:18.860069 18799 solver.cpp:218] Iteration 12168 (2.27441 iter/s, 5.27611s/12 iters), loss = 4.99308
I0405 14:36:18.860103 18799 solver.cpp:237]     Train net output #0: loss = 4.99308 (* 1 = 4.99308 loss)
I0405 14:36:18.860110 18799 sgd_solver.cpp:105] Iteration 12168, lr = 0.0001
I0405 14:36:24.383055 18799 solver.cpp:218] Iteration 12180 (2.17277 iter/s, 5.5229s/12 iters), loss = 4.90353
I0405 14:36:24.383107 18799 solver.cpp:237]     Train net output #0: loss = 4.90353 (* 1 = 4.90353 loss)
I0405 14:36:24.383116 18799 sgd_solver.cpp:105] Iteration 12180, lr = 0.0001
I0405 14:36:29.759176 18799 solver.cpp:218] Iteration 12192 (2.23213 iter/s, 5.37602s/12 iters), loss = 4.93314
I0405 14:36:29.759215 18799 solver.cpp:237]     Train net output #0: loss = 4.93314 (* 1 = 4.93314 loss)
I0405 14:36:29.759222 18799 sgd_solver.cpp:105] Iteration 12192, lr = 0.0001
I0405 14:36:35.174839 18799 solver.cpp:218] Iteration 12204 (2.21583 iter/s, 5.41557s/12 iters), loss = 4.87034
I0405 14:36:35.174888 18799 solver.cpp:237]     Train net output #0: loss = 4.87034 (* 1 = 4.87034 loss)
I0405 14:36:35.174896 18799 sgd_solver.cpp:105] Iteration 12204, lr = 0.0001
I0405 14:36:40.609841 18799 solver.cpp:218] Iteration 12216 (2.20795 iter/s, 5.4349s/12 iters), loss = 4.87638
I0405 14:36:40.609951 18799 solver.cpp:237]     Train net output #0: loss = 4.87638 (* 1 = 4.87638 loss)
I0405 14:36:40.609961 18799 sgd_solver.cpp:105] Iteration 12216, lr = 0.0001
I0405 14:36:46.256934 18799 solver.cpp:218] Iteration 12228 (2.12505 iter/s, 5.64694s/12 iters), loss = 4.81078
I0405 14:36:46.256973 18799 solver.cpp:237]     Train net output #0: loss = 4.81078 (* 1 = 4.81078 loss)
I0405 14:36:46.256978 18799 sgd_solver.cpp:105] Iteration 12228, lr = 0.0001
I0405 14:36:50.601928 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:36:50.690788 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12240.caffemodel
I0405 14:36:53.793785 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12240.solverstate
I0405 14:36:56.102520 18799 solver.cpp:330] Iteration 12240, Testing net (#0)
I0405 14:36:56.102542 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:37:00.572144 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:37:00.799013 18799 solver.cpp:397]     Test net output #0: accuracy = 0.026348
I0405 14:37:00.799048 18799 solver.cpp:397]     Test net output #1: loss = 4.94835 (* 1 = 4.94835 loss)
I0405 14:37:00.941095 18799 solver.cpp:218] Iteration 12240 (0.817215 iter/s, 14.684s/12 iters), loss = 4.98424
I0405 14:37:00.942680 18799 solver.cpp:237]     Train net output #0: loss = 4.98424 (* 1 = 4.98424 loss)
I0405 14:37:00.942694 18799 sgd_solver.cpp:105] Iteration 12240, lr = 0.0001
I0405 14:37:05.267872 18799 solver.cpp:218] Iteration 12252 (2.77447 iter/s, 4.32516s/12 iters), loss = 4.88966
I0405 14:37:05.267923 18799 solver.cpp:237]     Train net output #0: loss = 4.88966 (* 1 = 4.88966 loss)
I0405 14:37:05.267932 18799 sgd_solver.cpp:105] Iteration 12252, lr = 0.0001
I0405 14:37:10.650300 18799 solver.cpp:218] Iteration 12264 (2.22952 iter/s, 5.38233s/12 iters), loss = 4.80896
I0405 14:37:10.650437 18799 solver.cpp:237]     Train net output #0: loss = 4.80896 (* 1 = 4.80896 loss)
I0405 14:37:10.650444 18799 sgd_solver.cpp:105] Iteration 12264, lr = 0.0001
I0405 14:37:16.016618 18799 solver.cpp:218] Iteration 12276 (2.23625 iter/s, 5.36613s/12 iters), loss = 4.80993
I0405 14:37:16.016657 18799 solver.cpp:237]     Train net output #0: loss = 4.80993 (* 1 = 4.80993 loss)
I0405 14:37:16.016662 18799 sgd_solver.cpp:105] Iteration 12276, lr = 0.0001
I0405 14:37:21.275236 18799 solver.cpp:218] Iteration 12288 (2.28201 iter/s, 5.25853s/12 iters), loss = 4.85912
I0405 14:37:21.275276 18799 solver.cpp:237]     Train net output #0: loss = 4.85912 (* 1 = 4.85912 loss)
I0405 14:37:21.275282 18799 sgd_solver.cpp:105] Iteration 12288, lr = 0.0001
I0405 14:37:26.542158 18799 solver.cpp:218] Iteration 12300 (2.27841 iter/s, 5.26683s/12 iters), loss = 5.01107
I0405 14:37:26.542201 18799 solver.cpp:237]     Train net output #0: loss = 5.01107 (* 1 = 5.01107 loss)
I0405 14:37:26.542208 18799 sgd_solver.cpp:105] Iteration 12300, lr = 0.0001
I0405 14:37:32.038462 18799 solver.cpp:218] Iteration 12312 (2.18332 iter/s, 5.49621s/12 iters), loss = 4.87298
I0405 14:37:32.038499 18799 solver.cpp:237]     Train net output #0: loss = 4.87298 (* 1 = 4.87298 loss)
I0405 14:37:32.038506 18799 sgd_solver.cpp:105] Iteration 12312, lr = 0.0001
I0405 14:37:37.177968 18799 solver.cpp:218] Iteration 12324 (2.33489 iter/s, 5.13942s/12 iters), loss = 4.9791
I0405 14:37:37.178023 18799 solver.cpp:237]     Train net output #0: loss = 4.9791 (* 1 = 4.9791 loss)
I0405 14:37:37.178031 18799 sgd_solver.cpp:105] Iteration 12324, lr = 0.0001
I0405 14:37:42.450556 18799 solver.cpp:218] Iteration 12336 (2.27596 iter/s, 5.27249s/12 iters), loss = 4.83763
I0405 14:37:42.450675 18799 solver.cpp:237]     Train net output #0: loss = 4.83763 (* 1 = 4.83763 loss)
I0405 14:37:42.450683 18799 sgd_solver.cpp:105] Iteration 12336, lr = 0.0001
I0405 14:37:44.139565 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:37:44.478958 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12342.caffemodel
I0405 14:37:47.503682 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12342.solverstate
I0405 14:37:49.818871 18799 solver.cpp:330] Iteration 12342, Testing net (#0)
I0405 14:37:49.818889 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:37:54.024312 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:37:54.276077 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:37:54.276113 18799 solver.cpp:397]     Test net output #1: loss = 4.94096 (* 1 = 4.94096 loss)
I0405 14:37:56.195612 18799 solver.cpp:218] Iteration 12348 (0.873055 iter/s, 13.7448s/12 iters), loss = 4.88995
I0405 14:37:56.195662 18799 solver.cpp:237]     Train net output #0: loss = 4.88995 (* 1 = 4.88995 loss)
I0405 14:37:56.195669 18799 sgd_solver.cpp:105] Iteration 12348, lr = 0.0001
I0405 14:38:01.354369 18799 solver.cpp:218] Iteration 12360 (2.32619 iter/s, 5.15866s/12 iters), loss = 4.87996
I0405 14:38:01.354418 18799 solver.cpp:237]     Train net output #0: loss = 4.87996 (* 1 = 4.87996 loss)
I0405 14:38:01.354426 18799 sgd_solver.cpp:105] Iteration 12360, lr = 0.0001
I0405 14:38:06.644513 18799 solver.cpp:218] Iteration 12372 (2.26841 iter/s, 5.29005s/12 iters), loss = 4.80884
I0405 14:38:06.644558 18799 solver.cpp:237]     Train net output #0: loss = 4.80884 (* 1 = 4.80884 loss)
I0405 14:38:06.644563 18799 sgd_solver.cpp:105] Iteration 12372, lr = 0.0001
I0405 14:38:11.833762 18799 solver.cpp:218] Iteration 12384 (2.31252 iter/s, 5.18915s/12 iters), loss = 4.72151
I0405 14:38:11.833804 18799 solver.cpp:237]     Train net output #0: loss = 4.72151 (* 1 = 4.72151 loss)
I0405 14:38:11.833811 18799 sgd_solver.cpp:105] Iteration 12384, lr = 0.0001
I0405 14:38:17.125460 18799 solver.cpp:218] Iteration 12396 (2.26774 iter/s, 5.29161s/12 iters), loss = 4.82832
I0405 14:38:17.125566 18799 solver.cpp:237]     Train net output #0: loss = 4.82832 (* 1 = 4.82832 loss)
I0405 14:38:17.125572 18799 sgd_solver.cpp:105] Iteration 12396, lr = 0.0001
I0405 14:38:22.410102 18799 solver.cpp:218] Iteration 12408 (2.2708 iter/s, 5.28448s/12 iters), loss = 4.85565
I0405 14:38:22.410151 18799 solver.cpp:237]     Train net output #0: loss = 4.85565 (* 1 = 4.85565 loss)
I0405 14:38:22.410156 18799 sgd_solver.cpp:105] Iteration 12408, lr = 0.0001
I0405 14:38:27.605073 18799 solver.cpp:218] Iteration 12420 (2.30997 iter/s, 5.19488s/12 iters), loss = 4.84762
I0405 14:38:27.605118 18799 solver.cpp:237]     Train net output #0: loss = 4.84762 (* 1 = 4.84762 loss)
I0405 14:38:27.605123 18799 sgd_solver.cpp:105] Iteration 12420, lr = 0.0001
I0405 14:38:32.671892 18799 solver.cpp:218] Iteration 12432 (2.36839 iter/s, 5.06672s/12 iters), loss = 4.84375
I0405 14:38:32.671945 18799 solver.cpp:237]     Train net output #0: loss = 4.84375 (* 1 = 4.84375 loss)
I0405 14:38:32.671954 18799 sgd_solver.cpp:105] Iteration 12432, lr = 0.0001
I0405 14:38:36.764900 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:38:37.503718 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12444.caffemodel
I0405 14:38:40.528373 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12444.solverstate
I0405 14:38:42.852756 18799 solver.cpp:330] Iteration 12444, Testing net (#0)
I0405 14:38:42.852774 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:38:47.076371 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:38:47.416311 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:38:47.416412 18799 solver.cpp:397]     Test net output #1: loss = 4.93694 (* 1 = 4.93694 loss)
I0405 14:38:47.552757 18799 solver.cpp:218] Iteration 12444 (0.806413 iter/s, 14.8807s/12 iters), loss = 4.91881
I0405 14:38:47.552807 18799 solver.cpp:237]     Train net output #0: loss = 4.91881 (* 1 = 4.91881 loss)
I0405 14:38:47.552814 18799 sgd_solver.cpp:105] Iteration 12444, lr = 0.0001
I0405 14:38:51.967941 18799 solver.cpp:218] Iteration 12456 (2.71795 iter/s, 4.41509s/12 iters), loss = 4.88761
I0405 14:38:51.967979 18799 solver.cpp:237]     Train net output #0: loss = 4.88761 (* 1 = 4.88761 loss)
I0405 14:38:51.967985 18799 sgd_solver.cpp:105] Iteration 12456, lr = 0.0001
I0405 14:38:56.282812 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:38:57.265457 18799 solver.cpp:218] Iteration 12468 (2.26525 iter/s, 5.29743s/12 iters), loss = 4.78776
I0405 14:38:57.265499 18799 solver.cpp:237]     Train net output #0: loss = 4.78776 (* 1 = 4.78776 loss)
I0405 14:38:57.265506 18799 sgd_solver.cpp:105] Iteration 12468, lr = 0.0001
I0405 14:39:02.536460 18799 solver.cpp:218] Iteration 12480 (2.27665 iter/s, 5.2709s/12 iters), loss = 4.78503
I0405 14:39:02.536509 18799 solver.cpp:237]     Train net output #0: loss = 4.78503 (* 1 = 4.78503 loss)
I0405 14:39:02.536515 18799 sgd_solver.cpp:105] Iteration 12480, lr = 0.0001
I0405 14:39:07.661581 18799 solver.cpp:218] Iteration 12492 (2.34145 iter/s, 5.12502s/12 iters), loss = 4.8456
I0405 14:39:07.661628 18799 solver.cpp:237]     Train net output #0: loss = 4.8456 (* 1 = 4.8456 loss)
I0405 14:39:07.661634 18799 sgd_solver.cpp:105] Iteration 12492, lr = 0.0001
I0405 14:39:13.150406 18799 solver.cpp:218] Iteration 12504 (2.1863 iter/s, 5.48873s/12 iters), loss = 4.72172
I0405 14:39:13.150449 18799 solver.cpp:237]     Train net output #0: loss = 4.72172 (* 1 = 4.72172 loss)
I0405 14:39:13.150455 18799 sgd_solver.cpp:105] Iteration 12504, lr = 0.0001
I0405 14:39:18.565922 18799 solver.cpp:218] Iteration 12516 (2.21589 iter/s, 5.41542s/12 iters), loss = 4.80833
I0405 14:39:18.566048 18799 solver.cpp:237]     Train net output #0: loss = 4.80833 (* 1 = 4.80833 loss)
I0405 14:39:18.566054 18799 sgd_solver.cpp:105] Iteration 12516, lr = 0.0001
I0405 14:39:23.985045 18799 solver.cpp:218] Iteration 12528 (2.21445 iter/s, 5.41894s/12 iters), loss = 4.88067
I0405 14:39:23.985105 18799 solver.cpp:237]     Train net output #0: loss = 4.88067 (* 1 = 4.88067 loss)
I0405 14:39:23.985117 18799 sgd_solver.cpp:105] Iteration 12528, lr = 0.0001
I0405 14:39:29.156877 18799 solver.cpp:218] Iteration 12540 (2.32031 iter/s, 5.17173s/12 iters), loss = 4.87264
I0405 14:39:29.156919 18799 solver.cpp:237]     Train net output #0: loss = 4.87264 (* 1 = 4.87264 loss)
I0405 14:39:29.156925 18799 sgd_solver.cpp:105] Iteration 12540, lr = 0.0001
I0405 14:39:30.163195 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:39:31.259660 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12546.caffemodel
I0405 14:39:34.265710 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12546.solverstate
I0405 14:39:36.569411 18799 solver.cpp:330] Iteration 12546, Testing net (#0)
I0405 14:39:36.569432 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:39:40.575956 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:39:40.904866 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0294118
I0405 14:39:40.904911 18799 solver.cpp:397]     Test net output #1: loss = 4.93183 (* 1 = 4.93183 loss)
I0405 14:39:42.788456 18799 solver.cpp:218] Iteration 12552 (0.880318 iter/s, 13.6314s/12 iters), loss = 4.85292
I0405 14:39:42.788501 18799 solver.cpp:237]     Train net output #0: loss = 4.85292 (* 1 = 4.85292 loss)
I0405 14:39:42.788508 18799 sgd_solver.cpp:105] Iteration 12552, lr = 0.0001
I0405 14:39:47.927122 18799 solver.cpp:218] Iteration 12564 (2.33528 iter/s, 5.13857s/12 iters), loss = 4.96152
I0405 14:39:47.927175 18799 solver.cpp:237]     Train net output #0: loss = 4.96152 (* 1 = 4.96152 loss)
I0405 14:39:47.927182 18799 sgd_solver.cpp:105] Iteration 12564, lr = 0.0001
I0405 14:39:53.214594 18799 solver.cpp:218] Iteration 12576 (2.26956 iter/s, 5.28737s/12 iters), loss = 4.89751
I0405 14:39:53.214728 18799 solver.cpp:237]     Train net output #0: loss = 4.89751 (* 1 = 4.89751 loss)
I0405 14:39:53.214737 18799 sgd_solver.cpp:105] Iteration 12576, lr = 0.0001
I0405 14:39:58.586690 18799 solver.cpp:218] Iteration 12588 (2.23384 iter/s, 5.37192s/12 iters), loss = 4.91615
I0405 14:39:58.586731 18799 solver.cpp:237]     Train net output #0: loss = 4.91615 (* 1 = 4.91615 loss)
I0405 14:39:58.586737 18799 sgd_solver.cpp:105] Iteration 12588, lr = 0.0001
I0405 14:40:03.663919 18799 solver.cpp:218] Iteration 12600 (2.36353 iter/s, 5.07714s/12 iters), loss = 5.04238
I0405 14:40:03.663965 18799 solver.cpp:237]     Train net output #0: loss = 5.04238 (* 1 = 5.04238 loss)
I0405 14:40:03.663971 18799 sgd_solver.cpp:105] Iteration 12600, lr = 0.0001
I0405 14:40:08.958895 18799 solver.cpp:218] Iteration 12612 (2.26634 iter/s, 5.29489s/12 iters), loss = 4.85393
I0405 14:40:08.958932 18799 solver.cpp:237]     Train net output #0: loss = 4.85393 (* 1 = 4.85393 loss)
I0405 14:40:08.958938 18799 sgd_solver.cpp:105] Iteration 12612, lr = 0.0001
I0405 14:40:14.163007 18799 solver.cpp:218] Iteration 12624 (2.30591 iter/s, 5.20402s/12 iters), loss = 4.87503
I0405 14:40:14.163051 18799 solver.cpp:237]     Train net output #0: loss = 4.87503 (* 1 = 4.87503 loss)
I0405 14:40:14.163056 18799 sgd_solver.cpp:105] Iteration 12624, lr = 0.0001
I0405 14:40:19.511373 18799 solver.cpp:218] Iteration 12636 (2.24372 iter/s, 5.34827s/12 iters), loss = 4.84308
I0405 14:40:19.511415 18799 solver.cpp:237]     Train net output #0: loss = 4.84308 (* 1 = 4.84308 loss)
I0405 14:40:19.511421 18799 sgd_solver.cpp:105] Iteration 12636, lr = 0.0001
I0405 14:40:22.965174 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:40:24.571640 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12648.caffemodel
I0405 14:40:27.613160 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12648.solverstate
I0405 14:40:29.918232 18799 solver.cpp:330] Iteration 12648, Testing net (#0)
I0405 14:40:29.918256 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:40:33.918135 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:40:34.294433 18799 solver.cpp:397]     Test net output #0: accuracy = 0.028799
I0405 14:40:34.294467 18799 solver.cpp:397]     Test net output #1: loss = 4.92792 (* 1 = 4.92792 loss)
I0405 14:40:34.431362 18799 solver.cpp:218] Iteration 12648 (0.804298 iter/s, 14.9198s/12 iters), loss = 4.82941
I0405 14:40:34.432960 18799 solver.cpp:237]     Train net output #0: loss = 4.82941 (* 1 = 4.82941 loss)
I0405 14:40:34.432974 18799 sgd_solver.cpp:105] Iteration 12648, lr = 0.0001
I0405 14:40:38.630173 18799 solver.cpp:218] Iteration 12660 (2.85906 iter/s, 4.19718s/12 iters), loss = 4.85063
I0405 14:40:38.630214 18799 solver.cpp:237]     Train net output #0: loss = 4.85063 (* 1 = 4.85063 loss)
I0405 14:40:38.630220 18799 sgd_solver.cpp:105] Iteration 12660, lr = 0.0001
I0405 14:40:43.792865 18799 solver.cpp:218] Iteration 12672 (2.32441 iter/s, 5.1626s/12 iters), loss = 4.97108
I0405 14:40:43.792912 18799 solver.cpp:237]     Train net output #0: loss = 4.97108 (* 1 = 4.97108 loss)
I0405 14:40:43.792918 18799 sgd_solver.cpp:105] Iteration 12672, lr = 0.0001
I0405 14:40:49.184252 18799 solver.cpp:218] Iteration 12684 (2.22581 iter/s, 5.39129s/12 iters), loss = 4.91444
I0405 14:40:49.184306 18799 solver.cpp:237]     Train net output #0: loss = 4.91444 (* 1 = 4.91444 loss)
I0405 14:40:49.184314 18799 sgd_solver.cpp:105] Iteration 12684, lr = 0.0001
I0405 14:40:54.464803 18799 solver.cpp:218] Iteration 12696 (2.27253 iter/s, 5.28045s/12 iters), loss = 4.92903
I0405 14:40:54.464843 18799 solver.cpp:237]     Train net output #0: loss = 4.92903 (* 1 = 4.92903 loss)
I0405 14:40:54.464849 18799 sgd_solver.cpp:105] Iteration 12696, lr = 0.0001
I0405 14:41:00.038079 18799 solver.cpp:218] Iteration 12708 (2.15317 iter/s, 5.57319s/12 iters), loss = 4.90133
I0405 14:41:00.038223 18799 solver.cpp:237]     Train net output #0: loss = 4.90133 (* 1 = 4.90133 loss)
I0405 14:41:00.038233 18799 sgd_solver.cpp:105] Iteration 12708, lr = 0.0001
I0405 14:41:05.461273 18799 solver.cpp:218] Iteration 12720 (2.2128 iter/s, 5.42301s/12 iters), loss = 4.9546
I0405 14:41:05.461315 18799 solver.cpp:237]     Train net output #0: loss = 4.9546 (* 1 = 4.9546 loss)
I0405 14:41:05.461321 18799 sgd_solver.cpp:105] Iteration 12720, lr = 0.0001
I0405 14:41:11.009693 18799 solver.cpp:218] Iteration 12732 (2.16282 iter/s, 5.54832s/12 iters), loss = 4.96099
I0405 14:41:11.009745 18799 solver.cpp:237]     Train net output #0: loss = 4.96099 (* 1 = 4.96099 loss)
I0405 14:41:11.009753 18799 sgd_solver.cpp:105] Iteration 12732, lr = 0.0001
I0405 14:41:16.364699 18799 solver.cpp:218] Iteration 12744 (2.24093 iter/s, 5.35491s/12 iters), loss = 4.85203
I0405 14:41:16.364738 18799 solver.cpp:237]     Train net output #0: loss = 4.85203 (* 1 = 4.85203 loss)
I0405 14:41:16.364743 18799 sgd_solver.cpp:105] Iteration 12744, lr = 0.0001
I0405 14:41:16.522615 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:41:18.369011 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12750.caffemodel
I0405 14:41:21.361550 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12750.solverstate
I0405 14:41:23.666424 18799 solver.cpp:330] Iteration 12750, Testing net (#0)
I0405 14:41:23.666443 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:41:27.632181 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:41:28.040477 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0405 14:41:28.040518 18799 solver.cpp:397]     Test net output #1: loss = 4.93035 (* 1 = 4.93035 loss)
I0405 14:41:30.007663 18799 solver.cpp:218] Iteration 12756 (0.879583 iter/s, 13.6428s/12 iters), loss = 4.93806
I0405 14:41:30.007704 18799 solver.cpp:237]     Train net output #0: loss = 4.93806 (* 1 = 4.93806 loss)
I0405 14:41:30.007709 18799 sgd_solver.cpp:105] Iteration 12756, lr = 0.0001
I0405 14:41:35.293817 18799 solver.cpp:218] Iteration 12768 (2.27012 iter/s, 5.28606s/12 iters), loss = 4.95406
I0405 14:41:35.293984 18799 solver.cpp:237]     Train net output #0: loss = 4.95406 (* 1 = 4.95406 loss)
I0405 14:41:35.293993 18799 sgd_solver.cpp:105] Iteration 12768, lr = 0.0001
I0405 14:41:40.312258 18799 solver.cpp:218] Iteration 12780 (2.39128 iter/s, 5.01823s/12 iters), loss = 4.84704
I0405 14:41:40.312309 18799 solver.cpp:237]     Train net output #0: loss = 4.84704 (* 1 = 4.84704 loss)
I0405 14:41:40.312323 18799 sgd_solver.cpp:105] Iteration 12780, lr = 0.0001
I0405 14:41:45.467507 18799 solver.cpp:218] Iteration 12792 (2.32777 iter/s, 5.15515s/12 iters), loss = 5.04426
I0405 14:41:45.467548 18799 solver.cpp:237]     Train net output #0: loss = 5.04426 (* 1 = 5.04426 loss)
I0405 14:41:45.467554 18799 sgd_solver.cpp:105] Iteration 12792, lr = 0.0001
I0405 14:41:50.741813 18799 solver.cpp:218] Iteration 12804 (2.27522 iter/s, 5.27422s/12 iters), loss = 4.79701
I0405 14:41:50.741866 18799 solver.cpp:237]     Train net output #0: loss = 4.79701 (* 1 = 4.79701 loss)
I0405 14:41:50.741875 18799 sgd_solver.cpp:105] Iteration 12804, lr = 0.0001
I0405 14:41:56.117869 18799 solver.cpp:218] Iteration 12816 (2.23216 iter/s, 5.37595s/12 iters), loss = 4.85823
I0405 14:41:56.117929 18799 solver.cpp:237]     Train net output #0: loss = 4.85823 (* 1 = 4.85823 loss)
I0405 14:41:56.117938 18799 sgd_solver.cpp:105] Iteration 12816, lr = 0.0001
I0405 14:42:01.498937 18799 solver.cpp:218] Iteration 12828 (2.23008 iter/s, 5.38096s/12 iters), loss = 4.92596
I0405 14:42:01.498983 18799 solver.cpp:237]     Train net output #0: loss = 4.92596 (* 1 = 4.92596 loss)
I0405 14:42:01.498991 18799 sgd_solver.cpp:105] Iteration 12828, lr = 0.0001
I0405 14:42:06.527513 18799 solver.cpp:218] Iteration 12840 (2.3864 iter/s, 5.02849s/12 iters), loss = 4.86999
I0405 14:42:06.527613 18799 solver.cpp:237]     Train net output #0: loss = 4.86999 (* 1 = 4.86999 loss)
I0405 14:42:06.527619 18799 sgd_solver.cpp:105] Iteration 12840, lr = 0.0001
I0405 14:42:09.024669 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:42:11.500288 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12852.caffemodel
I0405 14:42:14.574383 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12852.solverstate
I0405 14:42:16.989981 18799 solver.cpp:330] Iteration 12852, Testing net (#0)
I0405 14:42:16.990002 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:42:20.876400 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:42:21.330443 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0330882
I0405 14:42:21.330478 18799 solver.cpp:397]     Test net output #1: loss = 4.91946 (* 1 = 4.91946 loss)
I0405 14:42:21.468848 18799 solver.cpp:218] Iteration 12852 (0.803152 iter/s, 14.9411s/12 iters), loss = 4.88391
I0405 14:42:21.468912 18799 solver.cpp:237]     Train net output #0: loss = 4.88391 (* 1 = 4.88391 loss)
I0405 14:42:21.468919 18799 sgd_solver.cpp:105] Iteration 12852, lr = 0.0001
I0405 14:42:25.824730 18799 solver.cpp:218] Iteration 12864 (2.75496 iter/s, 4.35577s/12 iters), loss = 4.80745
I0405 14:42:25.824777 18799 solver.cpp:237]     Train net output #0: loss = 4.80745 (* 1 = 4.80745 loss)
I0405 14:42:25.824784 18799 sgd_solver.cpp:105] Iteration 12864, lr = 0.0001
I0405 14:42:31.182554 18799 solver.cpp:218] Iteration 12876 (2.23976 iter/s, 5.35772s/12 iters), loss = 4.9549
I0405 14:42:31.182616 18799 solver.cpp:237]     Train net output #0: loss = 4.9549 (* 1 = 4.9549 loss)
I0405 14:42:31.182624 18799 sgd_solver.cpp:105] Iteration 12876, lr = 0.0001
I0405 14:42:36.546228 18799 solver.cpp:218] Iteration 12888 (2.23732 iter/s, 5.36357s/12 iters), loss = 4.92275
I0405 14:42:36.546356 18799 solver.cpp:237]     Train net output #0: loss = 4.92275 (* 1 = 4.92275 loss)
I0405 14:42:36.546363 18799 sgd_solver.cpp:105] Iteration 12888, lr = 0.0001
I0405 14:42:41.923990 18799 solver.cpp:218] Iteration 12900 (2.23148 iter/s, 5.37759s/12 iters), loss = 4.97126
I0405 14:42:41.924027 18799 solver.cpp:237]     Train net output #0: loss = 4.97126 (* 1 = 4.97126 loss)
I0405 14:42:41.924032 18799 sgd_solver.cpp:105] Iteration 12900, lr = 0.0001
I0405 14:42:47.007763 18799 solver.cpp:218] Iteration 12912 (2.36049 iter/s, 5.08369s/12 iters), loss = 4.81961
I0405 14:42:47.007800 18799 solver.cpp:237]     Train net output #0: loss = 4.81961 (* 1 = 4.81961 loss)
I0405 14:42:47.007807 18799 sgd_solver.cpp:105] Iteration 12912, lr = 0.0001
I0405 14:42:52.631381 18799 solver.cpp:218] Iteration 12924 (2.13389 iter/s, 5.62353s/12 iters), loss = 4.80001
I0405 14:42:52.631418 18799 solver.cpp:237]     Train net output #0: loss = 4.80001 (* 1 = 4.80001 loss)
I0405 14:42:52.631423 18799 sgd_solver.cpp:105] Iteration 12924, lr = 0.0001
I0405 14:42:58.036161 18799 solver.cpp:218] Iteration 12936 (2.22029 iter/s, 5.40469s/12 iters), loss = 4.81653
I0405 14:42:58.036204 18799 solver.cpp:237]     Train net output #0: loss = 4.81653 (* 1 = 4.81653 loss)
I0405 14:42:58.036211 18799 sgd_solver.cpp:105] Iteration 12936, lr = 0.0001
I0405 14:43:02.870376 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:03.467593 18799 solver.cpp:218] Iteration 12948 (2.2094 iter/s, 5.43133s/12 iters), loss = 4.91382
I0405 14:43:03.467648 18799 solver.cpp:237]     Train net output #0: loss = 4.91382 (* 1 = 4.91382 loss)
I0405 14:43:03.467658 18799 sgd_solver.cpp:105] Iteration 12948, lr = 0.0001
I0405 14:43:05.620609 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12954.caffemodel
I0405 14:43:08.666296 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12954.solverstate
I0405 14:43:10.967072 18799 solver.cpp:330] Iteration 12954, Testing net (#0)
I0405 14:43:10.967092 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:43:14.805238 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:15.291976 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0349265
I0405 14:43:15.292011 18799 solver.cpp:397]     Test net output #1: loss = 4.92041 (* 1 = 4.92041 loss)
I0405 14:43:17.225562 18799 solver.cpp:218] Iteration 12960 (0.872231 iter/s, 13.7578s/12 iters), loss = 4.86039
I0405 14:43:17.225605 18799 solver.cpp:237]     Train net output #0: loss = 4.86039 (* 1 = 4.86039 loss)
I0405 14:43:17.225612 18799 sgd_solver.cpp:105] Iteration 12960, lr = 0.0001
I0405 14:43:22.704624 18799 solver.cpp:218] Iteration 12972 (2.19019 iter/s, 5.47897s/12 iters), loss = 4.79608
I0405 14:43:22.704665 18799 solver.cpp:237]     Train net output #0: loss = 4.79608 (* 1 = 4.79608 loss)
I0405 14:43:22.704670 18799 sgd_solver.cpp:105] Iteration 12972, lr = 0.0001
I0405 14:43:27.960573 18799 solver.cpp:218] Iteration 12984 (2.28317 iter/s, 5.25586s/12 iters), loss = 4.78088
I0405 14:43:27.960616 18799 solver.cpp:237]     Train net output #0: loss = 4.78088 (* 1 = 4.78088 loss)
I0405 14:43:27.960623 18799 sgd_solver.cpp:105] Iteration 12984, lr = 0.0001
I0405 14:43:33.280644 18799 solver.cpp:218] Iteration 12996 (2.25565 iter/s, 5.31998s/12 iters), loss = 4.73765
I0405 14:43:33.280699 18799 solver.cpp:237]     Train net output #0: loss = 4.73765 (* 1 = 4.73765 loss)
I0405 14:43:33.280706 18799 sgd_solver.cpp:105] Iteration 12996, lr = 0.0001
I0405 14:43:38.528062 18799 solver.cpp:218] Iteration 13008 (2.28688 iter/s, 5.24731s/12 iters), loss = 4.89636
I0405 14:43:38.528106 18799 solver.cpp:237]     Train net output #0: loss = 4.89636 (* 1 = 4.89636 loss)
I0405 14:43:38.528115 18799 sgd_solver.cpp:105] Iteration 13008, lr = 0.0001
I0405 14:43:43.637732 18799 solver.cpp:218] Iteration 13020 (2.34853 iter/s, 5.10958s/12 iters), loss = 4.79658
I0405 14:43:43.637874 18799 solver.cpp:237]     Train net output #0: loss = 4.79658 (* 1 = 4.79658 loss)
I0405 14:43:43.637883 18799 sgd_solver.cpp:105] Iteration 13020, lr = 0.0001
I0405 14:43:48.824928 18799 solver.cpp:218] Iteration 13032 (2.31347 iter/s, 5.18701s/12 iters), loss = 4.93093
I0405 14:43:48.824990 18799 solver.cpp:237]     Train net output #0: loss = 4.93093 (* 1 = 4.93093 loss)
I0405 14:43:48.824998 18799 sgd_solver.cpp:105] Iteration 13032, lr = 0.0001
I0405 14:43:54.228603 18799 solver.cpp:218] Iteration 13044 (2.22075 iter/s, 5.40357s/12 iters), loss = 4.84865
I0405 14:43:54.228646 18799 solver.cpp:237]     Train net output #0: loss = 4.84865 (* 1 = 4.84865 loss)
I0405 14:43:54.228650 18799 sgd_solver.cpp:105] Iteration 13044, lr = 0.0001
I0405 14:43:56.049434 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:59.057257 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13056.caffemodel
I0405 14:44:02.069618 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13056.solverstate
I0405 14:44:04.377804 18799 solver.cpp:330] Iteration 13056, Testing net (#0)
I0405 14:44:04.377826 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:44:08.342316 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:44:08.911671 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0330882
I0405 14:44:08.911705 18799 solver.cpp:397]     Test net output #1: loss = 4.91864 (* 1 = 4.91864 loss)
I0405 14:44:09.047188 18799 solver.cpp:218] Iteration 13056 (0.809802 iter/s, 14.8184s/12 iters), loss = 4.89211
I0405 14:44:09.047250 18799 solver.cpp:237]     Train net output #0: loss = 4.89211 (* 1 = 4.89211 loss)
I0405 14:44:09.047261 18799 sgd_solver.cpp:105] Iteration 13056, lr = 0.0001
I0405 14:44:13.184530 18799 solver.cpp:218] Iteration 13068 (2.90048 iter/s, 4.13725s/12 iters), loss = 4.77007
I0405 14:44:13.184572 18799 solver.cpp:237]     Train net output #0: loss = 4.77007 (* 1 = 4.77007 loss)
I0405 14:44:13.184579 18799 sgd_solver.cpp:105] Iteration 13068, lr = 0.0001
I0405 14:44:18.280740 18799 solver.cpp:218] Iteration 13080 (2.35473 iter/s, 5.09612s/12 iters), loss = 4.67825
I0405 14:44:18.280845 18799 solver.cpp:237]     Train net output #0: loss = 4.67825 (* 1 = 4.67825 loss)
I0405 14:44:18.280851 18799 sgd_solver.cpp:105] Iteration 13080, lr = 0.0001
I0405 14:44:23.350786 18799 solver.cpp:218] Iteration 13092 (2.36691 iter/s, 5.06989s/12 iters), loss = 4.74641
I0405 14:44:23.350828 18799 solver.cpp:237]     Train net output #0: loss = 4.74641 (* 1 = 4.74641 loss)
I0405 14:44:23.350833 18799 sgd_solver.cpp:105] Iteration 13092, lr = 0.0001
I0405 14:44:28.528494 18799 solver.cpp:218] Iteration 13104 (2.31767 iter/s, 5.17762s/12 iters), loss = 4.79356
I0405 14:44:28.528534 18799 solver.cpp:237]     Train net output #0: loss = 4.79356 (* 1 = 4.79356 loss)
I0405 14:44:28.528539 18799 sgd_solver.cpp:105] Iteration 13104, lr = 0.0001
I0405 14:44:33.570956 18799 solver.cpp:218] Iteration 13116 (2.37983 iter/s, 5.04238s/12 iters), loss = 4.97509
I0405 14:44:33.570998 18799 solver.cpp:237]     Train net output #0: loss = 4.97509 (* 1 = 4.97509 loss)
I0405 14:44:33.571004 18799 sgd_solver.cpp:105] Iteration 13116, lr = 0.0001
I0405 14:44:38.914769 18799 solver.cpp:218] Iteration 13128 (2.24562 iter/s, 5.34373s/12 iters), loss = 4.82446
I0405 14:44:38.914801 18799 solver.cpp:237]     Train net output #0: loss = 4.82446 (* 1 = 4.82446 loss)
I0405 14:44:38.914808 18799 sgd_solver.cpp:105] Iteration 13128, lr = 0.0001
I0405 14:44:44.303395 18799 solver.cpp:218] Iteration 13140 (2.22695 iter/s, 5.38854s/12 iters), loss = 4.81118
I0405 14:44:44.303454 18799 solver.cpp:237]     Train net output #0: loss = 4.81118 (* 1 = 4.81118 loss)
I0405 14:44:44.303463 18799 sgd_solver.cpp:105] Iteration 13140, lr = 0.0001
I0405 14:44:48.442981 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:44:49.708066 18799 solver.cpp:218] Iteration 13152 (2.22035 iter/s, 5.40456s/12 iters), loss = 4.8651
I0405 14:44:49.708107 18799 solver.cpp:237]     Train net output #0: loss = 4.8651 (* 1 = 4.8651 loss)
I0405 14:44:49.708113 18799 sgd_solver.cpp:105] Iteration 13152, lr = 0.0001
I0405 14:44:51.798051 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13158.caffemodel
I0405 14:44:55.064193 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13158.solverstate
I0405 14:44:57.872339 18799 solver.cpp:330] Iteration 13158, Testing net (#0)
I0405 14:44:57.872359 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:45:01.366756 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:45:01.592973 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:02.157032 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0373775
I0405 14:45:02.157064 18799 solver.cpp:397]     Test net output #1: loss = 4.91094 (* 1 = 4.91094 loss)
I0405 14:45:04.021065 18799 solver.cpp:218] Iteration 13164 (0.838407 iter/s, 14.3129s/12 iters), loss = 4.90212
I0405 14:45:04.021109 18799 solver.cpp:237]     Train net output #0: loss = 4.90212 (* 1 = 4.90212 loss)
I0405 14:45:04.021116 18799 sgd_solver.cpp:105] Iteration 13164, lr = 0.0001
I0405 14:45:09.438731 18799 solver.cpp:218] Iteration 13176 (2.21501 iter/s, 5.41758s/12 iters), loss = 4.7841
I0405 14:45:09.438774 18799 solver.cpp:237]     Train net output #0: loss = 4.7841 (* 1 = 4.7841 loss)
I0405 14:45:09.438779 18799 sgd_solver.cpp:105] Iteration 13176, lr = 0.0001
I0405 14:45:14.788487 18799 solver.cpp:218] Iteration 13188 (2.24313 iter/s, 5.34967s/12 iters), loss = 4.71994
I0405 14:45:14.788528 18799 solver.cpp:237]     Train net output #0: loss = 4.71994 (* 1 = 4.71994 loss)
I0405 14:45:14.788534 18799 sgd_solver.cpp:105] Iteration 13188, lr = 0.0001
I0405 14:45:20.375387 18799 solver.cpp:218] Iteration 13200 (2.14792 iter/s, 5.5868s/12 iters), loss = 4.90276
I0405 14:45:20.375509 18799 solver.cpp:237]     Train net output #0: loss = 4.90276 (* 1 = 4.90276 loss)
I0405 14:45:20.375519 18799 sgd_solver.cpp:105] Iteration 13200, lr = 0.0001
I0405 14:45:25.447160 18799 solver.cpp:218] Iteration 13212 (2.36611 iter/s, 5.07161s/12 iters), loss = 4.63833
I0405 14:45:25.447197 18799 solver.cpp:237]     Train net output #0: loss = 4.63833 (* 1 = 4.63833 loss)
I0405 14:45:25.447203 18799 sgd_solver.cpp:105] Iteration 13212, lr = 0.0001
I0405 14:45:30.902879 18799 solver.cpp:218] Iteration 13224 (2.19956 iter/s, 5.45563s/12 iters), loss = 4.80643
I0405 14:45:30.902930 18799 solver.cpp:237]     Train net output #0: loss = 4.80643 (* 1 = 4.80643 loss)
I0405 14:45:30.902938 18799 sgd_solver.cpp:105] Iteration 13224, lr = 0.0001
I0405 14:45:36.391204 18799 solver.cpp:218] Iteration 13236 (2.1865 iter/s, 5.48823s/12 iters), loss = 4.76635
I0405 14:45:36.391245 18799 solver.cpp:237]     Train net output #0: loss = 4.76635 (* 1 = 4.76635 loss)
I0405 14:45:36.391252 18799 sgd_solver.cpp:105] Iteration 13236, lr = 0.0001
I0405 14:45:41.684495 18799 solver.cpp:218] Iteration 13248 (2.26706 iter/s, 5.2932s/12 iters), loss = 4.98137
I0405 14:45:41.684545 18799 solver.cpp:237]     Train net output #0: loss = 4.98137 (* 1 = 4.98137 loss)
I0405 14:45:41.684556 18799 sgd_solver.cpp:105] Iteration 13248, lr = 0.0001
I0405 14:45:42.738034 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:46.562757 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13260.caffemodel
I0405 14:45:49.589524 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13260.solverstate
I0405 14:45:51.886631 18799 solver.cpp:330] Iteration 13260, Testing net (#0)
I0405 14:45:51.886721 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:45:55.684084 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:56.283674 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:45:56.283715 18799 solver.cpp:397]     Test net output #1: loss = 4.91115 (* 1 = 4.91115 loss)
I0405 14:45:56.421269 18799 solver.cpp:218] Iteration 13260 (0.814297 iter/s, 14.7366s/12 iters), loss = 4.76556
I0405 14:45:56.421321 18799 solver.cpp:237]     Train net output #0: loss = 4.76556 (* 1 = 4.76556 loss)
I0405 14:45:56.421329 18799 sgd_solver.cpp:105] Iteration 13260, lr = 0.0001
I0405 14:46:00.749162 18799 solver.cpp:218] Iteration 13272 (2.77277 iter/s, 4.3278s/12 iters), loss = 4.97067
I0405 14:46:00.749217 18799 solver.cpp:237]     Train net output #0: loss = 4.97067 (* 1 = 4.97067 loss)
I0405 14:46:00.749225 18799 sgd_solver.cpp:105] Iteration 13272, lr = 0.0001
I0405 14:46:06.030061 18799 solver.cpp:218] Iteration 13284 (2.27238 iter/s, 5.2808s/12 iters), loss = 4.90628
I0405 14:46:06.030109 18799 solver.cpp:237]     Train net output #0: loss = 4.90628 (* 1 = 4.90628 loss)
I0405 14:46:06.030117 18799 sgd_solver.cpp:105] Iteration 13284, lr = 0.0001
I0405 14:46:10.993726 18799 solver.cpp:218] Iteration 13296 (2.41761 iter/s, 4.96358s/12 iters), loss = 4.91972
I0405 14:46:10.993767 18799 solver.cpp:237]     Train net output #0: loss = 4.91972 (* 1 = 4.91972 loss)
I0405 14:46:10.993774 18799 sgd_solver.cpp:105] Iteration 13296, lr = 0.0001
I0405 14:46:16.303063 18799 solver.cpp:218] Iteration 13308 (2.26021 iter/s, 5.30925s/12 iters), loss = 4.87001
I0405 14:46:16.303104 18799 solver.cpp:237]     Train net output #0: loss = 4.87001 (* 1 = 4.87001 loss)
I0405 14:46:16.303110 18799 sgd_solver.cpp:105] Iteration 13308, lr = 0.0001
I0405 14:46:21.690248 18799 solver.cpp:218] Iteration 13320 (2.22754 iter/s, 5.3871s/12 iters), loss = 4.8221
I0405 14:46:21.690286 18799 solver.cpp:237]     Train net output #0: loss = 4.8221 (* 1 = 4.8221 loss)
I0405 14:46:21.690291 18799 sgd_solver.cpp:105] Iteration 13320, lr = 0.0001
I0405 14:46:26.887053 18799 solver.cpp:218] Iteration 13332 (2.30915 iter/s, 5.19672s/12 iters), loss = 4.9189
I0405 14:46:26.887135 18799 solver.cpp:237]     Train net output #0: loss = 4.9189 (* 1 = 4.9189 loss)
I0405 14:46:26.887141 18799 sgd_solver.cpp:105] Iteration 13332, lr = 0.0001
I0405 14:46:32.134837 18799 solver.cpp:218] Iteration 13344 (2.28674 iter/s, 5.24766s/12 iters), loss = 4.79636
I0405 14:46:32.134881 18799 solver.cpp:237]     Train net output #0: loss = 4.79636 (* 1 = 4.79636 loss)
I0405 14:46:32.134886 18799 sgd_solver.cpp:105] Iteration 13344, lr = 0.0001
I0405 14:46:35.466763 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:46:37.548264 18799 solver.cpp:218] Iteration 13356 (2.21675 iter/s, 5.41333s/12 iters), loss = 4.75523
I0405 14:46:37.548311 18799 solver.cpp:237]     Train net output #0: loss = 4.75523 (* 1 = 4.75523 loss)
I0405 14:46:37.548319 18799 sgd_solver.cpp:105] Iteration 13356, lr = 0.0001
I0405 14:46:39.516733 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13362.caffemodel
I0405 14:46:42.553262 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13362.solverstate
I0405 14:46:44.935442 18799 solver.cpp:330] Iteration 13362, Testing net (#0)
I0405 14:46:44.935463 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:46:48.596715 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:46:49.245905 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0349265
I0405 14:46:49.245944 18799 solver.cpp:397]     Test net output #1: loss = 4.90263 (* 1 = 4.90263 loss)
I0405 14:46:51.091104 18799 solver.cpp:218] Iteration 13368 (0.886086 iter/s, 13.5427s/12 iters), loss = 4.79197
I0405 14:46:51.091145 18799 solver.cpp:237]     Train net output #0: loss = 4.79197 (* 1 = 4.79197 loss)
I0405 14:46:51.091150 18799 sgd_solver.cpp:105] Iteration 13368, lr = 0.0001
I0405 14:46:56.544562 18799 solver.cpp:218] Iteration 13380 (2.20048 iter/s, 5.45337s/12 iters), loss = 4.83933
I0405 14:46:56.544607 18799 solver.cpp:237]     Train net output #0: loss = 4.83933 (* 1 = 4.83933 loss)
I0405 14:46:56.544613 18799 sgd_solver.cpp:105] Iteration 13380, lr = 0.0001
I0405 14:47:01.789880 18799 solver.cpp:218] Iteration 13392 (2.28779 iter/s, 5.24523s/12 iters), loss = 4.82567
I0405 14:47:01.789999 18799 solver.cpp:237]     Train net output #0: loss = 4.82567 (* 1 = 4.82567 loss)
I0405 14:47:01.790005 18799 sgd_solver.cpp:105] Iteration 13392, lr = 0.0001
I0405 14:47:06.800413 18799 solver.cpp:218] Iteration 13404 (2.39503 iter/s, 5.01037s/12 iters), loss = 4.97508
I0405 14:47:06.800453 18799 solver.cpp:237]     Train net output #0: loss = 4.97508 (* 1 = 4.97508 loss)
I0405 14:47:06.800459 18799 sgd_solver.cpp:105] Iteration 13404, lr = 0.0001
I0405 14:47:12.128787 18799 solver.cpp:218] Iteration 13416 (2.25213 iter/s, 5.32829s/12 iters), loss = 4.79523
I0405 14:47:12.128827 18799 solver.cpp:237]     Train net output #0: loss = 4.79523 (* 1 = 4.79523 loss)
I0405 14:47:12.128834 18799 sgd_solver.cpp:105] Iteration 13416, lr = 0.0001
I0405 14:47:17.655025 18799 solver.cpp:218] Iteration 13428 (2.1715 iter/s, 5.52615s/12 iters), loss = 4.88982
I0405 14:47:17.655073 18799 solver.cpp:237]     Train net output #0: loss = 4.88982 (* 1 = 4.88982 loss)
I0405 14:47:17.655081 18799 sgd_solver.cpp:105] Iteration 13428, lr = 0.0001
I0405 14:47:22.857029 18799 solver.cpp:218] Iteration 13440 (2.30684 iter/s, 5.20191s/12 iters), loss = 4.89164
I0405 14:47:22.857074 18799 solver.cpp:237]     Train net output #0: loss = 4.89164 (* 1 = 4.89164 loss)
I0405 14:47:22.857081 18799 sgd_solver.cpp:105] Iteration 13440, lr = 0.0001
I0405 14:47:28.108459 18799 solver.cpp:218] Iteration 13452 (2.28513 iter/s, 5.25134s/12 iters), loss = 4.80955
I0405 14:47:28.108498 18799 solver.cpp:237]     Train net output #0: loss = 4.80955 (* 1 = 4.80955 loss)
I0405 14:47:28.108503 18799 sgd_solver.cpp:105] Iteration 13452, lr = 0.0001
I0405 14:47:28.352470 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:47:32.799000 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13464.caffemodel
I0405 14:47:35.764961 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13464.solverstate
I0405 14:47:38.081776 18799 solver.cpp:330] Iteration 13464, Testing net (#0)
I0405 14:47:38.081797 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:47:41.930285 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:47:42.614375 18799 solver.cpp:397]     Test net output #0: accuracy = 0.036152
I0405 14:47:42.614408 18799 solver.cpp:397]     Test net output #1: loss = 4.90268 (* 1 = 4.90268 loss)
I0405 14:47:42.756187 18799 solver.cpp:218] Iteration 13464 (0.819247 iter/s, 14.6476s/12 iters), loss = 4.85736
I0405 14:47:42.756251 18799 solver.cpp:237]     Train net output #0: loss = 4.85736 (* 1 = 4.85736 loss)
I0405 14:47:42.756261 18799 sgd_solver.cpp:105] Iteration 13464, lr = 0.0001
I0405 14:47:47.020013 18799 solver.cpp:218] Iteration 13476 (2.81445 iter/s, 4.26372s/12 iters), loss = 4.91831
I0405 14:47:47.020073 18799 solver.cpp:237]     Train net output #0: loss = 4.91831 (* 1 = 4.91831 loss)
I0405 14:47:47.020083 18799 sgd_solver.cpp:105] Iteration 13476, lr = 0.0001
I0405 14:47:52.387794 18799 solver.cpp:218] Iteration 13488 (2.2356 iter/s, 5.36768s/12 iters), loss = 4.76188
I0405 14:47:52.387831 18799 solver.cpp:237]     Train net output #0: loss = 4.76188 (* 1 = 4.76188 loss)
I0405 14:47:52.387836 18799 sgd_solver.cpp:105] Iteration 13488, lr = 0.0001
I0405 14:47:57.770027 18799 solver.cpp:218] Iteration 13500 (2.22959 iter/s, 5.38215s/12 iters), loss = 4.98385
I0405 14:47:57.770074 18799 solver.cpp:237]     Train net output #0: loss = 4.98385 (* 1 = 4.98385 loss)
I0405 14:47:57.770081 18799 sgd_solver.cpp:105] Iteration 13500, lr = 0.0001
I0405 14:48:03.052772 18799 solver.cpp:218] Iteration 13512 (2.27159 iter/s, 5.28265s/12 iters), loss = 4.76353
I0405 14:48:03.052909 18799 solver.cpp:237]     Train net output #0: loss = 4.76353 (* 1 = 4.76353 loss)
I0405 14:48:03.052917 18799 sgd_solver.cpp:105] Iteration 13512, lr = 0.0001
I0405 14:48:08.350854 18799 solver.cpp:218] Iteration 13524 (2.26505 iter/s, 5.2979s/12 iters), loss = 4.79444
I0405 14:48:08.350901 18799 solver.cpp:237]     Train net output #0: loss = 4.79444 (* 1 = 4.79444 loss)
I0405 14:48:08.350908 18799 sgd_solver.cpp:105] Iteration 13524, lr = 0.0001
I0405 14:48:13.575320 18799 solver.cpp:218] Iteration 13536 (2.29692 iter/s, 5.22438s/12 iters), loss = 4.83262
I0405 14:48:13.575357 18799 solver.cpp:237]     Train net output #0: loss = 4.83262 (* 1 = 4.83262 loss)
I0405 14:48:13.575363 18799 sgd_solver.cpp:105] Iteration 13536, lr = 0.0001
I0405 14:48:18.932672 18799 solver.cpp:218] Iteration 13548 (2.23995 iter/s, 5.35726s/12 iters), loss = 4.8475
I0405 14:48:18.932713 18799 solver.cpp:237]     Train net output #0: loss = 4.8475 (* 1 = 4.8475 loss)
I0405 14:48:18.932718 18799 sgd_solver.cpp:105] Iteration 13548, lr = 0.0001
I0405 14:48:21.622073 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:48:24.490404 18799 solver.cpp:218] Iteration 13560 (2.15919 iter/s, 5.55764s/12 iters), loss = 4.82761
I0405 14:48:24.490459 18799 solver.cpp:237]     Train net output #0: loss = 4.82761 (* 1 = 4.82761 loss)
I0405 14:48:24.490468 18799 sgd_solver.cpp:105] Iteration 13560, lr = 0.0001
I0405 14:48:26.638021 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13566.caffemodel
I0405 14:48:29.649646 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13566.solverstate
I0405 14:48:31.956751 18799 solver.cpp:330] Iteration 13566, Testing net (#0)
I0405 14:48:31.956773 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:48:35.869642 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:48:36.599205 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0373775
I0405 14:48:36.599234 18799 solver.cpp:397]     Test net output #1: loss = 4.89939 (* 1 = 4.89939 loss)
I0405 14:48:38.518868 18799 solver.cpp:218] Iteration 13572 (0.855413 iter/s, 14.0283s/12 iters), loss = 4.79957
I0405 14:48:38.518909 18799 solver.cpp:237]     Train net output #0: loss = 4.79957 (* 1 = 4.79957 loss)
I0405 14:48:38.518914 18799 sgd_solver.cpp:105] Iteration 13572, lr = 0.0001
I0405 14:48:43.834033 18799 solver.cpp:218] Iteration 13584 (2.25773 iter/s, 5.31507s/12 iters), loss = 4.86805
I0405 14:48:43.834092 18799 solver.cpp:237]     Train net output #0: loss = 4.86805 (* 1 = 4.86805 loss)
I0405 14:48:43.834101 18799 sgd_solver.cpp:105] Iteration 13584, lr = 0.0001
I0405 14:48:49.109342 18799 solver.cpp:218] Iteration 13596 (2.27479 iter/s, 5.27521s/12 iters), loss = 4.79914
I0405 14:48:49.109382 18799 solver.cpp:237]     Train net output #0: loss = 4.79914 (* 1 = 4.79914 loss)
I0405 14:48:49.109388 18799 sgd_solver.cpp:105] Iteration 13596, lr = 0.0001
I0405 14:48:54.272401 18799 solver.cpp:218] Iteration 13608 (2.32424 iter/s, 5.16297s/12 iters), loss = 4.7825
I0405 14:48:54.272457 18799 solver.cpp:237]     Train net output #0: loss = 4.7825 (* 1 = 4.7825 loss)
I0405 14:48:54.272465 18799 sgd_solver.cpp:105] Iteration 13608, lr = 0.0001
I0405 14:48:59.660195 18799 solver.cpp:218] Iteration 13620 (2.2273 iter/s, 5.38769s/12 iters), loss = 4.7804
I0405 14:48:59.660249 18799 solver.cpp:237]     Train net output #0: loss = 4.7804 (* 1 = 4.7804 loss)
I0405 14:48:59.660259 18799 sgd_solver.cpp:105] Iteration 13620, lr = 0.0001
I0405 14:49:04.943169 18799 solver.cpp:218] Iteration 13632 (2.27149 iter/s, 5.28288s/12 iters), loss = 4.78891
I0405 14:49:04.943222 18799 solver.cpp:237]     Train net output #0: loss = 4.78891 (* 1 = 4.78891 loss)
I0405 14:49:04.943228 18799 sgd_solver.cpp:105] Iteration 13632, lr = 0.0001
I0405 14:49:10.251098 18799 solver.cpp:218] Iteration 13644 (2.26081 iter/s, 5.30783s/12 iters), loss = 4.75935
I0405 14:49:10.251217 18799 solver.cpp:237]     Train net output #0: loss = 4.75935 (* 1 = 4.75935 loss)
I0405 14:49:10.251224 18799 sgd_solver.cpp:105] Iteration 13644, lr = 0.0001
I0405 14:49:15.055086 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:49:15.477699 18799 solver.cpp:218] Iteration 13656 (2.29602 iter/s, 5.22644s/12 iters), loss = 4.85595
I0405 14:49:15.477741 18799 solver.cpp:237]     Train net output #0: loss = 4.85595 (* 1 = 4.85595 loss)
I0405 14:49:15.477746 18799 sgd_solver.cpp:105] Iteration 13656, lr = 0.0001
I0405 14:49:20.362766 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13668.caffemodel
I0405 14:49:23.450139 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13668.solverstate
I0405 14:49:25.777556 18799 solver.cpp:330] Iteration 13668, Testing net (#0)
I0405 14:49:25.777581 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:49:29.317503 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:49:30.073483 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0355392
I0405 14:49:30.073518 18799 solver.cpp:397]     Test net output #1: loss = 4.89774 (* 1 = 4.89774 loss)
I0405 14:49:30.203363 18799 solver.cpp:218] Iteration 13668 (0.814912 iter/s, 14.7255s/12 iters), loss = 4.81307
I0405 14:49:30.203413 18799 solver.cpp:237]     Train net output #0: loss = 4.81307 (* 1 = 4.81307 loss)
I0405 14:49:30.203421 18799 sgd_solver.cpp:105] Iteration 13668, lr = 0.0001
I0405 14:49:34.326282 18799 solver.cpp:218] Iteration 13680 (2.91062 iter/s, 4.12283s/12 iters), loss = 4.71291
I0405 14:49:34.326331 18799 solver.cpp:237]     Train net output #0: loss = 4.71291 (* 1 = 4.71291 loss)
I0405 14:49:34.326339 18799 sgd_solver.cpp:105] Iteration 13680, lr = 0.0001
I0405 14:49:39.678207 18799 solver.cpp:218] Iteration 13692 (2.24222 iter/s, 5.35183s/12 iters), loss = 4.87802
I0405 14:49:39.678252 18799 solver.cpp:237]     Train net output #0: loss = 4.87802 (* 1 = 4.87802 loss)
I0405 14:49:39.678257 18799 sgd_solver.cpp:105] Iteration 13692, lr = 0.0001
I0405 14:49:44.808430 18799 solver.cpp:218] Iteration 13704 (2.33912 iter/s, 5.13013s/12 iters), loss = 4.69403
I0405 14:49:44.808539 18799 solver.cpp:237]     Train net output #0: loss = 4.69403 (* 1 = 4.69403 loss)
I0405 14:49:44.808547 18799 sgd_solver.cpp:105] Iteration 13704, lr = 0.0001
I0405 14:49:50.269587 18799 solver.cpp:218] Iteration 13716 (2.1974 iter/s, 5.461s/12 iters), loss = 4.89781
I0405 14:49:50.269634 18799 solver.cpp:237]     Train net output #0: loss = 4.89781 (* 1 = 4.89781 loss)
I0405 14:49:50.269640 18799 sgd_solver.cpp:105] Iteration 13716, lr = 0.0001
I0405 14:49:55.601128 18799 solver.cpp:218] Iteration 13728 (2.2508 iter/s, 5.33144s/12 iters), loss = 4.71499
I0405 14:49:55.601195 18799 solver.cpp:237]     Train net output #0: loss = 4.71499 (* 1 = 4.71499 loss)
I0405 14:49:55.601204 18799 sgd_solver.cpp:105] Iteration 13728, lr = 0.0001
I0405 14:50:00.979300 18799 solver.cpp:218] Iteration 13740 (2.23129 iter/s, 5.37806s/12 iters), loss = 4.86699
I0405 14:50:00.979347 18799 solver.cpp:237]     Train net output #0: loss = 4.86699 (* 1 = 4.86699 loss)
I0405 14:50:00.979352 18799 sgd_solver.cpp:105] Iteration 13740, lr = 0.0001
I0405 14:50:06.255270 18799 solver.cpp:218] Iteration 13752 (2.2745 iter/s, 5.27588s/12 iters), loss = 4.77665
I0405 14:50:06.255309 18799 solver.cpp:237]     Train net output #0: loss = 4.77665 (* 1 = 4.77665 loss)
I0405 14:50:06.255316 18799 sgd_solver.cpp:105] Iteration 13752, lr = 0.0001
I0405 14:50:08.123010 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:50:11.616681 18799 solver.cpp:218] Iteration 13764 (2.23825 iter/s, 5.36132s/12 iters), loss = 4.85872
I0405 14:50:11.616726 18799 solver.cpp:237]     Train net output #0: loss = 4.85872 (* 1 = 4.85872 loss)
I0405 14:50:11.616732 18799 sgd_solver.cpp:105] Iteration 13764, lr = 0.0001
I0405 14:50:13.874090 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13770.caffemodel
I0405 14:50:16.845517 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13770.solverstate
I0405 14:50:19.160423 18799 solver.cpp:330] Iteration 13770, Testing net (#0)
I0405 14:50:19.160441 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:50:22.847695 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:50:23.635406 18799 solver.cpp:397]     Test net output #0: accuracy = 0.036152
I0405 14:50:23.635442 18799 solver.cpp:397]     Test net output #1: loss = 4.89486 (* 1 = 4.89486 loss)
I0405 14:50:25.625708 18799 solver.cpp:218] Iteration 13776 (0.856599 iter/s, 14.0089s/12 iters), loss = 4.92102
I0405 14:50:25.625771 18799 solver.cpp:237]     Train net output #0: loss = 4.92102 (* 1 = 4.92102 loss)
I0405 14:50:25.625779 18799 sgd_solver.cpp:105] Iteration 13776, lr = 0.0001
I0405 14:50:30.998711 18799 solver.cpp:218] Iteration 13788 (2.23343 iter/s, 5.3729s/12 iters), loss = 4.74033
I0405 14:50:30.998752 18799 solver.cpp:237]     Train net output #0: loss = 4.74033 (* 1 = 4.74033 loss)
I0405 14:50:30.998759 18799 sgd_solver.cpp:105] Iteration 13788, lr = 0.0001
I0405 14:50:36.219467 18799 solver.cpp:218] Iteration 13800 (2.29856 iter/s, 5.22067s/12 iters), loss = 4.75759
I0405 14:50:36.219523 18799 solver.cpp:237]     Train net output #0: loss = 4.75759 (* 1 = 4.75759 loss)
I0405 14:50:36.219532 18799 sgd_solver.cpp:105] Iteration 13800, lr = 0.0001
I0405 14:50:41.526955 18799 solver.cpp:218] Iteration 13812 (2.261 iter/s, 5.30739s/12 iters), loss = 4.69031
I0405 14:50:41.527000 18799 solver.cpp:237]     Train net output #0: loss = 4.69031 (* 1 = 4.69031 loss)
I0405 14:50:41.527006 18799 sgd_solver.cpp:105] Iteration 13812, lr = 0.0001
I0405 14:50:46.841665 18799 solver.cpp:218] Iteration 13824 (2.25792 iter/s, 5.31462s/12 iters), loss = 4.86969
I0405 14:50:46.841706 18799 solver.cpp:237]     Train net output #0: loss = 4.86969 (* 1 = 4.86969 loss)
I0405 14:50:46.841711 18799 sgd_solver.cpp:105] Iteration 13824, lr = 0.0001
I0405 14:50:52.144788 18799 solver.cpp:218] Iteration 13836 (2.26286 iter/s, 5.30303s/12 iters), loss = 4.81945
I0405 14:50:52.144891 18799 solver.cpp:237]     Train net output #0: loss = 4.81945 (* 1 = 4.81945 loss)
I0405 14:50:52.144898 18799 sgd_solver.cpp:105] Iteration 13836, lr = 0.0001
I0405 14:50:57.393983 18799 solver.cpp:218] Iteration 13848 (2.28613 iter/s, 5.24905s/12 iters), loss = 4.75563
I0405 14:50:57.394039 18799 solver.cpp:237]     Train net output #0: loss = 4.75563 (* 1 = 4.75563 loss)
I0405 14:50:57.394047 18799 sgd_solver.cpp:105] Iteration 13848, lr = 0.0001
I0405 14:51:01.612352 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:02.837548 18799 solver.cpp:218] Iteration 13860 (2.20448 iter/s, 5.44346s/12 iters), loss = 4.88347
I0405 14:51:02.837592 18799 solver.cpp:237]     Train net output #0: loss = 4.88347 (* 1 = 4.88347 loss)
I0405 14:51:02.837597 18799 sgd_solver.cpp:105] Iteration 13860, lr = 0.0001
I0405 14:51:07.641556 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13872.caffemodel
I0405 14:51:10.688091 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13872.solverstate
I0405 14:51:12.989768 18799 solver.cpp:330] Iteration 13872, Testing net (#0)
I0405 14:51:12.989789 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:51:13.961251 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:51:16.610515 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:17.473050 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:51:17.473085 18799 solver.cpp:397]     Test net output #1: loss = 4.8857 (* 1 = 4.8857 loss)
I0405 14:51:17.615401 18799 solver.cpp:218] Iteration 13872 (0.812034 iter/s, 14.7777s/12 iters), loss = 4.83021
I0405 14:51:17.615478 18799 solver.cpp:237]     Train net output #0: loss = 4.83021 (* 1 = 4.83021 loss)
I0405 14:51:17.615487 18799 sgd_solver.cpp:105] Iteration 13872, lr = 0.0001
I0405 14:51:22.023805 18799 solver.cpp:218] Iteration 13884 (2.72215 iter/s, 4.40828s/12 iters), loss = 4.83845
I0405 14:51:22.023847 18799 solver.cpp:237]     Train net output #0: loss = 4.83845 (* 1 = 4.83845 loss)
I0405 14:51:22.023854 18799 sgd_solver.cpp:105] Iteration 13884, lr = 0.0001
I0405 14:51:27.130084 18799 solver.cpp:218] Iteration 13896 (2.35009 iter/s, 5.10618s/12 iters), loss = 4.76313
I0405 14:51:27.130239 18799 solver.cpp:237]     Train net output #0: loss = 4.76313 (* 1 = 4.76313 loss)
I0405 14:51:27.130249 18799 sgd_solver.cpp:105] Iteration 13896, lr = 0.0001
I0405 14:51:32.334218 18799 solver.cpp:218] Iteration 13908 (2.30595 iter/s, 5.20394s/12 iters), loss = 4.83882
I0405 14:51:32.334268 18799 solver.cpp:237]     Train net output #0: loss = 4.83882 (* 1 = 4.83882 loss)
I0405 14:51:32.334276 18799 sgd_solver.cpp:105] Iteration 13908, lr = 0.0001
I0405 14:51:37.759429 18799 solver.cpp:218] Iteration 13920 (2.21193 iter/s, 5.42512s/12 iters), loss = 4.6133
I0405 14:51:37.759471 18799 solver.cpp:237]     Train net output #0: loss = 4.6133 (* 1 = 4.6133 loss)
I0405 14:51:37.759476 18799 sgd_solver.cpp:105] Iteration 13920, lr = 0.0001
I0405 14:51:43.134660 18799 solver.cpp:218] Iteration 13932 (2.2325 iter/s, 5.37514s/12 iters), loss = 4.81219
I0405 14:51:43.134701 18799 solver.cpp:237]     Train net output #0: loss = 4.81219 (* 1 = 4.81219 loss)
I0405 14:51:43.134706 18799 sgd_solver.cpp:105] Iteration 13932, lr = 0.0001
I0405 14:51:48.308480 18799 solver.cpp:218] Iteration 13944 (2.31941 iter/s, 5.17373s/12 iters), loss = 4.72114
I0405 14:51:48.308526 18799 solver.cpp:237]     Train net output #0: loss = 4.72114 (* 1 = 4.72114 loss)
I0405 14:51:48.308531 18799 sgd_solver.cpp:105] Iteration 13944, lr = 0.0001
I0405 14:51:53.316049 18799 solver.cpp:218] Iteration 13956 (2.39642 iter/s, 5.00748s/12 iters), loss = 4.87075
I0405 14:51:53.316093 18799 solver.cpp:237]     Train net output #0: loss = 4.87075 (* 1 = 4.87075 loss)
I0405 14:51:53.316099 18799 sgd_solver.cpp:105] Iteration 13956, lr = 0.0001
I0405 14:51:54.407650 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:58.698977 18799 solver.cpp:218] Iteration 13968 (2.22931 iter/s, 5.38284s/12 iters), loss = 4.79323
I0405 14:51:58.699079 18799 solver.cpp:237]     Train net output #0: loss = 4.79323 (* 1 = 4.79323 loss)
I0405 14:51:58.699086 18799 sgd_solver.cpp:105] Iteration 13968, lr = 0.0001
I0405 14:52:00.880481 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13974.caffemodel
I0405 14:52:03.871639 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13974.solverstate
I0405 14:52:06.189077 18799 solver.cpp:330] Iteration 13974, Testing net (#0)
I0405 14:52:06.189097 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:52:09.772981 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:52:10.640254 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:52:10.640288 18799 solver.cpp:397]     Test net output #1: loss = 4.88307 (* 1 = 4.88307 loss)
I0405 14:52:12.589907 18799 solver.cpp:218] Iteration 13980 (0.863885 iter/s, 13.8907s/12 iters), loss = 4.94607
I0405 14:52:12.589951 18799 solver.cpp:237]     Train net output #0: loss = 4.94607 (* 1 = 4.94607 loss)
I0405 14:52:12.589956 18799 sgd_solver.cpp:105] Iteration 13980, lr = 0.0001
I0405 14:52:17.922608 18799 solver.cpp:218] Iteration 13992 (2.25031 iter/s, 5.33261s/12 iters), loss = 4.83255
I0405 14:52:17.922654 18799 solver.cpp:237]     Train net output #0: loss = 4.83255 (* 1 = 4.83255 loss)
I0405 14:52:17.922662 18799 sgd_solver.cpp:105] Iteration 13992, lr = 0.0001
I0405 14:52:23.036959 18799 solver.cpp:218] Iteration 14004 (2.34638 iter/s, 5.11427s/12 iters), loss = 4.83328
I0405 14:52:23.036996 18799 solver.cpp:237]     Train net output #0: loss = 4.83328 (* 1 = 4.83328 loss)
I0405 14:52:23.037003 18799 sgd_solver.cpp:105] Iteration 14004, lr = 0.0001
I0405 14:52:28.200065 18799 solver.cpp:218] Iteration 14016 (2.32422 iter/s, 5.16302s/12 iters), loss = 4.85695
I0405 14:52:28.200117 18799 solver.cpp:237]     Train net output #0: loss = 4.85695 (* 1 = 4.85695 loss)
I0405 14:52:28.200125 18799 sgd_solver.cpp:105] Iteration 14016, lr = 0.0001
I0405 14:52:33.217567 18799 solver.cpp:218] Iteration 14028 (2.39167 iter/s, 5.01741s/12 iters), loss = 4.76558
I0405 14:52:33.217691 18799 solver.cpp:237]     Train net output #0: loss = 4.76558 (* 1 = 4.76558 loss)
I0405 14:52:33.217698 18799 sgd_solver.cpp:105] Iteration 14028, lr = 0.0001
I0405 14:52:38.776255 18799 solver.cpp:218] Iteration 14040 (2.15885 iter/s, 5.55851s/12 iters), loss = 4.80474
I0405 14:52:38.776304 18799 solver.cpp:237]     Train net output #0: loss = 4.80474 (* 1 = 4.80474 loss)
I0405 14:52:38.776311 18799 sgd_solver.cpp:105] Iteration 14040, lr = 0.0001
I0405 14:52:44.225637 18799 solver.cpp:218] Iteration 14052 (2.20212 iter/s, 5.44928s/12 iters), loss = 4.76671
I0405 14:52:44.225695 18799 solver.cpp:237]     Train net output #0: loss = 4.76671 (* 1 = 4.76671 loss)
I0405 14:52:44.225704 18799 sgd_solver.cpp:105] Iteration 14052, lr = 0.0001
I0405 14:52:47.593086 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:52:49.627552 18799 solver.cpp:218] Iteration 14064 (2.22148 iter/s, 5.40181s/12 iters), loss = 4.66449
I0405 14:52:49.627606 18799 solver.cpp:237]     Train net output #0: loss = 4.66449 (* 1 = 4.66449 loss)
I0405 14:52:49.627615 18799 sgd_solver.cpp:105] Iteration 14064, lr = 0.0001
I0405 14:52:54.193629 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14076.caffemodel
I0405 14:52:57.212174 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14076.solverstate
I0405 14:52:59.527380 18799 solver.cpp:330] Iteration 14076, Testing net (#0)
I0405 14:52:59.527405 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:53:02.954721 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:53:03.878917 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:53:03.879036 18799 solver.cpp:397]     Test net output #1: loss = 4.88147 (* 1 = 4.88147 loss)
I0405 14:53:04.020912 18799 solver.cpp:218] Iteration 14076 (0.833726 iter/s, 14.3932s/12 iters), loss = 4.80927
I0405 14:53:04.020953 18799 solver.cpp:237]     Train net output #0: loss = 4.80927 (* 1 = 4.80927 loss)
I0405 14:53:04.020958 18799 sgd_solver.cpp:105] Iteration 14076, lr = 0.0001
I0405 14:53:08.320456 18799 solver.cpp:218] Iteration 14088 (2.79105 iter/s, 4.29946s/12 iters), loss = 4.83082
I0405 14:53:08.320497 18799 solver.cpp:237]     Train net output #0: loss = 4.83082 (* 1 = 4.83082 loss)
I0405 14:53:08.320502 18799 sgd_solver.cpp:105] Iteration 14088, lr = 0.0001
I0405 14:53:13.691668 18799 solver.cpp:218] Iteration 14100 (2.23417 iter/s, 5.37113s/12 iters), loss = 4.81744
I0405 14:53:13.691705 18799 solver.cpp:237]     Train net output #0: loss = 4.81744 (* 1 = 4.81744 loss)
I0405 14:53:13.691711 18799 sgd_solver.cpp:105] Iteration 14100, lr = 0.0001
I0405 14:53:18.721426 18799 solver.cpp:218] Iteration 14112 (2.38584 iter/s, 5.02968s/12 iters), loss = 4.90553
I0405 14:53:18.721468 18799 solver.cpp:237]     Train net output #0: loss = 4.90553 (* 1 = 4.90553 loss)
I0405 14:53:18.721475 18799 sgd_solver.cpp:105] Iteration 14112, lr = 0.0001
I0405 14:53:24.094803 18799 solver.cpp:218] Iteration 14124 (2.23327 iter/s, 5.37329s/12 iters), loss = 4.80407
I0405 14:53:24.094861 18799 solver.cpp:237]     Train net output #0: loss = 4.80407 (* 1 = 4.80407 loss)
I0405 14:53:24.094871 18799 sgd_solver.cpp:105] Iteration 14124, lr = 0.0001
I0405 14:53:29.317003 18799 solver.cpp:218] Iteration 14136 (2.29793 iter/s, 5.2221s/12 iters), loss = 4.82857
I0405 14:53:29.317045 18799 solver.cpp:237]     Train net output #0: loss = 4.82857 (* 1 = 4.82857 loss)
I0405 14:53:29.317051 18799 sgd_solver.cpp:105] Iteration 14136, lr = 0.0001
I0405 14:53:34.476840 18799 solver.cpp:218] Iteration 14148 (2.3257 iter/s, 5.15975s/12 iters), loss = 4.93651
I0405 14:53:34.476981 18799 solver.cpp:237]     Train net output #0: loss = 4.93651 (* 1 = 4.93651 loss)
I0405 14:53:34.476989 18799 sgd_solver.cpp:105] Iteration 14148, lr = 0.0001
I0405 14:53:39.756413 18799 solver.cpp:218] Iteration 14160 (2.27299 iter/s, 5.27939s/12 iters), loss = 4.86809
I0405 14:53:39.756459 18799 solver.cpp:237]     Train net output #0: loss = 4.86809 (* 1 = 4.86809 loss)
I0405 14:53:39.756464 18799 sgd_solver.cpp:105] Iteration 14160, lr = 0.0001
I0405 14:53:40.014847 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:53:45.280977 18799 solver.cpp:218] Iteration 14172 (2.17216 iter/s, 5.52447s/12 iters), loss = 4.82422
I0405 14:53:45.281020 18799 solver.cpp:237]     Train net output #0: loss = 4.82422 (* 1 = 4.82422 loss)
I0405 14:53:45.281026 18799 sgd_solver.cpp:105] Iteration 14172, lr = 0.0001
I0405 14:53:47.417771 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14178.caffemodel
I0405 14:53:50.474896 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14178.solverstate
I0405 14:53:52.786103 18799 solver.cpp:330] Iteration 14178, Testing net (#0)
I0405 14:53:52.786124 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:53:56.139712 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:53:57.086591 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0367647
I0405 14:53:57.086628 18799 solver.cpp:397]     Test net output #1: loss = 4.87936 (* 1 = 4.87936 loss)
I0405 14:53:59.049517 18799 solver.cpp:218] Iteration 14184 (0.871561 iter/s, 13.7684s/12 iters), loss = 4.87658
I0405 14:53:59.049562 18799 solver.cpp:237]     Train net output #0: loss = 4.87658 (* 1 = 4.87658 loss)
I0405 14:53:59.049569 18799 sgd_solver.cpp:105] Iteration 14184, lr = 0.0001
I0405 14:54:04.148855 18799 solver.cpp:218] Iteration 14196 (2.35329 iter/s, 5.09924s/12 iters), loss = 4.79446
I0405 14:54:04.148914 18799 solver.cpp:237]     Train net output #0: loss = 4.79446 (* 1 = 4.79446 loss)
I0405 14:54:04.148922 18799 sgd_solver.cpp:105] Iteration 14196, lr = 0.0001
I0405 14:54:09.296815 18799 solver.cpp:218] Iteration 14208 (2.33106 iter/s, 5.14786s/12 iters), loss = 4.86025
I0405 14:54:09.296916 18799 solver.cpp:237]     Train net output #0: loss = 4.86025 (* 1 = 4.86025 loss)
I0405 14:54:09.296923 18799 sgd_solver.cpp:105] Iteration 14208, lr = 0.0001
I0405 14:54:14.759671 18799 solver.cpp:218] Iteration 14220 (2.19671 iter/s, 5.46271s/12 iters), loss = 4.73522
I0405 14:54:14.759727 18799 solver.cpp:237]     Train net output #0: loss = 4.73522 (* 1 = 4.73522 loss)
I0405 14:54:14.759737 18799 sgd_solver.cpp:105] Iteration 14220, lr = 0.0001
I0405 14:54:20.149106 18799 solver.cpp:218] Iteration 14232 (2.22662 iter/s, 5.38933s/12 iters), loss = 4.76098
I0405 14:54:20.149168 18799 solver.cpp:237]     Train net output #0: loss = 4.76098 (* 1 = 4.76098 loss)
I0405 14:54:20.149176 18799 sgd_solver.cpp:105] Iteration 14232, lr = 0.0001
I0405 14:54:25.544317 18799 solver.cpp:218] Iteration 14244 (2.22424 iter/s, 5.3951s/12 iters), loss = 4.88823
I0405 14:54:25.544358 18799 solver.cpp:237]     Train net output #0: loss = 4.88823 (* 1 = 4.88823 loss)
I0405 14:54:25.544363 18799 sgd_solver.cpp:105] Iteration 14244, lr = 0.0001
I0405 14:54:30.767280 18799 solver.cpp:218] Iteration 14256 (2.29758 iter/s, 5.22288s/12 iters), loss = 4.8324
I0405 14:54:30.767323 18799 solver.cpp:237]     Train net output #0: loss = 4.8324 (* 1 = 4.8324 loss)
I0405 14:54:30.767328 18799 sgd_solver.cpp:105] Iteration 14256, lr = 0.0001
I0405 14:54:33.350950 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:54:36.019603 18799 solver.cpp:218] Iteration 14268 (2.28474 iter/s, 5.25223s/12 iters), loss = 4.79403
I0405 14:54:36.019642 18799 solver.cpp:237]     Train net output #0: loss = 4.79403 (* 1 = 4.79403 loss)
I0405 14:54:36.019649 18799 sgd_solver.cpp:105] Iteration 14268, lr = 0.0001
I0405 14:54:40.844470 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14280.caffemodel
I0405 14:54:43.880271 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14280.solverstate
I0405 14:54:47.334741 18799 solver.cpp:330] Iteration 14280, Testing net (#0)
I0405 14:54:47.334764 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:54:50.695132 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:54:51.738437 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0404412
I0405 14:54:51.738476 18799 solver.cpp:397]     Test net output #1: loss = 4.87361 (* 1 = 4.87361 loss)
I0405 14:54:51.880722 18799 solver.cpp:218] Iteration 14280 (0.756574 iter/s, 15.861s/12 iters), loss = 4.67529
I0405 14:54:51.880772 18799 solver.cpp:237]     Train net output #0: loss = 4.67529 (* 1 = 4.67529 loss)
I0405 14:54:51.880780 18799 sgd_solver.cpp:105] Iteration 14280, lr = 0.0001
I0405 14:54:56.025497 18799 solver.cpp:218] Iteration 14292 (2.89527 iter/s, 4.14469s/12 iters), loss = 4.77835
I0405 14:54:56.025534 18799 solver.cpp:237]     Train net output #0: loss = 4.77835 (* 1 = 4.77835 loss)
I0405 14:54:56.025539 18799 sgd_solver.cpp:105] Iteration 14292, lr = 0.0001
I0405 14:55:01.511122 18799 solver.cpp:218] Iteration 14304 (2.18757 iter/s, 5.48553s/12 iters), loss = 4.73641
I0405 14:55:01.511174 18799 solver.cpp:237]     Train net output #0: loss = 4.73641 (* 1 = 4.73641 loss)
I0405 14:55:01.511183 18799 sgd_solver.cpp:105] Iteration 14304, lr = 0.0001
I0405 14:55:06.791815 18799 solver.cpp:218] Iteration 14316 (2.27247 iter/s, 5.28059s/12 iters), loss = 4.77215
I0405 14:55:06.791875 18799 solver.cpp:237]     Train net output #0: loss = 4.77215 (* 1 = 4.77215 loss)
I0405 14:55:06.791883 18799 sgd_solver.cpp:105] Iteration 14316, lr = 0.0001
I0405 14:55:12.213228 18799 solver.cpp:218] Iteration 14328 (2.21349 iter/s, 5.42131s/12 iters), loss = 4.76095
I0405 14:55:12.213338 18799 solver.cpp:237]     Train net output #0: loss = 4.76095 (* 1 = 4.76095 loss)
I0405 14:55:12.213346 18799 sgd_solver.cpp:105] Iteration 14328, lr = 0.0001
I0405 14:55:17.315436 18799 solver.cpp:218] Iteration 14340 (2.35199 iter/s, 5.10206s/12 iters), loss = 4.70808
I0405 14:55:17.315479 18799 solver.cpp:237]     Train net output #0: loss = 4.70808 (* 1 = 4.70808 loss)
I0405 14:55:17.315485 18799 sgd_solver.cpp:105] Iteration 14340, lr = 0.0001
I0405 14:55:22.211319 18799 solver.cpp:218] Iteration 14352 (2.45108 iter/s, 4.8958s/12 iters), loss = 4.70536
I0405 14:55:22.211359 18799 solver.cpp:237]     Train net output #0: loss = 4.70536 (* 1 = 4.70536 loss)
I0405 14:55:22.211365 18799 sgd_solver.cpp:105] Iteration 14352, lr = 0.0001
I0405 14:55:27.165187 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:55:27.551895 18799 solver.cpp:218] Iteration 14364 (2.24699 iter/s, 5.34049s/12 iters), loss = 4.79324
I0405 14:55:27.551964 18799 solver.cpp:237]     Train net output #0: loss = 4.79324 (* 1 = 4.79324 loss)
I0405 14:55:27.551972 18799 sgd_solver.cpp:105] Iteration 14364, lr = 0.0001
I0405 14:55:32.936609 18799 solver.cpp:218] Iteration 14376 (2.22858 iter/s, 5.3846s/12 iters), loss = 4.72088
I0405 14:55:32.936646 18799 solver.cpp:237]     Train net output #0: loss = 4.72088 (* 1 = 4.72088 loss)
I0405 14:55:32.936651 18799 sgd_solver.cpp:105] Iteration 14376, lr = 0.0001
I0405 14:55:34.942381 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14382.caffemodel
I0405 14:55:37.973727 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14382.solverstate
I0405 14:55:40.303582 18799 solver.cpp:330] Iteration 14382, Testing net (#0)
I0405 14:55:40.303607 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:55:43.611362 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:55:44.639319 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:55:44.639359 18799 solver.cpp:397]     Test net output #1: loss = 4.87197 (* 1 = 4.87197 loss)
I0405 14:55:46.571885 18799 solver.cpp:218] Iteration 14388 (0.880078 iter/s, 13.6351s/12 iters), loss = 4.63839
I0405 14:55:46.571925 18799 solver.cpp:237]     Train net output #0: loss = 4.63839 (* 1 = 4.63839 loss)
I0405 14:55:46.571931 18799 sgd_solver.cpp:105] Iteration 14388, lr = 0.0001
I0405 14:55:51.661429 18799 solver.cpp:218] Iteration 14400 (2.35782 iter/s, 5.08946s/12 iters), loss = 4.74765
I0405 14:55:51.661473 18799 solver.cpp:237]     Train net output #0: loss = 4.74765 (* 1 = 4.74765 loss)
I0405 14:55:51.661480 18799 sgd_solver.cpp:105] Iteration 14400, lr = 0.0001
I0405 14:55:57.015930 18799 solver.cpp:218] Iteration 14412 (2.24114 iter/s, 5.35441s/12 iters), loss = 4.72606
I0405 14:55:57.015970 18799 solver.cpp:237]     Train net output #0: loss = 4.72606 (* 1 = 4.72606 loss)
I0405 14:55:57.015976 18799 sgd_solver.cpp:105] Iteration 14412, lr = 0.0001
I0405 14:56:02.279366 18799 solver.cpp:218] Iteration 14424 (2.27992 iter/s, 5.26335s/12 iters), loss = 4.84127
I0405 14:56:02.279407 18799 solver.cpp:237]     Train net output #0: loss = 4.84127 (* 1 = 4.84127 loss)
I0405 14:56:02.279413 18799 sgd_solver.cpp:105] Iteration 14424, lr = 0.0001
I0405 14:56:07.507769 18799 solver.cpp:218] Iteration 14436 (2.2952 iter/s, 5.22831s/12 iters), loss = 4.67011
I0405 14:56:07.507829 18799 solver.cpp:237]     Train net output #0: loss = 4.67011 (* 1 = 4.67011 loss)
I0405 14:56:07.507839 18799 sgd_solver.cpp:105] Iteration 14436, lr = 0.0001
I0405 14:56:12.829999 18799 solver.cpp:218] Iteration 14448 (2.25474 iter/s, 5.32212s/12 iters), loss = 4.71674
I0405 14:56:12.830051 18799 solver.cpp:237]     Train net output #0: loss = 4.71674 (* 1 = 4.71674 loss)
I0405 14:56:12.830057 18799 sgd_solver.cpp:105] Iteration 14448, lr = 0.0001
I0405 14:56:18.052278 18799 solver.cpp:218] Iteration 14460 (2.29789 iter/s, 5.22218s/12 iters), loss = 4.78783
I0405 14:56:18.052386 18799 solver.cpp:237]     Train net output #0: loss = 4.78783 (* 1 = 4.78783 loss)
I0405 14:56:18.052392 18799 sgd_solver.cpp:105] Iteration 14460, lr = 0.0001
I0405 14:56:19.964092 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:56:23.578842 18799 solver.cpp:218] Iteration 14472 (2.17139 iter/s, 5.52641s/12 iters), loss = 4.80738
I0405 14:56:23.578887 18799 solver.cpp:237]     Train net output #0: loss = 4.80738 (* 1 = 4.80738 loss)
I0405 14:56:23.578893 18799 sgd_solver.cpp:105] Iteration 14472, lr = 0.0001
I0405 14:56:28.308533 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14484.caffemodel
I0405 14:56:31.308759 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14484.solverstate
I0405 14:56:33.614312 18799 solver.cpp:330] Iteration 14484, Testing net (#0)
I0405 14:56:33.614331 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:56:36.823340 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:56:37.892844 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0379902
I0405 14:56:37.892879 18799 solver.cpp:397]     Test net output #1: loss = 4.8621 (* 1 = 4.8621 loss)
I0405 14:56:38.031415 18799 solver.cpp:218] Iteration 14484 (0.83031 iter/s, 14.4524s/12 iters), loss = 4.83575
I0405 14:56:38.031471 18799 solver.cpp:237]     Train net output #0: loss = 4.83575 (* 1 = 4.83575 loss)
I0405 14:56:38.031479 18799 sgd_solver.cpp:105] Iteration 14484, lr = 0.0001
I0405 14:56:42.454834 18799 solver.cpp:218] Iteration 14496 (2.71289 iter/s, 4.42333s/12 iters), loss = 4.59732
I0405 14:56:42.454891 18799 solver.cpp:237]     Train net output #0: loss = 4.59732 (* 1 = 4.59732 loss)
I0405 14:56:42.454900 18799 sgd_solver.cpp:105] Iteration 14496, lr = 0.0001
I0405 14:56:47.826490 18799 solver.cpp:218] Iteration 14508 (2.23399 iter/s, 5.37156s/12 iters), loss = 4.62338
I0405 14:56:47.826531 18799 solver.cpp:237]     Train net output #0: loss = 4.62338 (* 1 = 4.62338 loss)
I0405 14:56:47.826536 18799 sgd_solver.cpp:105] Iteration 14508, lr = 0.0001
I0405 14:56:52.960266 18799 solver.cpp:218] Iteration 14520 (2.3375 iter/s, 5.13369s/12 iters), loss = 4.78621
I0405 14:56:52.960398 18799 solver.cpp:237]     Train net output #0: loss = 4.78621 (* 1 = 4.78621 loss)
I0405 14:56:52.960404 18799 sgd_solver.cpp:105] Iteration 14520, lr = 0.0001
I0405 14:56:58.248136 18799 solver.cpp:218] Iteration 14532 (2.26942 iter/s, 5.28769s/12 iters), loss = 4.87291
I0405 14:56:58.248193 18799 solver.cpp:237]     Train net output #0: loss = 4.87291 (* 1 = 4.87291 loss)
I0405 14:56:58.248200 18799 sgd_solver.cpp:105] Iteration 14532, lr = 0.0001
I0405 14:57:03.643090 18799 solver.cpp:218] Iteration 14544 (2.22434 iter/s, 5.39485s/12 iters), loss = 4.75536
I0405 14:57:03.643132 18799 solver.cpp:237]     Train net output #0: loss = 4.75536 (* 1 = 4.75536 loss)
I0405 14:57:03.643137 18799 sgd_solver.cpp:105] Iteration 14544, lr = 0.0001
I0405 14:57:08.844311 18799 solver.cpp:218] Iteration 14556 (2.30719 iter/s, 5.20113s/12 iters), loss = 4.77186
I0405 14:57:08.844352 18799 solver.cpp:237]     Train net output #0: loss = 4.77186 (* 1 = 4.77186 loss)
I0405 14:57:08.844358 18799 sgd_solver.cpp:105] Iteration 14556, lr = 0.0001
I0405 14:57:12.938567 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:57:13.144646 18799 blocking_queue.cpp:49] Waiting for data
I0405 14:57:14.132452 18799 solver.cpp:218] Iteration 14568 (2.26927 iter/s, 5.28804s/12 iters), loss = 4.79997
I0405 14:57:14.132511 18799 solver.cpp:237]     Train net output #0: loss = 4.79997 (* 1 = 4.79997 loss)
I0405 14:57:14.132520 18799 sgd_solver.cpp:105] Iteration 14568, lr = 0.0001
I0405 14:57:19.156390 18799 solver.cpp:218] Iteration 14580 (2.38861 iter/s, 5.02384s/12 iters), loss = 4.80903
I0405 14:57:19.156433 18799 solver.cpp:237]     Train net output #0: loss = 4.80903 (* 1 = 4.80903 loss)
I0405 14:57:19.156440 18799 sgd_solver.cpp:105] Iteration 14580, lr = 0.0001
I0405 14:57:21.165215 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14586.caffemodel
I0405 14:57:24.281983 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14586.solverstate
I0405 14:57:26.629829 18799 solver.cpp:330] Iteration 14586, Testing net (#0)
I0405 14:57:26.629849 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:57:30.117796 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:57:31.247872 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0373775
I0405 14:57:31.247910 18799 solver.cpp:397]     Test net output #1: loss = 4.8666 (* 1 = 4.8666 loss)
I0405 14:57:33.139341 18799 solver.cpp:218] Iteration 14592 (0.858197 iter/s, 13.9828s/12 iters), loss = 4.77885
I0405 14:57:33.139391 18799 solver.cpp:237]     Train net output #0: loss = 4.77885 (* 1 = 4.77885 loss)
I0405 14:57:33.139400 18799 sgd_solver.cpp:105] Iteration 14592, lr = 0.0001
I0405 14:57:38.391793 18799 solver.cpp:218] Iteration 14604 (2.28469 iter/s, 5.25236s/12 iters), loss = 4.65554
I0405 14:57:38.391831 18799 solver.cpp:237]     Train net output #0: loss = 4.65554 (* 1 = 4.65554 loss)
I0405 14:57:38.391837 18799 sgd_solver.cpp:105] Iteration 14604, lr = 0.0001
I0405 14:57:43.490218 18799 solver.cpp:218] Iteration 14616 (2.35371 iter/s, 5.09834s/12 iters), loss = 4.84037
I0405 14:57:43.490276 18799 solver.cpp:237]     Train net output #0: loss = 4.84037 (* 1 = 4.84037 loss)
I0405 14:57:43.490285 18799 sgd_solver.cpp:105] Iteration 14616, lr = 0.0001
I0405 14:57:48.742391 18799 solver.cpp:218] Iteration 14628 (2.28481 iter/s, 5.25207s/12 iters), loss = 4.59115
I0405 14:57:48.742445 18799 solver.cpp:237]     Train net output #0: loss = 4.59115 (* 1 = 4.59115 loss)
I0405 14:57:48.742453 18799 sgd_solver.cpp:105] Iteration 14628, lr = 0.0001
I0405 14:57:54.240854 18799 solver.cpp:218] Iteration 14640 (2.18247 iter/s, 5.49836s/12 iters), loss = 4.72441
I0405 14:57:54.240901 18799 solver.cpp:237]     Train net output #0: loss = 4.72441 (* 1 = 4.72441 loss)
I0405 14:57:54.240907 18799 sgd_solver.cpp:105] Iteration 14640, lr = 0.0001
I0405 14:57:59.620101 18799 solver.cpp:218] Iteration 14652 (2.23084 iter/s, 5.37915s/12 iters), loss = 4.69179
I0405 14:57:59.620245 18799 solver.cpp:237]     Train net output #0: loss = 4.69179 (* 1 = 4.69179 loss)
I0405 14:57:59.620254 18799 sgd_solver.cpp:105] Iteration 14652, lr = 0.0001
I0405 14:58:05.046908 18799 solver.cpp:218] Iteration 14664 (2.21132 iter/s, 5.42662s/12 iters), loss = 4.76399
I0405 14:58:05.046957 18799 solver.cpp:237]     Train net output #0: loss = 4.76399 (* 1 = 4.76399 loss)
I0405 14:58:05.046964 18799 sgd_solver.cpp:105] Iteration 14664, lr = 0.0001
I0405 14:58:06.144609 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:58:10.488267 18799 solver.cpp:218] Iteration 14676 (2.20537 iter/s, 5.44126s/12 iters), loss = 4.73607
I0405 14:58:10.488324 18799 solver.cpp:237]     Train net output #0: loss = 4.73607 (* 1 = 4.73607 loss)
I0405 14:58:10.488332 18799 sgd_solver.cpp:105] Iteration 14676, lr = 0.0001
I0405 14:58:15.181761 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14688.caffemodel
I0405 14:58:18.141038 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14688.solverstate
I0405 14:58:20.578574 18799 solver.cpp:330] Iteration 14688, Testing net (#0)
I0405 14:58:20.578598 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:58:23.752903 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:58:24.949373 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0422794
I0405 14:58:24.949400 18799 solver.cpp:397]     Test net output #1: loss = 4.85366 (* 1 = 4.85366 loss)
I0405 14:58:25.087611 18799 solver.cpp:218] Iteration 14688 (0.821964 iter/s, 14.5992s/12 iters), loss = 4.84403
I0405 14:58:25.087651 18799 solver.cpp:237]     Train net output #0: loss = 4.84403 (* 1 = 4.84403 loss)
I0405 14:58:25.087656 18799 sgd_solver.cpp:105] Iteration 14688, lr = 0.0001
I0405 14:58:29.253787 18799 solver.cpp:218] Iteration 14700 (2.8804 iter/s, 4.16609s/12 iters), loss = 4.76419
I0405 14:58:29.253834 18799 solver.cpp:237]     Train net output #0: loss = 4.76419 (* 1 = 4.76419 loss)
I0405 14:58:29.253842 18799 sgd_solver.cpp:105] Iteration 14700, lr = 0.0001
I0405 14:58:34.656749 18799 solver.cpp:218] Iteration 14712 (2.22104 iter/s, 5.40286s/12 iters), loss = 4.77619
I0405 14:58:34.656867 18799 solver.cpp:237]     Train net output #0: loss = 4.77619 (* 1 = 4.77619 loss)
I0405 14:58:34.656877 18799 sgd_solver.cpp:105] Iteration 14712, lr = 0.0001
I0405 14:58:39.977378 18799 solver.cpp:218] Iteration 14724 (2.25544 iter/s, 5.32047s/12 iters), loss = 4.73436
I0405 14:58:39.977419 18799 solver.cpp:237]     Train net output #0: loss = 4.73436 (* 1 = 4.73436 loss)
I0405 14:58:39.977424 18799 sgd_solver.cpp:105] Iteration 14724, lr = 0.0001
I0405 14:58:45.349318 18799 solver.cpp:218] Iteration 14736 (2.23387 iter/s, 5.37185s/12 iters), loss = 4.69035
I0405 14:58:45.349356 18799 solver.cpp:237]     Train net output #0: loss = 4.69035 (* 1 = 4.69035 loss)
I0405 14:58:45.349362 18799 sgd_solver.cpp:105] Iteration 14736, lr = 0.0001
I0405 14:58:50.761101 18799 solver.cpp:218] Iteration 14748 (2.21742 iter/s, 5.4117s/12 iters), loss = 4.70782
I0405 14:58:50.761142 18799 solver.cpp:237]     Train net output #0: loss = 4.70782 (* 1 = 4.70782 loss)
I0405 14:58:50.761147 18799 sgd_solver.cpp:105] Iteration 14748, lr = 0.0001
I0405 14:58:56.142432 18799 solver.cpp:218] Iteration 14760 (2.22997 iter/s, 5.38124s/12 iters), loss = 4.7169
I0405 14:58:56.142483 18799 solver.cpp:237]     Train net output #0: loss = 4.7169 (* 1 = 4.7169 loss)
I0405 14:58:56.142491 18799 sgd_solver.cpp:105] Iteration 14760, lr = 0.0001
I0405 14:58:59.362066 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:01.085604 18799 solver.cpp:218] Iteration 14772 (2.42764 iter/s, 4.94308s/12 iters), loss = 4.67948
I0405 14:59:01.085644 18799 solver.cpp:237]     Train net output #0: loss = 4.67948 (* 1 = 4.67948 loss)
I0405 14:59:01.085649 18799 sgd_solver.cpp:105] Iteration 14772, lr = 0.0001
I0405 14:59:06.001178 18799 solver.cpp:218] Iteration 14784 (2.44126 iter/s, 4.91549s/12 iters), loss = 4.66619
I0405 14:59:06.001361 18799 solver.cpp:237]     Train net output #0: loss = 4.66619 (* 1 = 4.66619 loss)
I0405 14:59:06.001379 18799 sgd_solver.cpp:105] Iteration 14784, lr = 0.0001
I0405 14:59:08.095372 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14790.caffemodel
I0405 14:59:11.110466 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14790.solverstate
I0405 14:59:13.408413 18799 solver.cpp:330] Iteration 14790, Testing net (#0)
I0405 14:59:13.408432 18799 net.cpp:676] Ignoring source layer train-data
I0405 14:59:16.729861 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:17.911860 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0386029
I0405 14:59:17.911893 18799 solver.cpp:397]     Test net output #1: loss = 4.86595 (* 1 = 4.86595 loss)
I0405 14:59:19.859781 18799 solver.cpp:218] Iteration 14796 (0.865905 iter/s, 13.8583s/12 iters), loss = 4.83088
I0405 14:59:19.859828 18799 solver.cpp:237]     Train net output #0: loss = 4.83088 (* 1 = 4.83088 loss)
I0405 14:59:19.859834 18799 sgd_solver.cpp:105] Iteration 14796, lr = 0.0001
I0405 14:59:25.083138 18799 solver.cpp:218] Iteration 14808 (2.29741 iter/s, 5.22327s/12 iters), loss = 4.71988
I0405 14:59:25.083178 18799 solver.cpp:237]     Train net output #0: loss = 4.71988 (* 1 = 4.71988 loss)
I0405 14:59:25.083184 18799 sgd_solver.cpp:105] Iteration 14808, lr = 0.0001
I0405 14:59:30.336614 18799 solver.cpp:218] Iteration 14820 (2.28424 iter/s, 5.25339s/12 iters), loss = 4.94245
I0405 14:59:30.336665 18799 solver.cpp:237]     Train net output #0: loss = 4.94245 (* 1 = 4.94245 loss)
I0405 14:59:30.336675 18799 sgd_solver.cpp:105] Iteration 14820, lr = 0.0001
I0405 14:59:35.547394 18799 solver.cpp:218] Iteration 14832 (2.30296 iter/s, 5.21068s/12 iters), loss = 4.69439
I0405 14:59:35.547435 18799 solver.cpp:237]     Train net output #0: loss = 4.69439 (* 1 = 4.69439 loss)
I0405 14:59:35.547439 18799 sgd_solver.cpp:105] Iteration 14832, lr = 0.0001
I0405 14:59:40.744786 18799 solver.cpp:218] Iteration 14844 (2.30889 iter/s, 5.1973s/12 iters), loss = 4.85973
I0405 14:59:40.744908 18799 solver.cpp:237]     Train net output #0: loss = 4.85973 (* 1 = 4.85973 loss)
I0405 14:59:40.744915 18799 sgd_solver.cpp:105] Iteration 14844, lr = 0.0001
I0405 14:59:46.094379 18799 solver.cpp:218] Iteration 14856 (2.24323 iter/s, 5.34943s/12 iters), loss = 4.86522
I0405 14:59:46.094419 18799 solver.cpp:237]     Train net output #0: loss = 4.86522 (* 1 = 4.86522 loss)
I0405 14:59:46.094424 18799 sgd_solver.cpp:105] Iteration 14856, lr = 0.0001
I0405 14:59:51.201542 18799 solver.cpp:218] Iteration 14868 (2.34968 iter/s, 5.10708s/12 iters), loss = 4.76444
I0405 14:59:51.201589 18799 solver.cpp:237]     Train net output #0: loss = 4.76444 (* 1 = 4.76444 loss)
I0405 14:59:51.201596 18799 sgd_solver.cpp:105] Iteration 14868, lr = 0.0001
I0405 14:59:51.489033 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:56.436379 18799 solver.cpp:218] Iteration 14880 (2.29238 iter/s, 5.23474s/12 iters), loss = 4.78
I0405 14:59:56.436424 18799 solver.cpp:237]     Train net output #0: loss = 4.78 (* 1 = 4.78 loss)
I0405 14:59:56.436429 18799 sgd_solver.cpp:105] Iteration 14880, lr = 0.0001
I0405 15:00:01.108566 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14892.caffemodel
I0405 15:00:04.118237 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14892.solverstate
I0405 15:00:06.426486 18799 solver.cpp:330] Iteration 14892, Testing net (#0)
I0405 15:00:06.426506 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:00:09.684419 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:00:10.923704 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0373775
I0405 15:00:10.923825 18799 solver.cpp:397]     Test net output #1: loss = 4.85815 (* 1 = 4.85815 loss)
I0405 15:00:11.065865 18799 solver.cpp:218] Iteration 14892 (0.820269 iter/s, 14.6293s/12 iters), loss = 4.98519
I0405 15:00:11.067428 18799 solver.cpp:237]     Train net output #0: loss = 4.98519 (* 1 = 4.98519 loss)
I0405 15:00:11.067441 18799 sgd_solver.cpp:105] Iteration 14892, lr = 0.0001
I0405 15:00:15.492947 18799 solver.cpp:218] Iteration 14904 (2.71157 iter/s, 4.42548s/12 iters), loss = 4.67134
I0405 15:00:15.493007 18799 solver.cpp:237]     Train net output #0: loss = 4.67134 (* 1 = 4.67134 loss)
I0405 15:00:15.493016 18799 sgd_solver.cpp:105] Iteration 14904, lr = 0.0001
I0405 15:00:20.793870 18799 solver.cpp:218] Iteration 14916 (2.2638 iter/s, 5.30082s/12 iters), loss = 4.789
I0405 15:00:20.793915 18799 solver.cpp:237]     Train net output #0: loss = 4.789 (* 1 = 4.789 loss)
I0405 15:00:20.793922 18799 sgd_solver.cpp:105] Iteration 14916, lr = 0.0001
I0405 15:00:25.857725 18799 solver.cpp:218] Iteration 14928 (2.36978 iter/s, 5.06377s/12 iters), loss = 4.6382
I0405 15:00:25.857766 18799 solver.cpp:237]     Train net output #0: loss = 4.6382 (* 1 = 4.6382 loss)
I0405 15:00:25.857774 18799 sgd_solver.cpp:105] Iteration 14928, lr = 0.0001
I0405 15:00:31.175194 18799 solver.cpp:218] Iteration 14940 (2.25675 iter/s, 5.31738s/12 iters), loss = 4.58605
I0405 15:00:31.175249 18799 solver.cpp:237]     Train net output #0: loss = 4.58605 (* 1 = 4.58605 loss)
I0405 15:00:31.175258 18799 sgd_solver.cpp:105] Iteration 14940, lr = 0.0001
I0405 15:00:36.714236 18799 solver.cpp:218] Iteration 14952 (2.16648 iter/s, 5.53894s/12 iters), loss = 4.80944
I0405 15:00:36.714277 18799 solver.cpp:237]     Train net output #0: loss = 4.80944 (* 1 = 4.80944 loss)
I0405 15:00:36.714283 18799 sgd_solver.cpp:105] Iteration 14952, lr = 0.0001
I0405 15:00:41.923342 18799 solver.cpp:218] Iteration 14964 (2.3037 iter/s, 5.20902s/12 iters), loss = 4.73964
I0405 15:00:41.923451 18799 solver.cpp:237]     Train net output #0: loss = 4.73964 (* 1 = 4.73964 loss)
I0405 15:00:41.923457 18799 sgd_solver.cpp:105] Iteration 14964, lr = 0.0001
I0405 15:00:44.480432 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:00:47.161202 18799 solver.cpp:218] Iteration 14976 (2.29108 iter/s, 5.23771s/12 iters), loss = 4.76894
I0405 15:00:47.161250 18799 solver.cpp:237]     Train net output #0: loss = 4.76894 (* 1 = 4.76894 loss)
I0405 15:00:47.161257 18799 sgd_solver.cpp:105] Iteration 14976, lr = 0.0001
I0405 15:00:52.467263 18799 solver.cpp:218] Iteration 14988 (2.2616 iter/s, 5.30597s/12 iters), loss = 4.68857
I0405 15:00:52.467303 18799 solver.cpp:237]     Train net output #0: loss = 4.68857 (* 1 = 4.68857 loss)
I0405 15:00:52.467308 18799 sgd_solver.cpp:105] Iteration 14988, lr = 0.0001
I0405 15:00:54.635578 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14994.caffemodel
I0405 15:00:57.707309 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14994.solverstate
I0405 15:01:00.016326 18799 solver.cpp:330] Iteration 14994, Testing net (#0)
I0405 15:01:00.016352 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:01:03.082304 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:01:04.353768 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0435049
I0405 15:01:04.353809 18799 solver.cpp:397]     Test net output #1: loss = 4.8494 (* 1 = 4.8494 loss)
I0405 15:01:06.143926 18799 solver.cpp:218] Iteration 15000 (0.877416 iter/s, 13.6765s/12 iters), loss = 4.6966
I0405 15:01:06.143968 18799 solver.cpp:237]     Train net output #0: loss = 4.6966 (* 1 = 4.6966 loss)
I0405 15:01:06.143975 18799 sgd_solver.cpp:105] Iteration 15000, lr = 0.0001
I0405 15:01:11.511560 18799 solver.cpp:218] Iteration 15012 (2.23566 iter/s, 5.36754s/12 iters), loss = 4.83832
I0405 15:01:11.511602 18799 solver.cpp:237]     Train net output #0: loss = 4.83832 (* 1 = 4.83832 loss)
I0405 15:01:11.511607 18799 sgd_solver.cpp:105] Iteration 15012, lr = 0.0001
I0405 15:01:17.037266 18799 solver.cpp:218] Iteration 15024 (2.1717 iter/s, 5.52561s/12 iters), loss = 4.82896
I0405 15:01:17.037362 18799 solver.cpp:237]     Train net output #0: loss = 4.82896 (* 1 = 4.82896 loss)
I0405 15:01:17.037369 18799 sgd_solver.cpp:105] Iteration 15024, lr = 0.0001
I0405 15:01:22.445302 18799 solver.cpp:218] Iteration 15036 (2.21898 iter/s, 5.40789s/12 iters), loss = 4.77921
I0405 15:01:22.445346 18799 solver.cpp:237]     Train net output #0: loss = 4.77921 (* 1 = 4.77921 loss)
I0405 15:01:22.445353 18799 sgd_solver.cpp:105] Iteration 15036, lr = 0.0001
I0405 15:01:27.751107 18799 solver.cpp:218] Iteration 15048 (2.26171 iter/s, 5.30571s/12 iters), loss = 4.74355
I0405 15:01:27.751166 18799 solver.cpp:237]     Train net output #0: loss = 4.74355 (* 1 = 4.74355 loss)
I0405 15:01:27.751175 18799 sgd_solver.cpp:105] Iteration 15048, lr = 0.0001
I0405 15:01:33.075848 18799 solver.cpp:218] Iteration 15060 (2.25367 iter/s, 5.32464s/12 iters), loss = 4.61893
I0405 15:01:33.075888 18799 solver.cpp:237]     Train net output #0: loss = 4.61893 (* 1 = 4.61893 loss)
I0405 15:01:33.075893 18799 sgd_solver.cpp:105] Iteration 15060, lr = 0.0001
I0405 15:01:37.806519 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:01:38.167665 18799 solver.cpp:218] Iteration 15072 (2.35676 iter/s, 5.09173s/12 iters), loss = 4.79688
I0405 15:01:38.167706 18799 solver.cpp:237]     Train net output #0: loss = 4.79688 (* 1 = 4.79688 loss)
I0405 15:01:38.167712 18799 sgd_solver.cpp:105] Iteration 15072, lr = 0.0001
I0405 15:01:43.544836 18799 solver.cpp:218] Iteration 15084 (2.23169 iter/s, 5.37708s/12 iters), loss = 4.62822
I0405 15:01:43.544893 18799 solver.cpp:237]     Train net output #0: loss = 4.62822 (* 1 = 4.62822 loss)
I0405 15:01:43.544900 18799 sgd_solver.cpp:105] Iteration 15084, lr = 0.0001
I0405 15:01:48.450872 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15096.caffemodel
I0405 15:01:51.542615 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15096.solverstate
I0405 15:01:53.859335 18799 solver.cpp:330] Iteration 15096, Testing net (#0)
I0405 15:01:53.859357 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:01:56.898490 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:01:58.220988 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0422794
I0405 15:01:58.221021 18799 solver.cpp:397]     Test net output #1: loss = 4.84412 (* 1 = 4.84412 loss)
I0405 15:01:58.358289 18799 solver.cpp:218] Iteration 15096 (0.810082 iter/s, 14.8133s/12 iters), loss = 4.64408
I0405 15:01:58.358330 18799 solver.cpp:237]     Train net output #0: loss = 4.64408 (* 1 = 4.64408 loss)
I0405 15:01:58.358335 18799 sgd_solver.cpp:105] Iteration 15096, lr = 0.0001
I0405 15:02:02.770351 18799 solver.cpp:218] Iteration 15108 (2.71987 iter/s, 4.41198s/12 iters), loss = 4.709
I0405 15:02:02.770395 18799 solver.cpp:237]     Train net output #0: loss = 4.709 (* 1 = 4.709 loss)
I0405 15:02:02.770399 18799 sgd_solver.cpp:105] Iteration 15108, lr = 0.0001
I0405 15:02:07.926542 18799 solver.cpp:218] Iteration 15120 (2.32734 iter/s, 5.1561s/12 iters), loss = 4.71461
I0405 15:02:07.926599 18799 solver.cpp:237]     Train net output #0: loss = 4.71461 (* 1 = 4.71461 loss)
I0405 15:02:07.926607 18799 sgd_solver.cpp:105] Iteration 15120, lr = 0.0001
I0405 15:02:13.216315 18799 solver.cpp:218] Iteration 15132 (2.26857 iter/s, 5.28967s/12 iters), loss = 4.81694
I0405 15:02:13.216368 18799 solver.cpp:237]     Train net output #0: loss = 4.81694 (* 1 = 4.81694 loss)
I0405 15:02:13.216377 18799 sgd_solver.cpp:105] Iteration 15132, lr = 0.0001
I0405 15:02:18.746196 18799 solver.cpp:218] Iteration 15144 (2.17007 iter/s, 5.52978s/12 iters), loss = 4.61391
I0405 15:02:18.746292 18799 solver.cpp:237]     Train net output #0: loss = 4.61391 (* 1 = 4.61391 loss)
I0405 15:02:18.746299 18799 sgd_solver.cpp:105] Iteration 15144, lr = 0.0001
I0405 15:02:24.044553 18799 solver.cpp:218] Iteration 15156 (2.26491 iter/s, 5.29821s/12 iters), loss = 4.69692
I0405 15:02:24.044600 18799 solver.cpp:237]     Train net output #0: loss = 4.69692 (* 1 = 4.69692 loss)
I0405 15:02:24.044605 18799 sgd_solver.cpp:105] Iteration 15156, lr = 0.0001
I0405 15:02:29.208163 18799 solver.cpp:218] Iteration 15168 (2.324 iter/s, 5.16352s/12 iters), loss = 4.60904
I0405 15:02:29.208210 18799 solver.cpp:237]     Train net output #0: loss = 4.60904 (* 1 = 4.60904 loss)
I0405 15:02:29.208218 18799 sgd_solver.cpp:105] Iteration 15168, lr = 0.0001
I0405 15:02:31.011581 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:02:34.463968 18799 solver.cpp:218] Iteration 15180 (2.28323 iter/s, 5.25571s/12 iters), loss = 4.66814
I0405 15:02:34.464022 18799 solver.cpp:237]     Train net output #0: loss = 4.66814 (* 1 = 4.66814 loss)
I0405 15:02:34.464030 18799 sgd_solver.cpp:105] Iteration 15180, lr = 0.0001
I0405 15:02:39.925164 18799 solver.cpp:218] Iteration 15192 (2.19736 iter/s, 5.46109s/12 iters), loss = 4.71917
I0405 15:02:39.925211 18799 solver.cpp:237]     Train net output #0: loss = 4.71917 (* 1 = 4.71917 loss)
I0405 15:02:39.925216 18799 sgd_solver.cpp:105] Iteration 15192, lr = 0.0001
I0405 15:02:42.269271 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15198.caffemodel
I0405 15:02:46.216459 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15198.solverstate
I0405 15:02:49.244004 18799 solver.cpp:330] Iteration 15198, Testing net (#0)
I0405 15:02:49.244127 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:02:55.159811 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:02:57.676057 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0410539
I0405 15:02:57.676169 18799 solver.cpp:397]     Test net output #1: loss = 4.83582 (* 1 = 4.83582 loss)
I0405 15:03:01.757050 18799 solver.cpp:218] Iteration 15204 (0.54966 iter/s, 21.8317s/12 iters), loss = 4.52716
I0405 15:03:01.757108 18799 solver.cpp:237]     Train net output #0: loss = 4.52716 (* 1 = 4.52716 loss)
I0405 15:03:01.757117 18799 sgd_solver.cpp:105] Iteration 15204, lr = 0.0001
I0405 15:03:10.387250 18799 solver.cpp:218] Iteration 15216 (1.39049 iter/s, 8.63007s/12 iters), loss = 4.6959
I0405 15:03:10.387308 18799 solver.cpp:237]     Train net output #0: loss = 4.6959 (* 1 = 4.6959 loss)
I0405 15:03:10.387316 18799 sgd_solver.cpp:105] Iteration 15216, lr = 0.0001
I0405 15:03:16.835705 18799 solver.cpp:218] Iteration 15228 (1.86094 iter/s, 6.44834s/12 iters), loss = 4.80089
I0405 15:03:16.835762 18799 solver.cpp:237]     Train net output #0: loss = 4.80089 (* 1 = 4.80089 loss)
I0405 15:03:16.835770 18799 sgd_solver.cpp:105] Iteration 15228, lr = 0.0001
I0405 15:03:23.572371 18799 solver.cpp:218] Iteration 15240 (1.78133 iter/s, 6.73655s/12 iters), loss = 4.86901
I0405 15:03:23.572501 18799 solver.cpp:237]     Train net output #0: loss = 4.86901 (* 1 = 4.86901 loss)
I0405 15:03:23.572510 18799 sgd_solver.cpp:105] Iteration 15240, lr = 0.0001
I0405 15:03:29.434288 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:03:30.095557 18799 solver.cpp:218] Iteration 15252 (1.83965 iter/s, 6.523s/12 iters), loss = 4.78644
I0405 15:03:30.095618 18799 solver.cpp:237]     Train net output #0: loss = 4.78644 (* 1 = 4.78644 loss)
I0405 15:03:30.095628 18799 sgd_solver.cpp:105] Iteration 15252, lr = 0.0001
I0405 15:03:36.785131 18799 solver.cpp:218] Iteration 15264 (1.79387 iter/s, 6.68945s/12 iters), loss = 4.73555
I0405 15:03:36.785199 18799 solver.cpp:237]     Train net output #0: loss = 4.73555 (* 1 = 4.73555 loss)
I0405 15:03:36.785209 18799 sgd_solver.cpp:105] Iteration 15264, lr = 0.0001
I0405 15:03:41.491309 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:03:42.920127 18799 solver.cpp:218] Iteration 15276 (1.95603 iter/s, 6.13488s/12 iters), loss = 4.65538
I0405 15:03:42.920181 18799 solver.cpp:237]     Train net output #0: loss = 4.65538 (* 1 = 4.65538 loss)
I0405 15:03:42.920189 18799 sgd_solver.cpp:105] Iteration 15276, lr = 0.0001
I0405 15:03:49.383282 18799 solver.cpp:218] Iteration 15288 (1.85671 iter/s, 6.46305s/12 iters), loss = 4.84879
I0405 15:03:49.383333 18799 solver.cpp:237]     Train net output #0: loss = 4.84879 (* 1 = 4.84879 loss)
I0405 15:03:49.383342 18799 sgd_solver.cpp:105] Iteration 15288, lr = 0.0001
I0405 15:03:55.506405 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15300.caffemodel
I0405 15:03:59.095957 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15300.solverstate
I0405 15:04:02.296620 18799 solver.cpp:330] Iteration 15300, Testing net (#0)
I0405 15:04:02.296648 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:04:06.391784 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:04:08.324241 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0422794
I0405 15:04:08.324275 18799 solver.cpp:397]     Test net output #1: loss = 4.83069 (* 1 = 4.83069 loss)
I0405 15:04:08.462005 18799 solver.cpp:218] Iteration 15300 (0.628979 iter/s, 19.0785s/12 iters), loss = 4.65813
I0405 15:04:08.462054 18799 solver.cpp:237]     Train net output #0: loss = 4.65813 (* 1 = 4.65813 loss)
I0405 15:04:08.462062 18799 sgd_solver.cpp:105] Iteration 15300, lr = 0.0001
I0405 15:04:13.958055 18799 solver.cpp:218] Iteration 15312 (2.18343 iter/s, 5.49595s/12 iters), loss = 4.65742
I0405 15:04:13.962013 18799 solver.cpp:237]     Train net output #0: loss = 4.65742 (* 1 = 4.65742 loss)
I0405 15:04:13.962036 18799 sgd_solver.cpp:105] Iteration 15312, lr = 0.0001
I0405 15:04:20.606190 18799 solver.cpp:218] Iteration 15324 (1.8061 iter/s, 6.64414s/12 iters), loss = 4.76439
I0405 15:04:20.624974 18799 solver.cpp:237]     Train net output #0: loss = 4.76439 (* 1 = 4.76439 loss)
I0405 15:04:20.624996 18799 sgd_solver.cpp:105] Iteration 15324, lr = 0.0001
I0405 15:04:27.164925 18799 solver.cpp:218] Iteration 15336 (1.83693 iter/s, 6.53263s/12 iters), loss = 4.67028
I0405 15:04:27.169005 18799 solver.cpp:237]     Train net output #0: loss = 4.67028 (* 1 = 4.67028 loss)
I0405 15:04:27.169019 18799 sgd_solver.cpp:105] Iteration 15336, lr = 0.0001
I0405 15:04:33.515739 18799 solver.cpp:218] Iteration 15348 (1.89075 iter/s, 6.34669s/12 iters), loss = 4.68788
I0405 15:04:33.515789 18799 solver.cpp:237]     Train net output #0: loss = 4.68788 (* 1 = 4.68788 loss)
I0405 15:04:33.515797 18799 sgd_solver.cpp:105] Iteration 15348, lr = 0.0001
I0405 15:04:39.175344 18799 solver.cpp:218] Iteration 15360 (2.12033 iter/s, 5.65951s/12 iters), loss = 4.69069
I0405 15:04:39.175392 18799 solver.cpp:237]     Train net output #0: loss = 4.69069 (* 1 = 4.69069 loss)
I0405 15:04:39.175400 18799 sgd_solver.cpp:105] Iteration 15360, lr = 0.0001
I0405 15:04:44.505196 18799 solver.cpp:218] Iteration 15372 (2.25151 iter/s, 5.32976s/12 iters), loss = 4.79649
I0405 15:04:44.505234 18799 solver.cpp:237]     Train net output #0: loss = 4.79649 (* 1 = 4.79649 loss)
I0405 15:04:44.505240 18799 sgd_solver.cpp:105] Iteration 15372, lr = 0.0001
I0405 15:04:45.704939 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:04:49.920086 18799 solver.cpp:218] Iteration 15384 (2.21615 iter/s, 5.4148s/12 iters), loss = 4.68962
I0405 15:04:49.920136 18799 solver.cpp:237]     Train net output #0: loss = 4.68962 (* 1 = 4.68962 loss)
I0405 15:04:49.920145 18799 sgd_solver.cpp:105] Iteration 15384, lr = 0.0001
I0405 15:04:55.069636 18799 solver.cpp:218] Iteration 15396 (2.33034 iter/s, 5.14946s/12 iters), loss = 4.82344
I0405 15:04:55.069679 18799 solver.cpp:237]     Train net output #0: loss = 4.82344 (* 1 = 4.82344 loss)
I0405 15:04:55.069684 18799 sgd_solver.cpp:105] Iteration 15396, lr = 0.0001
I0405 15:04:57.175169 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15402.caffemodel
I0405 15:05:01.494259 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15402.solverstate
I0405 15:05:03.900321 18799 solver.cpp:330] Iteration 15402, Testing net (#0)
I0405 15:05:03.900344 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:05:06.850674 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:05:08.286175 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0398284
I0405 15:05:08.286212 18799 solver.cpp:397]     Test net output #1: loss = 4.83376 (* 1 = 4.83376 loss)
I0405 15:05:10.063772 18799 solver.cpp:218] Iteration 15408 (0.800321 iter/s, 14.994s/12 iters), loss = 4.84798
I0405 15:05:10.063822 18799 solver.cpp:237]     Train net output #0: loss = 4.84798 (* 1 = 4.84798 loss)
I0405 15:05:10.063830 18799 sgd_solver.cpp:105] Iteration 15408, lr = 0.0001
I0405 15:05:15.238977 18799 solver.cpp:218] Iteration 15420 (2.31879 iter/s, 5.17511s/12 iters), loss = 4.77875
I0405 15:05:15.239020 18799 solver.cpp:237]     Train net output #0: loss = 4.77875 (* 1 = 4.77875 loss)
I0405 15:05:15.239025 18799 sgd_solver.cpp:105] Iteration 15420, lr = 0.0001
I0405 15:05:20.426263 18799 solver.cpp:218] Iteration 15432 (2.31339 iter/s, 5.18719s/12 iters), loss = 4.74683
I0405 15:05:20.426319 18799 solver.cpp:237]     Train net output #0: loss = 4.74683 (* 1 = 4.74683 loss)
I0405 15:05:20.426327 18799 sgd_solver.cpp:105] Iteration 15432, lr = 0.0001
I0405 15:05:25.986984 18799 solver.cpp:218] Iteration 15444 (2.15803 iter/s, 5.56062s/12 iters), loss = 4.67425
I0405 15:05:25.987025 18799 solver.cpp:237]     Train net output #0: loss = 4.67425 (* 1 = 4.67425 loss)
I0405 15:05:25.987030 18799 sgd_solver.cpp:105] Iteration 15444, lr = 0.0001
I0405 15:05:31.370503 18799 solver.cpp:218] Iteration 15456 (2.22906 iter/s, 5.38343s/12 iters), loss = 4.65683
I0405 15:05:31.370671 18799 solver.cpp:237]     Train net output #0: loss = 4.65683 (* 1 = 4.65683 loss)
I0405 15:05:31.370678 18799 sgd_solver.cpp:105] Iteration 15456, lr = 0.0001
I0405 15:05:36.614392 18799 solver.cpp:218] Iteration 15468 (2.28847 iter/s, 5.24368s/12 iters), loss = 4.67968
I0405 15:05:36.614430 18799 solver.cpp:237]     Train net output #0: loss = 4.67968 (* 1 = 4.67968 loss)
I0405 15:05:36.614436 18799 sgd_solver.cpp:105] Iteration 15468, lr = 0.0001
I0405 15:05:39.966686 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:05:41.914002 18799 solver.cpp:218] Iteration 15480 (2.26435 iter/s, 5.29953s/12 iters), loss = 4.65751
I0405 15:05:41.914043 18799 solver.cpp:237]     Train net output #0: loss = 4.65751 (* 1 = 4.65751 loss)
I0405 15:05:41.914048 18799 sgd_solver.cpp:105] Iteration 15480, lr = 0.0001
I0405 15:05:47.118144 18799 solver.cpp:218] Iteration 15492 (2.30589 iter/s, 5.20405s/12 iters), loss = 4.64184
I0405 15:05:47.118182 18799 solver.cpp:237]     Train net output #0: loss = 4.64184 (* 1 = 4.64184 loss)
I0405 15:05:47.118187 18799 sgd_solver.cpp:105] Iteration 15492, lr = 0.0001
I0405 15:05:52.011971 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15504.caffemodel
I0405 15:05:55.816303 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15504.solverstate
I0405 15:05:58.136603 18799 solver.cpp:330] Iteration 15504, Testing net (#0)
I0405 15:05:58.136626 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:06:00.989763 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:06:02.490547 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0447304
I0405 15:06:02.490648 18799 solver.cpp:397]     Test net output #1: loss = 4.82921 (* 1 = 4.82921 loss)
I0405 15:06:02.632663 18799 solver.cpp:218] Iteration 15504 (0.773476 iter/s, 15.5144s/12 iters), loss = 4.82707
I0405 15:06:02.632719 18799 solver.cpp:237]     Train net output #0: loss = 4.82707 (* 1 = 4.82707 loss)
I0405 15:06:02.632726 18799 sgd_solver.cpp:105] Iteration 15504, lr = 0.0001
I0405 15:06:07.291421 18799 solver.cpp:218] Iteration 15516 (2.57585 iter/s, 4.65866s/12 iters), loss = 4.65535
I0405 15:06:07.291466 18799 solver.cpp:237]     Train net output #0: loss = 4.65535 (* 1 = 4.65535 loss)
I0405 15:06:07.291472 18799 sgd_solver.cpp:105] Iteration 15516, lr = 0.0001
I0405 15:06:12.733306 18799 solver.cpp:218] Iteration 15528 (2.20515 iter/s, 5.4418s/12 iters), loss = 4.83238
I0405 15:06:12.733362 18799 solver.cpp:237]     Train net output #0: loss = 4.83238 (* 1 = 4.83238 loss)
I0405 15:06:12.733371 18799 sgd_solver.cpp:105] Iteration 15528, lr = 0.0001
I0405 15:06:18.059777 18799 solver.cpp:218] Iteration 15540 (2.25294 iter/s, 5.32637s/12 iters), loss = 4.70125
I0405 15:06:18.059819 18799 solver.cpp:237]     Train net output #0: loss = 4.70125 (* 1 = 4.70125 loss)
I0405 15:06:18.059824 18799 sgd_solver.cpp:105] Iteration 15540, lr = 0.0001
I0405 15:06:23.146340 18799 solver.cpp:218] Iteration 15552 (2.3592 iter/s, 5.08647s/12 iters), loss = 4.73197
I0405 15:06:23.146385 18799 solver.cpp:237]     Train net output #0: loss = 4.73197 (* 1 = 4.73197 loss)
I0405 15:06:23.146391 18799 sgd_solver.cpp:105] Iteration 15552, lr = 0.0001
I0405 15:06:28.498477 18799 solver.cpp:218] Iteration 15564 (2.24213 iter/s, 5.35204s/12 iters), loss = 4.78271
I0405 15:06:28.498525 18799 solver.cpp:237]     Train net output #0: loss = 4.78271 (* 1 = 4.78271 loss)
I0405 15:06:28.498533 18799 sgd_solver.cpp:105] Iteration 15564, lr = 0.0001
I0405 15:06:33.787089 18799 solver.cpp:218] Iteration 15576 (2.26907 iter/s, 5.28852s/12 iters), loss = 4.62676
I0405 15:06:33.787236 18799 solver.cpp:237]     Train net output #0: loss = 4.62676 (* 1 = 4.62676 loss)
I0405 15:06:33.787245 18799 sgd_solver.cpp:105] Iteration 15576, lr = 0.0001
I0405 15:06:34.263572 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:06:38.923267 18799 solver.cpp:218] Iteration 15588 (2.33645 iter/s, 5.13599s/12 iters), loss = 4.74811
I0405 15:06:38.923306 18799 solver.cpp:237]     Train net output #0: loss = 4.74811 (* 1 = 4.74811 loss)
I0405 15:06:38.923311 18799 sgd_solver.cpp:105] Iteration 15588, lr = 0.0001
I0405 15:06:44.192415 18799 solver.cpp:218] Iteration 15600 (2.27745 iter/s, 5.26906s/12 iters), loss = 4.93977
I0405 15:06:44.192469 18799 solver.cpp:237]     Train net output #0: loss = 4.93977 (* 1 = 4.93977 loss)
I0405 15:06:44.192477 18799 sgd_solver.cpp:105] Iteration 15600, lr = 0.0001
I0405 15:06:46.194445 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15606.caffemodel
I0405 15:06:49.439893 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15606.solverstate
I0405 15:06:51.751256 18799 solver.cpp:330] Iteration 15606, Testing net (#0)
I0405 15:06:51.751278 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:06:54.567256 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:06:56.156601 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0441176
I0405 15:06:56.156636 18799 solver.cpp:397]     Test net output #1: loss = 4.82325 (* 1 = 4.82325 loss)
I0405 15:06:58.034548 18799 solver.cpp:218] Iteration 15612 (0.866928 iter/s, 13.842s/12 iters), loss = 4.73333
I0405 15:06:58.034603 18799 solver.cpp:237]     Train net output #0: loss = 4.73333 (* 1 = 4.73333 loss)
I0405 15:06:58.034612 18799 sgd_solver.cpp:105] Iteration 15612, lr = 0.0001
I0405 15:07:03.347784 18799 solver.cpp:218] Iteration 15624 (2.25855 iter/s, 5.31313s/12 iters), loss = 4.80728
I0405 15:07:03.347841 18799 solver.cpp:237]     Train net output #0: loss = 4.80728 (* 1 = 4.80728 loss)
I0405 15:07:03.347851 18799 sgd_solver.cpp:105] Iteration 15624, lr = 0.0001
I0405 15:07:08.855139 18799 solver.cpp:218] Iteration 15636 (2.17895 iter/s, 5.50725s/12 iters), loss = 4.57973
I0405 15:07:08.855262 18799 solver.cpp:237]     Train net output #0: loss = 4.57973 (* 1 = 4.57973 loss)
I0405 15:07:08.855270 18799 sgd_solver.cpp:105] Iteration 15636, lr = 0.0001
I0405 15:07:14.043377 18799 solver.cpp:218] Iteration 15648 (2.313 iter/s, 5.18807s/12 iters), loss = 4.45289
I0405 15:07:14.043432 18799 solver.cpp:237]     Train net output #0: loss = 4.45289 (* 1 = 4.45289 loss)
I0405 15:07:14.043442 18799 sgd_solver.cpp:105] Iteration 15648, lr = 0.0001
I0405 15:07:19.281754 18799 solver.cpp:218] Iteration 15660 (2.29083 iter/s, 5.23828s/12 iters), loss = 4.80782
I0405 15:07:19.281800 18799 solver.cpp:237]     Train net output #0: loss = 4.80782 (* 1 = 4.80782 loss)
I0405 15:07:19.281805 18799 sgd_solver.cpp:105] Iteration 15660, lr = 0.0001
I0405 15:07:24.584899 18799 solver.cpp:218] Iteration 15672 (2.26285 iter/s, 5.30305s/12 iters), loss = 4.82242
I0405 15:07:24.584951 18799 solver.cpp:237]     Train net output #0: loss = 4.82242 (* 1 = 4.82242 loss)
I0405 15:07:24.584961 18799 sgd_solver.cpp:105] Iteration 15672, lr = 0.0001
I0405 15:07:27.359728 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:07:29.982244 18799 solver.cpp:218] Iteration 15684 (2.22336 iter/s, 5.39725s/12 iters), loss = 4.81809
I0405 15:07:29.982301 18799 solver.cpp:237]     Train net output #0: loss = 4.81809 (* 1 = 4.81809 loss)
I0405 15:07:29.982311 18799 sgd_solver.cpp:105] Iteration 15684, lr = 0.0001
I0405 15:07:35.297513 18799 solver.cpp:218] Iteration 15696 (2.25781 iter/s, 5.31489s/12 iters), loss = 4.64375
I0405 15:07:35.297567 18799 solver.cpp:237]     Train net output #0: loss = 4.64375 (* 1 = 4.64375 loss)
I0405 15:07:35.297575 18799 sgd_solver.cpp:105] Iteration 15696, lr = 0.0001
I0405 15:07:40.134385 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15708.caffemodel
I0405 15:07:43.235513 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15708.solverstate
I0405 15:07:45.542866 18799 solver.cpp:330] Iteration 15708, Testing net (#0)
I0405 15:07:45.542884 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:07:48.309876 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:07:49.839691 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0490196
I0405 15:07:49.839725 18799 solver.cpp:397]     Test net output #1: loss = 4.81883 (* 1 = 4.81883 loss)
I0405 15:07:49.981475 18799 solver.cpp:218] Iteration 15708 (0.817226 iter/s, 14.6838s/12 iters), loss = 4.66765
I0405 15:07:49.983067 18799 solver.cpp:237]     Train net output #0: loss = 4.66765 (* 1 = 4.66765 loss)
I0405 15:07:49.983078 18799 sgd_solver.cpp:105] Iteration 15708, lr = 0.0001
I0405 15:07:54.387531 18799 solver.cpp:218] Iteration 15720 (2.72453 iter/s, 4.40443s/12 iters), loss = 4.71938
I0405 15:07:54.387573 18799 solver.cpp:237]     Train net output #0: loss = 4.71938 (* 1 = 4.71938 loss)
I0405 15:07:54.387578 18799 sgd_solver.cpp:105] Iteration 15720, lr = 0.0001
I0405 15:07:59.689409 18799 solver.cpp:218] Iteration 15732 (2.26339 iter/s, 5.30179s/12 iters), loss = 4.7788
I0405 15:07:59.689462 18799 solver.cpp:237]     Train net output #0: loss = 4.7788 (* 1 = 4.7788 loss)
I0405 15:07:59.689471 18799 sgd_solver.cpp:105] Iteration 15732, lr = 0.0001
I0405 15:08:04.947530 18799 solver.cpp:218] Iteration 15744 (2.28223 iter/s, 5.25802s/12 iters), loss = 4.746
I0405 15:08:04.947572 18799 solver.cpp:237]     Train net output #0: loss = 4.746 (* 1 = 4.746 loss)
I0405 15:08:04.947578 18799 sgd_solver.cpp:105] Iteration 15744, lr = 0.0001
I0405 15:08:10.420380 18799 solver.cpp:218] Iteration 15756 (2.19268 iter/s, 5.47276s/12 iters), loss = 4.53202
I0405 15:08:10.420495 18799 solver.cpp:237]     Train net output #0: loss = 4.53202 (* 1 = 4.53202 loss)
I0405 15:08:10.420502 18799 sgd_solver.cpp:105] Iteration 15756, lr = 0.0001
I0405 15:08:15.910616 18799 solver.cpp:218] Iteration 15768 (2.18576 iter/s, 5.49008s/12 iters), loss = 4.51338
I0405 15:08:15.910665 18799 solver.cpp:237]     Train net output #0: loss = 4.51338 (* 1 = 4.51338 loss)
I0405 15:08:15.910672 18799 sgd_solver.cpp:105] Iteration 15768, lr = 0.0001
I0405 15:08:20.946346 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:08:21.280942 18799 solver.cpp:218] Iteration 15780 (2.23454 iter/s, 5.37023s/12 iters), loss = 4.7373
I0405 15:08:21.280982 18799 solver.cpp:237]     Train net output #0: loss = 4.7373 (* 1 = 4.7373 loss)
I0405 15:08:21.280987 18799 sgd_solver.cpp:105] Iteration 15780, lr = 0.0001
I0405 15:08:26.470008 18799 solver.cpp:218] Iteration 15792 (2.31259 iter/s, 5.18898s/12 iters), loss = 4.53008
I0405 15:08:26.470053 18799 solver.cpp:237]     Train net output #0: loss = 4.53008 (* 1 = 4.53008 loss)
I0405 15:08:26.470062 18799 sgd_solver.cpp:105] Iteration 15792, lr = 0.0001
I0405 15:08:31.533951 18799 solver.cpp:218] Iteration 15804 (2.36973 iter/s, 5.06386s/12 iters), loss = 4.66126
I0405 15:08:31.533991 18799 solver.cpp:237]     Train net output #0: loss = 4.66126 (* 1 = 4.66126 loss)
I0405 15:08:31.533998 18799 sgd_solver.cpp:105] Iteration 15804, lr = 0.0001
I0405 15:08:33.651568 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15810.caffemodel
I0405 15:08:36.715930 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15810.solverstate
I0405 15:08:39.023098 18799 solver.cpp:330] Iteration 15810, Testing net (#0)
I0405 15:08:39.023118 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:08:41.949430 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:08:43.583920 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0502451
I0405 15:08:43.584309 18799 solver.cpp:397]     Test net output #1: loss = 4.81182 (* 1 = 4.81182 loss)
I0405 15:08:45.343092 18799 solver.cpp:218] Iteration 15816 (0.868998 iter/s, 13.809s/12 iters), loss = 4.63533
I0405 15:08:45.343142 18799 solver.cpp:237]     Train net output #0: loss = 4.63533 (* 1 = 4.63533 loss)
I0405 15:08:45.343150 18799 sgd_solver.cpp:105] Iteration 15816, lr = 0.0001
I0405 15:08:50.698829 18799 solver.cpp:218] Iteration 15828 (2.24063 iter/s, 5.35564s/12 iters), loss = 4.56311
I0405 15:08:50.698870 18799 solver.cpp:237]     Train net output #0: loss = 4.56311 (* 1 = 4.56311 loss)
I0405 15:08:50.698877 18799 sgd_solver.cpp:105] Iteration 15828, lr = 0.0001
I0405 15:08:56.100215 18799 solver.cpp:218] Iteration 15840 (2.22169 iter/s, 5.40129s/12 iters), loss = 4.72212
I0405 15:08:56.100279 18799 solver.cpp:237]     Train net output #0: loss = 4.72212 (* 1 = 4.72212 loss)
I0405 15:08:56.100286 18799 sgd_solver.cpp:105] Iteration 15840, lr = 0.0001
I0405 15:09:01.239099 18799 solver.cpp:218] Iteration 15852 (2.33518 iter/s, 5.13878s/12 iters), loss = 4.61132
I0405 15:09:01.239140 18799 solver.cpp:237]     Train net output #0: loss = 4.61132 (* 1 = 4.61132 loss)
I0405 15:09:01.239145 18799 sgd_solver.cpp:105] Iteration 15852, lr = 0.0001
I0405 15:09:06.612445 18799 solver.cpp:218] Iteration 15864 (2.23328 iter/s, 5.37326s/12 iters), loss = 4.57543
I0405 15:09:06.612483 18799 solver.cpp:237]     Train net output #0: loss = 4.57543 (* 1 = 4.57543 loss)
I0405 15:09:06.612489 18799 sgd_solver.cpp:105] Iteration 15864, lr = 0.0001
I0405 15:09:11.952797 18799 solver.cpp:218] Iteration 15876 (2.24708 iter/s, 5.34027s/12 iters), loss = 4.71747
I0405 15:09:11.952905 18799 solver.cpp:237]     Train net output #0: loss = 4.71747 (* 1 = 4.71747 loss)
I0405 15:09:11.952914 18799 sgd_solver.cpp:105] Iteration 15876, lr = 0.0001
I0405 15:09:13.946156 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:09:17.422830 18799 solver.cpp:218] Iteration 15888 (2.19383 iter/s, 5.46988s/12 iters), loss = 4.68918
I0405 15:09:17.422888 18799 solver.cpp:237]     Train net output #0: loss = 4.68918 (* 1 = 4.68918 loss)
I0405 15:09:17.422896 18799 sgd_solver.cpp:105] Iteration 15888, lr = 0.0001
I0405 15:09:22.712404 18799 solver.cpp:218] Iteration 15900 (2.26866 iter/s, 5.28947s/12 iters), loss = 4.77239
I0405 15:09:22.712456 18799 solver.cpp:237]     Train net output #0: loss = 4.77239 (* 1 = 4.77239 loss)
I0405 15:09:22.712466 18799 sgd_solver.cpp:105] Iteration 15900, lr = 0.0001
I0405 15:09:27.605540 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15912.caffemodel
I0405 15:09:30.632966 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15912.solverstate
I0405 15:09:32.933410 18799 solver.cpp:330] Iteration 15912, Testing net (#0)
I0405 15:09:32.933431 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:09:35.670902 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:09:37.311043 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0514706
I0405 15:09:37.311079 18799 solver.cpp:397]     Test net output #1: loss = 4.80697 (* 1 = 4.80697 loss)
I0405 15:09:37.451362 18799 solver.cpp:218] Iteration 15912 (0.814177 iter/s, 14.7388s/12 iters), loss = 4.57941
I0405 15:09:37.452965 18799 solver.cpp:237]     Train net output #0: loss = 4.57941 (* 1 = 4.57941 loss)
I0405 15:09:37.452976 18799 sgd_solver.cpp:105] Iteration 15912, lr = 0.0001
I0405 15:09:41.957950 18799 solver.cpp:218] Iteration 15924 (2.66374 iter/s, 4.50495s/12 iters), loss = 4.66184
I0405 15:09:41.958133 18799 solver.cpp:237]     Train net output #0: loss = 4.66184 (* 1 = 4.66184 loss)
I0405 15:09:41.958143 18799 sgd_solver.cpp:105] Iteration 15924, lr = 0.0001
I0405 15:09:47.030066 18799 solver.cpp:218] Iteration 15936 (2.36598 iter/s, 5.07189s/12 iters), loss = 4.76955
I0405 15:09:47.030122 18799 solver.cpp:237]     Train net output #0: loss = 4.76955 (* 1 = 4.76955 loss)
I0405 15:09:47.030131 18799 sgd_solver.cpp:105] Iteration 15936, lr = 0.0001
I0405 15:09:47.030447 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:09:52.180282 18799 solver.cpp:218] Iteration 15948 (2.33005 iter/s, 5.15011s/12 iters), loss = 4.8399
I0405 15:09:52.180335 18799 solver.cpp:237]     Train net output #0: loss = 4.8399 (* 1 = 4.8399 loss)
I0405 15:09:52.180342 18799 sgd_solver.cpp:105] Iteration 15948, lr = 0.0001
I0405 15:09:57.279399 18799 solver.cpp:218] Iteration 15960 (2.35339 iter/s, 5.09902s/12 iters), loss = 4.75686
I0405 15:09:57.279440 18799 solver.cpp:237]     Train net output #0: loss = 4.75686 (* 1 = 4.75686 loss)
I0405 15:09:57.279446 18799 sgd_solver.cpp:105] Iteration 15960, lr = 0.0001
I0405 15:10:02.554394 18799 solver.cpp:218] Iteration 15972 (2.27492 iter/s, 5.27491s/12 iters), loss = 4.63743
I0405 15:10:02.554433 18799 solver.cpp:237]     Train net output #0: loss = 4.63743 (* 1 = 4.63743 loss)
I0405 15:10:02.554438 18799 sgd_solver.cpp:105] Iteration 15972, lr = 0.0001
I0405 15:10:06.929374 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:10:08.074687 18799 solver.cpp:218] Iteration 15984 (2.17383 iter/s, 5.52021s/12 iters), loss = 4.61674
I0405 15:10:08.074731 18799 solver.cpp:237]     Train net output #0: loss = 4.61674 (* 1 = 4.61674 loss)
I0405 15:10:08.074738 18799 sgd_solver.cpp:105] Iteration 15984, lr = 0.0001
I0405 15:10:13.349653 18799 solver.cpp:218] Iteration 15996 (2.27493 iter/s, 5.27488s/12 iters), loss = 4.77128
I0405 15:10:13.349747 18799 solver.cpp:237]     Train net output #0: loss = 4.77128 (* 1 = 4.77128 loss)
I0405 15:10:13.349754 18799 sgd_solver.cpp:105] Iteration 15996, lr = 0.0001
I0405 15:10:18.630947 18799 solver.cpp:218] Iteration 16008 (2.27223 iter/s, 5.28116s/12 iters), loss = 4.65651
I0405 15:10:18.631002 18799 solver.cpp:237]     Train net output #0: loss = 4.65651 (* 1 = 4.65651 loss)
I0405 15:10:18.631011 18799 sgd_solver.cpp:105] Iteration 16008, lr = 0.0001
I0405 15:10:20.778301 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16014.caffemodel
I0405 15:10:23.862788 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16014.solverstate
I0405 15:10:26.210696 18799 solver.cpp:330] Iteration 16014, Testing net (#0)
I0405 15:10:26.210714 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:10:28.939296 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:10:30.585984 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0471814
I0405 15:10:30.586020 18799 solver.cpp:397]     Test net output #1: loss = 4.79782 (* 1 = 4.79782 loss)
I0405 15:10:32.573066 18799 solver.cpp:218] Iteration 16020 (0.86071 iter/s, 13.942s/12 iters), loss = 4.66172
I0405 15:10:32.573109 18799 solver.cpp:237]     Train net output #0: loss = 4.66172 (* 1 = 4.66172 loss)
I0405 15:10:32.573114 18799 sgd_solver.cpp:105] Iteration 16020, lr = 0.0001
I0405 15:10:38.134531 18799 solver.cpp:218] Iteration 16032 (2.15774 iter/s, 5.56137s/12 iters), loss = 4.71339
I0405 15:10:38.134579 18799 solver.cpp:237]     Train net output #0: loss = 4.71339 (* 1 = 4.71339 loss)
I0405 15:10:38.134588 18799 sgd_solver.cpp:105] Iteration 16032, lr = 0.0001
I0405 15:10:43.486977 18799 solver.cpp:218] Iteration 16044 (2.242 iter/s, 5.35235s/12 iters), loss = 4.57181
I0405 15:10:43.487087 18799 solver.cpp:237]     Train net output #0: loss = 4.57181 (* 1 = 4.57181 loss)
I0405 15:10:43.487095 18799 sgd_solver.cpp:105] Iteration 16044, lr = 0.0001
I0405 15:10:48.905890 18799 solver.cpp:218] Iteration 16056 (2.21453 iter/s, 5.41876s/12 iters), loss = 4.70337
I0405 15:10:48.905938 18799 solver.cpp:237]     Train net output #0: loss = 4.70337 (* 1 = 4.70337 loss)
I0405 15:10:48.905946 18799 sgd_solver.cpp:105] Iteration 16056, lr = 0.0001
I0405 15:10:54.188660 18799 solver.cpp:218] Iteration 16068 (2.27157 iter/s, 5.28268s/12 iters), loss = 4.58418
I0405 15:10:54.188714 18799 solver.cpp:237]     Train net output #0: loss = 4.58418 (* 1 = 4.58418 loss)
I0405 15:10:54.188724 18799 sgd_solver.cpp:105] Iteration 16068, lr = 0.0001
I0405 15:10:59.426856 18799 solver.cpp:218] Iteration 16080 (2.29091 iter/s, 5.2381s/12 iters), loss = 4.79965
I0405 15:10:59.426908 18799 solver.cpp:237]     Train net output #0: loss = 4.79965 (* 1 = 4.79965 loss)
I0405 15:10:59.426916 18799 sgd_solver.cpp:105] Iteration 16080, lr = 0.0001
I0405 15:11:00.516527 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:04.715047 18799 solver.cpp:218] Iteration 16092 (2.26925 iter/s, 5.28809s/12 iters), loss = 4.61704
I0405 15:11:04.715098 18799 solver.cpp:237]     Train net output #0: loss = 4.61704 (* 1 = 4.61704 loss)
I0405 15:11:04.715106 18799 sgd_solver.cpp:105] Iteration 16092, lr = 0.0001
I0405 15:11:10.082127 18799 solver.cpp:218] Iteration 16104 (2.23589 iter/s, 5.36699s/12 iters), loss = 4.7664
I0405 15:11:10.082171 18799 solver.cpp:237]     Train net output #0: loss = 4.7664 (* 1 = 4.7664 loss)
I0405 15:11:10.082178 18799 sgd_solver.cpp:105] Iteration 16104, lr = 0.0001
I0405 15:11:15.101289 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16116.caffemodel
I0405 15:11:18.124133 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16116.solverstate
I0405 15:11:20.512181 18799 solver.cpp:330] Iteration 16116, Testing net (#0)
I0405 15:11:20.512204 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:11:23.209983 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:24.951058 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0490196
I0405 15:11:24.951093 18799 solver.cpp:397]     Test net output #1: loss = 4.79661 (* 1 = 4.79661 loss)
I0405 15:11:25.093047 18799 solver.cpp:218] Iteration 16116 (0.799425 iter/s, 15.0108s/12 iters), loss = 4.77069
I0405 15:11:25.094655 18799 solver.cpp:237]     Train net output #0: loss = 4.77069 (* 1 = 4.77069 loss)
I0405 15:11:25.094668 18799 sgd_solver.cpp:105] Iteration 16116, lr = 0.0001
I0405 15:11:29.466603 18799 solver.cpp:218] Iteration 16128 (2.74479 iter/s, 4.37192s/12 iters), loss = 4.49904
I0405 15:11:29.466643 18799 solver.cpp:237]     Train net output #0: loss = 4.49904 (* 1 = 4.49904 loss)
I0405 15:11:29.466650 18799 sgd_solver.cpp:105] Iteration 16128, lr = 0.0001
I0405 15:11:34.846243 18799 solver.cpp:218] Iteration 16140 (2.23067 iter/s, 5.37956s/12 iters), loss = 4.68115
I0405 15:11:34.846282 18799 solver.cpp:237]     Train net output #0: loss = 4.68115 (* 1 = 4.68115 loss)
I0405 15:11:34.846287 18799 sgd_solver.cpp:105] Iteration 16140, lr = 0.0001
I0405 15:11:40.033043 18799 solver.cpp:218] Iteration 16152 (2.3136 iter/s, 5.18672s/12 iters), loss = 4.61179
I0405 15:11:40.033085 18799 solver.cpp:237]     Train net output #0: loss = 4.61179 (* 1 = 4.61179 loss)
I0405 15:11:40.033092 18799 sgd_solver.cpp:105] Iteration 16152, lr = 0.0001
I0405 15:11:45.531183 18799 solver.cpp:218] Iteration 16164 (2.18259 iter/s, 5.49805s/12 iters), loss = 4.57879
I0405 15:11:45.531265 18799 solver.cpp:237]     Train net output #0: loss = 4.57879 (* 1 = 4.57879 loss)
I0405 15:11:45.531270 18799 sgd_solver.cpp:105] Iteration 16164, lr = 0.0001
I0405 15:11:50.945199 18799 solver.cpp:218] Iteration 16176 (2.21652 iter/s, 5.41389s/12 iters), loss = 4.67728
I0405 15:11:50.945242 18799 solver.cpp:237]     Train net output #0: loss = 4.67728 (* 1 = 4.67728 loss)
I0405 15:11:50.945248 18799 sgd_solver.cpp:105] Iteration 16176, lr = 0.0001
I0405 15:11:54.331019 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:56.292156 18799 solver.cpp:218] Iteration 16188 (2.2443 iter/s, 5.34687s/12 iters), loss = 4.5333
I0405 15:11:56.292204 18799 solver.cpp:237]     Train net output #0: loss = 4.5333 (* 1 = 4.5333 loss)
I0405 15:11:56.292210 18799 sgd_solver.cpp:105] Iteration 16188, lr = 0.0001
I0405 15:12:01.559391 18799 solver.cpp:218] Iteration 16200 (2.27827 iter/s, 5.26715s/12 iters), loss = 4.66523
I0405 15:12:01.559430 18799 solver.cpp:237]     Train net output #0: loss = 4.66523 (* 1 = 4.66523 loss)
I0405 15:12:01.559435 18799 sgd_solver.cpp:105] Iteration 16200, lr = 0.0001
I0405 15:12:06.771545 18799 solver.cpp:218] Iteration 16212 (2.30235 iter/s, 5.21207s/12 iters), loss = 4.72147
I0405 15:12:06.771589 18799 solver.cpp:237]     Train net output #0: loss = 4.72147 (* 1 = 4.72147 loss)
I0405 15:12:06.771595 18799 sgd_solver.cpp:105] Iteration 16212, lr = 0.0001
I0405 15:12:08.831219 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16218.caffemodel
I0405 15:12:11.852697 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16218.solverstate
I0405 15:12:14.151623 18799 solver.cpp:330] Iteration 16218, Testing net (#0)
I0405 15:12:14.151639 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:12:16.807730 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:12:18.530375 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0508578
I0405 15:12:18.530408 18799 solver.cpp:397]     Test net output #1: loss = 4.79836 (* 1 = 4.79836 loss)
I0405 15:12:20.593364 18799 solver.cpp:218] Iteration 16224 (0.868201 iter/s, 13.8217s/12 iters), loss = 4.62166
I0405 15:12:20.593407 18799 solver.cpp:237]     Train net output #0: loss = 4.62166 (* 1 = 4.62166 loss)
I0405 15:12:20.593413 18799 sgd_solver.cpp:105] Iteration 16224, lr = 0.0001
I0405 15:12:25.802094 18799 solver.cpp:218] Iteration 16236 (2.30386 iter/s, 5.20864s/12 iters), loss = 4.80967
I0405 15:12:25.802136 18799 solver.cpp:237]     Train net output #0: loss = 4.80967 (* 1 = 4.80967 loss)
I0405 15:12:25.802141 18799 sgd_solver.cpp:105] Iteration 16236, lr = 0.0001
I0405 15:12:31.074067 18799 solver.cpp:218] Iteration 16248 (2.27622 iter/s, 5.27189s/12 iters), loss = 4.56967
I0405 15:12:31.074106 18799 solver.cpp:237]     Train net output #0: loss = 4.56967 (* 1 = 4.56967 loss)
I0405 15:12:31.074111 18799 sgd_solver.cpp:105] Iteration 16248, lr = 0.0001
I0405 15:12:36.122529 18799 solver.cpp:218] Iteration 16260 (2.377 iter/s, 5.04838s/12 iters), loss = 4.58876
I0405 15:12:36.122568 18799 solver.cpp:237]     Train net output #0: loss = 4.58876 (* 1 = 4.58876 loss)
I0405 15:12:36.122575 18799 sgd_solver.cpp:105] Iteration 16260, lr = 0.0001
I0405 15:12:41.000604 18799 solver.cpp:218] Iteration 16272 (2.46003 iter/s, 4.87799s/12 iters), loss = 4.74161
I0405 15:12:41.000651 18799 solver.cpp:237]     Train net output #0: loss = 4.74161 (* 1 = 4.74161 loss)
I0405 15:12:41.000656 18799 sgd_solver.cpp:105] Iteration 16272, lr = 0.0001
I0405 15:12:46.382076 18799 solver.cpp:218] Iteration 16284 (2.22991 iter/s, 5.38138s/12 iters), loss = 4.58293
I0405 15:12:46.382124 18799 solver.cpp:237]     Train net output #0: loss = 4.58293 (* 1 = 4.58293 loss)
I0405 15:12:46.382133 18799 sgd_solver.cpp:105] Iteration 16284, lr = 0.0001
I0405 15:12:46.805891 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:12:51.728535 18799 solver.cpp:218] Iteration 16296 (2.24452 iter/s, 5.34637s/12 iters), loss = 4.63862
I0405 15:12:51.728654 18799 solver.cpp:237]     Train net output #0: loss = 4.63862 (* 1 = 4.63862 loss)
I0405 15:12:51.728664 18799 sgd_solver.cpp:105] Iteration 16296, lr = 0.0001
I0405 15:12:56.846611 18799 solver.cpp:218] Iteration 16308 (2.3447 iter/s, 5.11792s/12 iters), loss = 4.74259
I0405 15:12:56.846652 18799 solver.cpp:237]     Train net output #0: loss = 4.74259 (* 1 = 4.74259 loss)
I0405 15:12:56.846657 18799 sgd_solver.cpp:105] Iteration 16308, lr = 0.0001
I0405 15:13:01.734143 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16320.caffemodel
I0405 15:13:04.723804 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16320.solverstate
I0405 15:13:07.026894 18799 solver.cpp:330] Iteration 16320, Testing net (#0)
I0405 15:13:07.026921 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:13:09.671737 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:13:11.596716 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0508578
I0405 15:13:11.596760 18799 solver.cpp:397]     Test net output #1: loss = 4.78839 (* 1 = 4.78839 loss)
I0405 15:13:11.735575 18799 solver.cpp:218] Iteration 16320 (0.805973 iter/s, 14.8888s/12 iters), loss = 4.69473
I0405 15:13:11.735625 18799 solver.cpp:237]     Train net output #0: loss = 4.69473 (* 1 = 4.69473 loss)
I0405 15:13:11.735631 18799 sgd_solver.cpp:105] Iteration 16320, lr = 0.0001
I0405 15:13:16.091706 18799 solver.cpp:218] Iteration 16332 (2.75479 iter/s, 4.35605s/12 iters), loss = 4.69128
I0405 15:13:16.091749 18799 solver.cpp:237]     Train net output #0: loss = 4.69128 (* 1 = 4.69128 loss)
I0405 15:13:16.091755 18799 sgd_solver.cpp:105] Iteration 16332, lr = 0.0001
I0405 15:13:21.356552 18799 solver.cpp:218] Iteration 16344 (2.27931 iter/s, 5.26476s/12 iters), loss = 4.62637
I0405 15:13:21.356593 18799 solver.cpp:237]     Train net output #0: loss = 4.62637 (* 1 = 4.62637 loss)
I0405 15:13:21.356598 18799 sgd_solver.cpp:105] Iteration 16344, lr = 0.0001
I0405 15:13:26.432458 18799 solver.cpp:218] Iteration 16356 (2.36415 iter/s, 5.07582s/12 iters), loss = 4.51793
I0405 15:13:26.432615 18799 solver.cpp:237]     Train net output #0: loss = 4.51793 (* 1 = 4.51793 loss)
I0405 15:13:26.432622 18799 sgd_solver.cpp:105] Iteration 16356, lr = 0.0001
I0405 15:13:31.749374 18799 solver.cpp:218] Iteration 16368 (2.25703 iter/s, 5.31672s/12 iters), loss = 4.75471
I0405 15:13:31.749425 18799 solver.cpp:237]     Train net output #0: loss = 4.75471 (* 1 = 4.75471 loss)
I0405 15:13:31.749433 18799 sgd_solver.cpp:105] Iteration 16368, lr = 0.0001
I0405 15:13:37.084180 18799 solver.cpp:218] Iteration 16380 (2.24942 iter/s, 5.33472s/12 iters), loss = 4.54582
I0405 15:13:37.084216 18799 solver.cpp:237]     Train net output #0: loss = 4.54582 (* 1 = 4.54582 loss)
I0405 15:13:37.084221 18799 sgd_solver.cpp:105] Iteration 16380, lr = 0.0001
I0405 15:13:39.863947 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:13:42.459205 18799 solver.cpp:218] Iteration 16392 (2.23258 iter/s, 5.37494s/12 iters), loss = 4.65193
I0405 15:13:42.459254 18799 solver.cpp:237]     Train net output #0: loss = 4.65193 (* 1 = 4.65193 loss)
I0405 15:13:42.459261 18799 sgd_solver.cpp:105] Iteration 16392, lr = 0.0001
I0405 15:13:47.769309 18799 solver.cpp:218] Iteration 16404 (2.25988 iter/s, 5.31001s/12 iters), loss = 4.64072
I0405 15:13:47.769357 18799 solver.cpp:237]     Train net output #0: loss = 4.64072 (* 1 = 4.64072 loss)
I0405 15:13:47.769362 18799 sgd_solver.cpp:105] Iteration 16404, lr = 0.0001
I0405 15:13:53.117854 18799 solver.cpp:218] Iteration 16416 (2.24364 iter/s, 5.34845s/12 iters), loss = 4.56189
I0405 15:13:53.117906 18799 solver.cpp:237]     Train net output #0: loss = 4.56189 (* 1 = 4.56189 loss)
I0405 15:13:53.117914 18799 sgd_solver.cpp:105] Iteration 16416, lr = 0.0001
I0405 15:13:55.199450 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16422.caffemodel
I0405 15:13:58.244724 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16422.solverstate
I0405 15:14:00.554396 18799 solver.cpp:330] Iteration 16422, Testing net (#0)
I0405 15:14:00.554419 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:14:03.102205 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:14:04.932355 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0477941
I0405 15:14:04.932389 18799 solver.cpp:397]     Test net output #1: loss = 4.78523 (* 1 = 4.78523 loss)
I0405 15:14:06.867672 18799 solver.cpp:218] Iteration 16428 (0.872747 iter/s, 13.7497s/12 iters), loss = 4.59548
I0405 15:14:06.867717 18799 solver.cpp:237]     Train net output #0: loss = 4.59548 (* 1 = 4.59548 loss)
I0405 15:14:06.867722 18799 sgd_solver.cpp:105] Iteration 16428, lr = 0.0001
I0405 15:14:12.111202 18799 solver.cpp:218] Iteration 16440 (2.28857 iter/s, 5.24344s/12 iters), loss = 4.6739
I0405 15:14:12.111243 18799 solver.cpp:237]     Train net output #0: loss = 4.6739 (* 1 = 4.6739 loss)
I0405 15:14:12.111248 18799 sgd_solver.cpp:105] Iteration 16440, lr = 0.0001
I0405 15:14:17.382627 18799 solver.cpp:218] Iteration 16452 (2.27646 iter/s, 5.27134s/12 iters), loss = 4.67653
I0405 15:14:17.382668 18799 solver.cpp:237]     Train net output #0: loss = 4.67653 (* 1 = 4.67653 loss)
I0405 15:14:17.382673 18799 sgd_solver.cpp:105] Iteration 16452, lr = 0.0001
I0405 15:14:22.774860 18799 solver.cpp:218] Iteration 16464 (2.22546 iter/s, 5.39215s/12 iters), loss = 4.5809
I0405 15:14:22.774900 18799 solver.cpp:237]     Train net output #0: loss = 4.5809 (* 1 = 4.5809 loss)
I0405 15:14:22.774905 18799 sgd_solver.cpp:105] Iteration 16464, lr = 0.0001
I0405 15:14:28.123534 18799 solver.cpp:218] Iteration 16476 (2.24358 iter/s, 5.34859s/12 iters), loss = 4.54154
I0405 15:14:28.123581 18799 solver.cpp:237]     Train net output #0: loss = 4.54154 (* 1 = 4.54154 loss)
I0405 15:14:28.123589 18799 sgd_solver.cpp:105] Iteration 16476, lr = 0.0001
I0405 15:14:33.255568 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:14:33.560127 18799 solver.cpp:218] Iteration 16488 (2.2073 iter/s, 5.4365s/12 iters), loss = 4.61669
I0405 15:14:33.560185 18799 solver.cpp:237]     Train net output #0: loss = 4.61669 (* 1 = 4.61669 loss)
I0405 15:14:33.560192 18799 sgd_solver.cpp:105] Iteration 16488, lr = 0.0001
I0405 15:14:38.898576 18799 solver.cpp:218] Iteration 16500 (2.24789 iter/s, 5.33835s/12 iters), loss = 4.65961
I0405 15:14:38.898622 18799 solver.cpp:237]     Train net output #0: loss = 4.65961 (* 1 = 4.65961 loss)
I0405 15:14:38.898630 18799 sgd_solver.cpp:105] Iteration 16500, lr = 0.0001
I0405 15:14:44.066330 18799 solver.cpp:218] Iteration 16512 (2.32213 iter/s, 5.16766s/12 iters), loss = 4.47251
I0405 15:14:44.066373 18799 solver.cpp:237]     Train net output #0: loss = 4.47251 (* 1 = 4.47251 loss)
I0405 15:14:44.066380 18799 sgd_solver.cpp:105] Iteration 16512, lr = 0.0001
I0405 15:14:48.837774 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16524.caffemodel
I0405 15:14:52.926069 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16524.solverstate
I0405 15:14:55.286172 18799 solver.cpp:330] Iteration 16524, Testing net (#0)
I0405 15:14:55.286195 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:14:57.711009 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:14:59.545668 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0526961
I0405 15:14:59.545711 18799 solver.cpp:397]     Test net output #1: loss = 4.77879 (* 1 = 4.77879 loss)
I0405 15:14:59.687351 18799 solver.cpp:218] Iteration 16524 (0.768203 iter/s, 15.6209s/12 iters), loss = 4.5841
I0405 15:14:59.687412 18799 solver.cpp:237]     Train net output #0: loss = 4.5841 (* 1 = 4.5841 loss)
I0405 15:14:59.687419 18799 sgd_solver.cpp:105] Iteration 16524, lr = 0.0001
I0405 15:15:03.889051 18799 solver.cpp:218] Iteration 16536 (2.85605 iter/s, 4.2016s/12 iters), loss = 4.56643
I0405 15:15:03.889160 18799 solver.cpp:237]     Train net output #0: loss = 4.56643 (* 1 = 4.56643 loss)
I0405 15:15:03.889168 18799 sgd_solver.cpp:105] Iteration 16536, lr = 0.0001
I0405 15:15:09.049367 18799 solver.cpp:218] Iteration 16548 (2.3255 iter/s, 5.16017s/12 iters), loss = 4.64987
I0405 15:15:09.049405 18799 solver.cpp:237]     Train net output #0: loss = 4.64987 (* 1 = 4.64987 loss)
I0405 15:15:09.049412 18799 sgd_solver.cpp:105] Iteration 16548, lr = 0.0001
I0405 15:15:14.268504 18799 solver.cpp:218] Iteration 16560 (2.29927 iter/s, 5.21906s/12 iters), loss = 4.61059
I0405 15:15:14.268541 18799 solver.cpp:237]     Train net output #0: loss = 4.61059 (* 1 = 4.61059 loss)
I0405 15:15:14.268546 18799 sgd_solver.cpp:105] Iteration 16560, lr = 0.0001
I0405 15:15:19.466143 18799 solver.cpp:218] Iteration 16572 (2.30878 iter/s, 5.19755s/12 iters), loss = 4.54076
I0405 15:15:19.466208 18799 solver.cpp:237]     Train net output #0: loss = 4.54076 (* 1 = 4.54076 loss)
I0405 15:15:19.466217 18799 sgd_solver.cpp:105] Iteration 16572, lr = 0.0001
I0405 15:15:24.928469 18799 solver.cpp:218] Iteration 16584 (2.19691 iter/s, 5.46222s/12 iters), loss = 4.61493
I0405 15:15:24.928526 18799 solver.cpp:237]     Train net output #0: loss = 4.61493 (* 1 = 4.61493 loss)
I0405 15:15:24.928534 18799 sgd_solver.cpp:105] Iteration 16584, lr = 0.0001
I0405 15:15:26.911190 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:15:30.444438 18799 solver.cpp:218] Iteration 16596 (2.17554 iter/s, 5.51587s/12 iters), loss = 4.62902
I0405 15:15:30.444476 18799 solver.cpp:237]     Train net output #0: loss = 4.62902 (* 1 = 4.62902 loss)
I0405 15:15:30.444483 18799 sgd_solver.cpp:105] Iteration 16596, lr = 0.0001
I0405 15:15:35.624048 18799 solver.cpp:218] Iteration 16608 (2.31681 iter/s, 5.17953s/12 iters), loss = 4.64048
I0405 15:15:35.624219 18799 solver.cpp:237]     Train net output #0: loss = 4.64048 (* 1 = 4.64048 loss)
I0405 15:15:35.624228 18799 sgd_solver.cpp:105] Iteration 16608, lr = 0.0001
I0405 15:15:40.725009 18799 solver.cpp:218] Iteration 16620 (2.35259 iter/s, 5.10075s/12 iters), loss = 4.54966
I0405 15:15:40.725064 18799 solver.cpp:237]     Train net output #0: loss = 4.54966 (* 1 = 4.54966 loss)
I0405 15:15:40.725072 18799 sgd_solver.cpp:105] Iteration 16620, lr = 0.0001
I0405 15:15:42.847463 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16626.caffemodel
I0405 15:15:45.980991 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16626.solverstate
I0405 15:15:48.457485 18799 solver.cpp:330] Iteration 16626, Testing net (#0)
I0405 15:15:48.457510 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:15:50.943682 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:15:52.205209 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:15:52.825227 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0508578
I0405 15:15:52.825263 18799 solver.cpp:397]     Test net output #1: loss = 4.76893 (* 1 = 4.76893 loss)
I0405 15:15:54.765331 18799 solver.cpp:218] Iteration 16632 (0.854689 iter/s, 14.0402s/12 iters), loss = 4.51489
I0405 15:15:54.765377 18799 solver.cpp:237]     Train net output #0: loss = 4.51489 (* 1 = 4.51489 loss)
I0405 15:15:54.765383 18799 sgd_solver.cpp:105] Iteration 16632, lr = 0.0001
I0405 15:15:59.932857 18799 solver.cpp:218] Iteration 16644 (2.32223 iter/s, 5.16744s/12 iters), loss = 4.66138
I0405 15:15:59.932922 18799 solver.cpp:237]     Train net output #0: loss = 4.66138 (* 1 = 4.66138 loss)
I0405 15:15:59.932932 18799 sgd_solver.cpp:105] Iteration 16644, lr = 0.0001
I0405 15:16:05.237828 18799 solver.cpp:218] Iteration 16656 (2.26207 iter/s, 5.30487s/12 iters), loss = 4.63256
I0405 15:16:05.237879 18799 solver.cpp:237]     Train net output #0: loss = 4.63256 (* 1 = 4.63256 loss)
I0405 15:16:05.237886 18799 sgd_solver.cpp:105] Iteration 16656, lr = 0.0001
I0405 15:16:10.538352 18799 solver.cpp:218] Iteration 16668 (2.26397 iter/s, 5.30043s/12 iters), loss = 4.67891
I0405 15:16:10.538440 18799 solver.cpp:237]     Train net output #0: loss = 4.67891 (* 1 = 4.67891 loss)
I0405 15:16:10.538447 18799 sgd_solver.cpp:105] Iteration 16668, lr = 0.0001
I0405 15:16:15.700237 18799 solver.cpp:218] Iteration 16680 (2.32479 iter/s, 5.16175s/12 iters), loss = 4.57367
I0405 15:16:15.700297 18799 solver.cpp:237]     Train net output #0: loss = 4.57367 (* 1 = 4.57367 loss)
I0405 15:16:15.700306 18799 sgd_solver.cpp:105] Iteration 16680, lr = 0.0001
I0405 15:16:19.871347 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:16:20.943058 18799 solver.cpp:218] Iteration 16692 (2.28889 iter/s, 5.24272s/12 iters), loss = 4.56459
I0405 15:16:20.943112 18799 solver.cpp:237]     Train net output #0: loss = 4.56459 (* 1 = 4.56459 loss)
I0405 15:16:20.943120 18799 sgd_solver.cpp:105] Iteration 16692, lr = 0.0001
I0405 15:16:26.213513 18799 solver.cpp:218] Iteration 16704 (2.27688 iter/s, 5.27037s/12 iters), loss = 4.76428
I0405 15:16:26.213549 18799 solver.cpp:237]     Train net output #0: loss = 4.76428 (* 1 = 4.76428 loss)
I0405 15:16:26.213554 18799 sgd_solver.cpp:105] Iteration 16704, lr = 0.0001
I0405 15:16:31.445019 18799 solver.cpp:218] Iteration 16716 (2.29383 iter/s, 5.23143s/12 iters), loss = 4.6089
I0405 15:16:31.445075 18799 solver.cpp:237]     Train net output #0: loss = 4.6089 (* 1 = 4.6089 loss)
I0405 15:16:31.445084 18799 sgd_solver.cpp:105] Iteration 16716, lr = 0.0001
I0405 15:16:36.301964 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16728.caffemodel
I0405 15:16:39.444684 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16728.solverstate
I0405 15:16:41.768344 18799 solver.cpp:330] Iteration 16728, Testing net (#0)
I0405 15:16:41.768446 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:16:44.165074 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:16:46.077591 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0508578
I0405 15:16:46.077623 18799 solver.cpp:397]     Test net output #1: loss = 4.76565 (* 1 = 4.76565 loss)
I0405 15:16:46.219760 18799 solver.cpp:218] Iteration 16728 (0.812204 iter/s, 14.7746s/12 iters), loss = 4.54155
I0405 15:16:46.219821 18799 solver.cpp:237]     Train net output #0: loss = 4.54155 (* 1 = 4.54155 loss)
I0405 15:16:46.219830 18799 sgd_solver.cpp:105] Iteration 16728, lr = 0.0001
I0405 15:16:50.618619 18799 solver.cpp:218] Iteration 16740 (2.72804 iter/s, 4.39877s/12 iters), loss = 4.5931
I0405 15:16:50.618656 18799 solver.cpp:237]     Train net output #0: loss = 4.5931 (* 1 = 4.5931 loss)
I0405 15:16:50.618661 18799 sgd_solver.cpp:105] Iteration 16740, lr = 0.0001
I0405 15:16:56.096931 18799 solver.cpp:218] Iteration 16752 (2.19049 iter/s, 5.47823s/12 iters), loss = 4.59135
I0405 15:16:56.096976 18799 solver.cpp:237]     Train net output #0: loss = 4.59135 (* 1 = 4.59135 loss)
I0405 15:16:56.096982 18799 sgd_solver.cpp:105] Iteration 16752, lr = 0.0001
I0405 15:17:01.401933 18799 solver.cpp:218] Iteration 16764 (2.26205 iter/s, 5.30492s/12 iters), loss = 4.55693
I0405 15:17:01.401974 18799 solver.cpp:237]     Train net output #0: loss = 4.55693 (* 1 = 4.55693 loss)
I0405 15:17:01.401979 18799 sgd_solver.cpp:105] Iteration 16764, lr = 0.0001
I0405 15:17:06.465054 18799 solver.cpp:218] Iteration 16776 (2.37012 iter/s, 5.06304s/12 iters), loss = 4.57091
I0405 15:17:06.465109 18799 solver.cpp:237]     Train net output #0: loss = 4.57091 (* 1 = 4.57091 loss)
I0405 15:17:06.465117 18799 sgd_solver.cpp:105] Iteration 16776, lr = 0.0001
I0405 15:17:11.846352 18799 solver.cpp:218] Iteration 16788 (2.22998 iter/s, 5.38121s/12 iters), loss = 4.68109
I0405 15:17:11.846489 18799 solver.cpp:237]     Train net output #0: loss = 4.68109 (* 1 = 4.68109 loss)
I0405 15:17:11.846498 18799 sgd_solver.cpp:105] Iteration 16788, lr = 0.0001
I0405 15:17:12.956279 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:17:17.259171 18799 solver.cpp:218] Iteration 16800 (2.21703 iter/s, 5.41265s/12 iters), loss = 4.59842
I0405 15:17:17.259207 18799 solver.cpp:237]     Train net output #0: loss = 4.59842 (* 1 = 4.59842 loss)
I0405 15:17:17.259212 18799 sgd_solver.cpp:105] Iteration 16800, lr = 0.0001
I0405 15:17:22.779776 18799 solver.cpp:218] Iteration 16812 (2.1737 iter/s, 5.52053s/12 iters), loss = 4.60099
I0405 15:17:22.779826 18799 solver.cpp:237]     Train net output #0: loss = 4.60099 (* 1 = 4.60099 loss)
I0405 15:17:22.779834 18799 sgd_solver.cpp:105] Iteration 16812, lr = 0.0001
I0405 15:17:28.258225 18799 solver.cpp:218] Iteration 16824 (2.19044 iter/s, 5.47836s/12 iters), loss = 4.58126
I0405 15:17:28.258281 18799 solver.cpp:237]     Train net output #0: loss = 4.58126 (* 1 = 4.58126 loss)
I0405 15:17:28.258289 18799 sgd_solver.cpp:105] Iteration 16824, lr = 0.0001
I0405 15:17:30.404382 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16830.caffemodel
I0405 15:17:33.519474 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16830.solverstate
I0405 15:17:35.912405 18799 solver.cpp:330] Iteration 16830, Testing net (#0)
I0405 15:17:35.912428 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:17:38.251087 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:17:40.398648 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0588235
I0405 15:17:40.398681 18799 solver.cpp:397]     Test net output #1: loss = 4.75583 (* 1 = 4.75583 loss)
I0405 15:17:42.334429 18799 solver.cpp:218] Iteration 16836 (0.85251 iter/s, 14.0761s/12 iters), loss = 4.65882
I0405 15:17:42.334539 18799 solver.cpp:237]     Train net output #0: loss = 4.65882 (* 1 = 4.65882 loss)
I0405 15:17:42.334545 18799 sgd_solver.cpp:105] Iteration 16836, lr = 0.0001
I0405 15:17:47.765722 18799 solver.cpp:218] Iteration 16848 (2.20948 iter/s, 5.43114s/12 iters), loss = 4.59641
I0405 15:17:47.765777 18799 solver.cpp:237]     Train net output #0: loss = 4.59641 (* 1 = 4.59641 loss)
I0405 15:17:47.765785 18799 sgd_solver.cpp:105] Iteration 16848, lr = 0.0001
I0405 15:17:52.860462 18799 solver.cpp:218] Iteration 16860 (2.35541 iter/s, 5.09465s/12 iters), loss = 4.70284
I0405 15:17:52.860508 18799 solver.cpp:237]     Train net output #0: loss = 4.70284 (* 1 = 4.70284 loss)
I0405 15:17:52.860517 18799 sgd_solver.cpp:105] Iteration 16860, lr = 0.0001
I0405 15:17:58.052057 18799 solver.cpp:218] Iteration 16872 (2.31146 iter/s, 5.19152s/12 iters), loss = 4.50253
I0405 15:17:58.052091 18799 solver.cpp:237]     Train net output #0: loss = 4.50253 (* 1 = 4.50253 loss)
I0405 15:17:58.052098 18799 sgd_solver.cpp:105] Iteration 16872, lr = 0.0001
I0405 15:18:03.269683 18799 solver.cpp:218] Iteration 16884 (2.29993 iter/s, 5.21755s/12 iters), loss = 4.46885
I0405 15:18:03.269734 18799 solver.cpp:237]     Train net output #0: loss = 4.46885 (* 1 = 4.46885 loss)
I0405 15:18:03.269742 18799 sgd_solver.cpp:105] Iteration 16884, lr = 0.0001
I0405 15:18:06.750901 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:18:08.580080 18799 solver.cpp:218] Iteration 16896 (2.25976 iter/s, 5.31031s/12 iters), loss = 4.33619
I0405 15:18:08.580121 18799 solver.cpp:237]     Train net output #0: loss = 4.33619 (* 1 = 4.33619 loss)
I0405 15:18:08.580125 18799 sgd_solver.cpp:105] Iteration 16896, lr = 0.0001
I0405 15:18:13.942534 18799 solver.cpp:218] Iteration 16908 (2.23781 iter/s, 5.36238s/12 iters), loss = 4.63159
I0405 15:18:13.942641 18799 solver.cpp:237]     Train net output #0: loss = 4.63159 (* 1 = 4.63159 loss)
I0405 15:18:13.942646 18799 sgd_solver.cpp:105] Iteration 16908, lr = 0.0001
I0405 15:18:19.212865 18799 solver.cpp:218] Iteration 16920 (2.27696 iter/s, 5.27019s/12 iters), loss = 4.62349
I0405 15:18:19.212924 18799 solver.cpp:237]     Train net output #0: loss = 4.62349 (* 1 = 4.62349 loss)
I0405 15:18:19.212931 18799 sgd_solver.cpp:105] Iteration 16920, lr = 0.0001
I0405 15:18:24.124590 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16932.caffemodel
I0405 15:18:27.165283 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16932.solverstate
I0405 15:18:29.469440 18799 solver.cpp:330] Iteration 16932, Testing net (#0)
I0405 15:18:29.469461 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:18:32.014930 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:18:34.006654 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0563725
I0405 15:18:34.006688 18799 solver.cpp:397]     Test net output #1: loss = 4.75877 (* 1 = 4.75877 loss)
I0405 15:18:34.148619 18799 solver.cpp:218] Iteration 16932 (0.803448 iter/s, 14.9356s/12 iters), loss = 4.53965
I0405 15:18:34.148684 18799 solver.cpp:237]     Train net output #0: loss = 4.53965 (* 1 = 4.53965 loss)
I0405 15:18:34.148690 18799 sgd_solver.cpp:105] Iteration 16932, lr = 0.0001
I0405 15:18:38.512042 18799 solver.cpp:218] Iteration 16944 (2.7502 iter/s, 4.36332s/12 iters), loss = 4.77894
I0405 15:18:38.512092 18799 solver.cpp:237]     Train net output #0: loss = 4.77894 (* 1 = 4.77894 loss)
I0405 15:18:38.512101 18799 sgd_solver.cpp:105] Iteration 16944, lr = 0.0001
I0405 15:18:43.868230 18799 solver.cpp:218] Iteration 16956 (2.24044 iter/s, 5.3561s/12 iters), loss = 4.42685
I0405 15:18:43.868275 18799 solver.cpp:237]     Train net output #0: loss = 4.42685 (* 1 = 4.42685 loss)
I0405 15:18:43.868283 18799 sgd_solver.cpp:105] Iteration 16956, lr = 0.0001
I0405 15:18:49.413244 18799 solver.cpp:218] Iteration 16968 (2.16414 iter/s, 5.54493s/12 iters), loss = 4.54665
I0405 15:18:49.413390 18799 solver.cpp:237]     Train net output #0: loss = 4.54665 (* 1 = 4.54665 loss)
I0405 15:18:49.413403 18799 sgd_solver.cpp:105] Iteration 16968, lr = 0.0001
I0405 15:18:54.838223 18799 solver.cpp:218] Iteration 16980 (2.21206 iter/s, 5.4248s/12 iters), loss = 4.63065
I0405 15:18:54.838274 18799 solver.cpp:237]     Train net output #0: loss = 4.63065 (* 1 = 4.63065 loss)
I0405 15:18:54.838282 18799 sgd_solver.cpp:105] Iteration 16980, lr = 0.0001
I0405 15:19:00.194612 18799 solver.cpp:218] Iteration 16992 (2.24035 iter/s, 5.3563s/12 iters), loss = 4.53674
I0405 15:19:00.194666 18799 solver.cpp:237]     Train net output #0: loss = 4.53674 (* 1 = 4.53674 loss)
I0405 15:19:00.194675 18799 sgd_solver.cpp:105] Iteration 16992, lr = 0.0001
I0405 15:19:00.724118 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:05.456467 18799 solver.cpp:218] Iteration 17004 (2.2806 iter/s, 5.26176s/12 iters), loss = 4.4596
I0405 15:19:05.456511 18799 solver.cpp:237]     Train net output #0: loss = 4.4596 (* 1 = 4.4596 loss)
I0405 15:19:05.456516 18799 sgd_solver.cpp:105] Iteration 17004, lr = 0.0001
I0405 15:19:10.824090 18799 solver.cpp:218] Iteration 17016 (2.23566 iter/s, 5.36753s/12 iters), loss = 4.57909
I0405 15:19:10.824147 18799 solver.cpp:237]     Train net output #0: loss = 4.57909 (* 1 = 4.57909 loss)
I0405 15:19:10.824157 18799 sgd_solver.cpp:105] Iteration 17016, lr = 0.0001
I0405 15:19:15.831769 18799 solver.cpp:218] Iteration 17028 (2.39636 iter/s, 5.00758s/12 iters), loss = 4.55008
I0405 15:19:15.831812 18799 solver.cpp:237]     Train net output #0: loss = 4.55008 (* 1 = 4.55008 loss)
I0405 15:19:15.831818 18799 sgd_solver.cpp:105] Iteration 17028, lr = 0.0001
I0405 15:19:18.049407 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17034.caffemodel
I0405 15:19:21.041352 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17034.solverstate
I0405 15:19:23.342520 18799 solver.cpp:330] Iteration 17034, Testing net (#0)
I0405 15:19:23.342540 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:19:25.654109 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:27.682126 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0563725
I0405 15:19:27.682158 18799 solver.cpp:397]     Test net output #1: loss = 4.75815 (* 1 = 4.75815 loss)
I0405 15:19:29.651880 18799 solver.cpp:218] Iteration 17040 (0.868307 iter/s, 13.82s/12 iters), loss = 4.71377
I0405 15:19:29.651924 18799 solver.cpp:237]     Train net output #0: loss = 4.71377 (* 1 = 4.71377 loss)
I0405 15:19:29.651930 18799 sgd_solver.cpp:105] Iteration 17040, lr = 0.0001
I0405 15:19:34.814132 18799 solver.cpp:218] Iteration 17052 (2.3246 iter/s, 5.16217s/12 iters), loss = 4.55459
I0405 15:19:34.814170 18799 solver.cpp:237]     Train net output #0: loss = 4.55459 (* 1 = 4.55459 loss)
I0405 15:19:34.814175 18799 sgd_solver.cpp:105] Iteration 17052, lr = 0.0001
I0405 15:19:40.315073 18799 solver.cpp:218] Iteration 17064 (2.18148 iter/s, 5.50086s/12 iters), loss = 4.27214
I0405 15:19:40.315135 18799 solver.cpp:237]     Train net output #0: loss = 4.27214 (* 1 = 4.27214 loss)
I0405 15:19:40.315143 18799 sgd_solver.cpp:105] Iteration 17064, lr = 0.0001
I0405 15:19:45.801687 18799 solver.cpp:218] Iteration 17076 (2.18718 iter/s, 5.48651s/12 iters), loss = 4.64274
I0405 15:19:45.801735 18799 solver.cpp:237]     Train net output #0: loss = 4.64274 (* 1 = 4.64274 loss)
I0405 15:19:45.801743 18799 sgd_solver.cpp:105] Iteration 17076, lr = 0.0001
I0405 15:19:51.191380 18799 solver.cpp:218] Iteration 17088 (2.22651 iter/s, 5.38961s/12 iters), loss = 4.49072
I0405 15:19:51.191468 18799 solver.cpp:237]     Train net output #0: loss = 4.49072 (* 1 = 4.49072 loss)
I0405 15:19:51.191474 18799 sgd_solver.cpp:105] Iteration 17088, lr = 0.0001
I0405 15:19:54.047231 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:56.637552 18799 solver.cpp:218] Iteration 17100 (2.20345 iter/s, 5.446s/12 iters), loss = 4.54825
I0405 15:19:56.637603 18799 solver.cpp:237]     Train net output #0: loss = 4.54825 (* 1 = 4.54825 loss)
I0405 15:19:56.637610 18799 sgd_solver.cpp:105] Iteration 17100, lr = 0.0001
I0405 15:20:02.117669 18799 solver.cpp:218] Iteration 17112 (2.18977 iter/s, 5.48003s/12 iters), loss = 4.46473
I0405 15:20:02.117712 18799 solver.cpp:237]     Train net output #0: loss = 4.46473 (* 1 = 4.46473 loss)
I0405 15:20:02.117719 18799 sgd_solver.cpp:105] Iteration 17112, lr = 0.0001
I0405 15:20:07.291990 18799 solver.cpp:218] Iteration 17124 (2.31918 iter/s, 5.17424s/12 iters), loss = 4.57853
I0405 15:20:07.292029 18799 solver.cpp:237]     Train net output #0: loss = 4.57853 (* 1 = 4.57853 loss)
I0405 15:20:07.292034 18799 sgd_solver.cpp:105] Iteration 17124, lr = 0.0001
I0405 15:20:12.073451 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17136.caffemodel
I0405 15:20:15.058804 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17136.solverstate
I0405 15:20:17.361594 18799 solver.cpp:330] Iteration 17136, Testing net (#0)
I0405 15:20:17.361611 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:20:19.632745 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:20:21.711776 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0551471
I0405 15:20:21.711881 18799 solver.cpp:397]     Test net output #1: loss = 4.74832 (* 1 = 4.74832 loss)
I0405 15:20:21.853631 18799 solver.cpp:218] Iteration 17136 (0.824089 iter/s, 14.5615s/12 iters), loss = 4.58928
I0405 15:20:21.853678 18799 solver.cpp:237]     Train net output #0: loss = 4.58928 (* 1 = 4.58928 loss)
I0405 15:20:21.853686 18799 sgd_solver.cpp:105] Iteration 17136, lr = 0.0001
I0405 15:20:26.311050 18799 solver.cpp:218] Iteration 17148 (2.69219 iter/s, 4.45734s/12 iters), loss = 4.59547
I0405 15:20:26.311091 18799 solver.cpp:237]     Train net output #0: loss = 4.59547 (* 1 = 4.59547 loss)
I0405 15:20:26.311097 18799 sgd_solver.cpp:105] Iteration 17148, lr = 0.0001
I0405 15:20:31.535142 18799 solver.cpp:218] Iteration 17160 (2.29709 iter/s, 5.22401s/12 iters), loss = 4.63139
I0405 15:20:31.535185 18799 solver.cpp:237]     Train net output #0: loss = 4.63139 (* 1 = 4.63139 loss)
I0405 15:20:31.535192 18799 sgd_solver.cpp:105] Iteration 17160, lr = 0.0001
I0405 15:20:36.892037 18799 solver.cpp:218] Iteration 17172 (2.24014 iter/s, 5.35681s/12 iters), loss = 4.4301
I0405 15:20:36.892081 18799 solver.cpp:237]     Train net output #0: loss = 4.4301 (* 1 = 4.4301 loss)
I0405 15:20:36.892086 18799 sgd_solver.cpp:105] Iteration 17172, lr = 0.0001
I0405 15:20:42.491349 18799 solver.cpp:218] Iteration 17184 (2.14315 iter/s, 5.59922s/12 iters), loss = 4.46014
I0405 15:20:42.491391 18799 solver.cpp:237]     Train net output #0: loss = 4.46014 (* 1 = 4.46014 loss)
I0405 15:20:42.491397 18799 sgd_solver.cpp:105] Iteration 17184, lr = 0.0001
I0405 15:20:47.628414 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:20:47.907161 18799 solver.cpp:218] Iteration 17196 (2.21577 iter/s, 5.41573s/12 iters), loss = 4.70426
I0405 15:20:47.907202 18799 solver.cpp:237]     Train net output #0: loss = 4.70426 (* 1 = 4.70426 loss)
I0405 15:20:47.907207 18799 sgd_solver.cpp:105] Iteration 17196, lr = 0.0001
I0405 15:20:53.322031 18799 solver.cpp:218] Iteration 17208 (2.21615 iter/s, 5.41479s/12 iters), loss = 4.47717
I0405 15:20:53.322149 18799 solver.cpp:237]     Train net output #0: loss = 4.47717 (* 1 = 4.47717 loss)
I0405 15:20:53.322158 18799 sgd_solver.cpp:105] Iteration 17208, lr = 0.0001
I0405 15:20:58.594187 18799 solver.cpp:218] Iteration 17220 (2.27618 iter/s, 5.272s/12 iters), loss = 4.40808
I0405 15:20:58.594228 18799 solver.cpp:237]     Train net output #0: loss = 4.40808 (* 1 = 4.40808 loss)
I0405 15:20:58.594233 18799 sgd_solver.cpp:105] Iteration 17220, lr = 0.0001
I0405 15:21:04.046598 18799 solver.cpp:218] Iteration 17232 (2.20089 iter/s, 5.45233s/12 iters), loss = 4.63471
I0405 15:21:04.046638 18799 solver.cpp:237]     Train net output #0: loss = 4.63471 (* 1 = 4.63471 loss)
I0405 15:21:04.046643 18799 sgd_solver.cpp:105] Iteration 17232, lr = 0.0001
I0405 15:21:06.084416 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17238.caffemodel
I0405 15:21:09.139361 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17238.solverstate
I0405 15:21:11.438526 18799 solver.cpp:330] Iteration 17238, Testing net (#0)
I0405 15:21:11.438551 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:21:13.697007 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:21:15.836071 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0551471
I0405 15:21:15.836110 18799 solver.cpp:397]     Test net output #1: loss = 4.74168 (* 1 = 4.74168 loss)
I0405 15:21:17.763768 18799 solver.cpp:218] Iteration 17244 (0.874823 iter/s, 13.7171s/12 iters), loss = 4.38558
I0405 15:21:17.763808 18799 solver.cpp:237]     Train net output #0: loss = 4.38558 (* 1 = 4.38558 loss)
I0405 15:21:17.763813 18799 sgd_solver.cpp:105] Iteration 17244, lr = 0.0001
I0405 15:21:23.083377 18799 solver.cpp:218] Iteration 17256 (2.25584 iter/s, 5.31953s/12 iters), loss = 4.59958
I0405 15:21:23.083434 18799 solver.cpp:237]     Train net output #0: loss = 4.59958 (* 1 = 4.59958 loss)
I0405 15:21:23.083442 18799 sgd_solver.cpp:105] Iteration 17256, lr = 0.0001
I0405 15:21:28.406574 18799 solver.cpp:218] Iteration 17268 (2.25432 iter/s, 5.3231s/12 iters), loss = 4.55328
I0405 15:21:28.406733 18799 solver.cpp:237]     Train net output #0: loss = 4.55328 (* 1 = 4.55328 loss)
I0405 15:21:28.406741 18799 sgd_solver.cpp:105] Iteration 17268, lr = 0.0001
I0405 15:21:33.664005 18799 solver.cpp:218] Iteration 17280 (2.28257 iter/s, 5.25724s/12 iters), loss = 4.49044
I0405 15:21:33.664044 18799 solver.cpp:237]     Train net output #0: loss = 4.49044 (* 1 = 4.49044 loss)
I0405 15:21:33.664050 18799 sgd_solver.cpp:105] Iteration 17280, lr = 0.0001
I0405 15:21:38.811487 18799 solver.cpp:218] Iteration 17292 (2.33127 iter/s, 5.1474s/12 iters), loss = 4.59318
I0405 15:21:38.811527 18799 solver.cpp:237]     Train net output #0: loss = 4.59318 (* 1 = 4.59318 loss)
I0405 15:21:38.811532 18799 sgd_solver.cpp:105] Iteration 17292, lr = 0.0001
I0405 15:21:40.825966 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:21:44.099402 18799 solver.cpp:218] Iteration 17304 (2.26936 iter/s, 5.28783s/12 iters), loss = 4.49941
I0405 15:21:44.099458 18799 solver.cpp:237]     Train net output #0: loss = 4.49941 (* 1 = 4.49941 loss)
I0405 15:21:44.099468 18799 sgd_solver.cpp:105] Iteration 17304, lr = 0.0001
I0405 15:21:49.463816 18799 solver.cpp:218] Iteration 17316 (2.237 iter/s, 5.36432s/12 iters), loss = 4.58699
I0405 15:21:49.463862 18799 solver.cpp:237]     Train net output #0: loss = 4.58699 (* 1 = 4.58699 loss)
I0405 15:21:49.463869 18799 sgd_solver.cpp:105] Iteration 17316, lr = 0.0001
I0405 15:21:54.668561 18799 solver.cpp:218] Iteration 17328 (2.30562 iter/s, 5.20466s/12 iters), loss = 4.5297
I0405 15:21:54.668602 18799 solver.cpp:237]     Train net output #0: loss = 4.5297 (* 1 = 4.5297 loss)
I0405 15:21:54.668607 18799 sgd_solver.cpp:105] Iteration 17328, lr = 0.0001
I0405 15:21:59.465412 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17340.caffemodel
I0405 15:22:02.574672 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17340.solverstate
I0405 15:22:04.923218 18799 solver.cpp:330] Iteration 17340, Testing net (#0)
I0405 15:22:04.923238 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:22:06.034889 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:22:07.064116 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:22:09.362751 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0545343
I0405 15:22:09.362787 18799 solver.cpp:397]     Test net output #1: loss = 4.7456 (* 1 = 4.7456 loss)
I0405 15:22:09.503491 18799 solver.cpp:218] Iteration 17340 (0.808908 iter/s, 14.8348s/12 iters), loss = 4.47216
I0405 15:22:09.503538 18799 solver.cpp:237]     Train net output #0: loss = 4.47216 (* 1 = 4.47216 loss)
I0405 15:22:09.503545 18799 sgd_solver.cpp:105] Iteration 17340, lr = 0.0001
I0405 15:22:13.751751 18799 solver.cpp:218] Iteration 17352 (2.82474 iter/s, 4.24818s/12 iters), loss = 4.60567
I0405 15:22:13.751791 18799 solver.cpp:237]     Train net output #0: loss = 4.60567 (* 1 = 4.60567 loss)
I0405 15:22:13.751796 18799 sgd_solver.cpp:105] Iteration 17352, lr = 0.0001
I0405 15:22:18.914379 18799 solver.cpp:218] Iteration 17364 (2.32443 iter/s, 5.16255s/12 iters), loss = 4.73683
I0405 15:22:18.914417 18799 solver.cpp:237]     Train net output #0: loss = 4.73683 (* 1 = 4.73683 loss)
I0405 15:22:18.914422 18799 sgd_solver.cpp:105] Iteration 17364, lr = 0.0001
I0405 15:22:24.110050 18799 solver.cpp:218] Iteration 17376 (2.30965 iter/s, 5.19559s/12 iters), loss = 4.7078
I0405 15:22:24.110097 18799 solver.cpp:237]     Train net output #0: loss = 4.7078 (* 1 = 4.7078 loss)
I0405 15:22:24.110105 18799 sgd_solver.cpp:105] Iteration 17376, lr = 0.0001
I0405 15:22:29.510658 18799 solver.cpp:218] Iteration 17388 (2.22201 iter/s, 5.40052s/12 iters), loss = 4.57813
I0405 15:22:29.510774 18799 solver.cpp:237]     Train net output #0: loss = 4.57813 (* 1 = 4.57813 loss)
I0405 15:22:29.510782 18799 sgd_solver.cpp:105] Iteration 17388, lr = 0.0001
I0405 15:22:33.850142 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:22:34.907788 18799 solver.cpp:218] Iteration 17400 (2.22347 iter/s, 5.39698s/12 iters), loss = 4.46517
I0405 15:22:34.907828 18799 solver.cpp:237]     Train net output #0: loss = 4.46517 (* 1 = 4.46517 loss)
I0405 15:22:34.907835 18799 sgd_solver.cpp:105] Iteration 17400, lr = 0.0001
I0405 15:22:40.238611 18799 solver.cpp:218] Iteration 17412 (2.2511 iter/s, 5.33074s/12 iters), loss = 4.56916
I0405 15:22:40.238672 18799 solver.cpp:237]     Train net output #0: loss = 4.56916 (* 1 = 4.56916 loss)
I0405 15:22:40.238682 18799 sgd_solver.cpp:105] Iteration 17412, lr = 0.0001
I0405 15:22:45.430910 18799 solver.cpp:218] Iteration 17424 (2.31116 iter/s, 5.1922s/12 iters), loss = 4.63902
I0405 15:22:45.430958 18799 solver.cpp:237]     Train net output #0: loss = 4.63902 (* 1 = 4.63902 loss)
I0405 15:22:45.430966 18799 sgd_solver.cpp:105] Iteration 17424, lr = 0.0001
I0405 15:22:50.534622 18799 solver.cpp:218] Iteration 17436 (2.35127 iter/s, 5.10363s/12 iters), loss = 4.46378
I0405 15:22:50.534660 18799 solver.cpp:237]     Train net output #0: loss = 4.46378 (* 1 = 4.46378 loss)
I0405 15:22:50.534665 18799 sgd_solver.cpp:105] Iteration 17436, lr = 0.0001
I0405 15:22:52.722235 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17442.caffemodel
I0405 15:22:55.782511 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17442.solverstate
I0405 15:22:58.094357 18799 solver.cpp:330] Iteration 17442, Testing net (#0)
I0405 15:22:58.094379 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:23:00.218654 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:23:02.405256 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0545343
I0405 15:23:02.405293 18799 solver.cpp:397]     Test net output #1: loss = 4.73993 (* 1 = 4.73993 loss)
I0405 15:23:04.363296 18799 solver.cpp:218] Iteration 17448 (0.86777 iter/s, 13.8286s/12 iters), loss = 4.518
I0405 15:23:04.363353 18799 solver.cpp:237]     Train net output #0: loss = 4.518 (* 1 = 4.518 loss)
I0405 15:23:04.363361 18799 sgd_solver.cpp:105] Iteration 17448, lr = 0.0001
I0405 15:23:09.630051 18799 solver.cpp:218] Iteration 17460 (2.27848 iter/s, 5.26666s/12 iters), loss = 4.61492
I0405 15:23:09.630093 18799 solver.cpp:237]     Train net output #0: loss = 4.61492 (* 1 = 4.61492 loss)
I0405 15:23:09.630098 18799 sgd_solver.cpp:105] Iteration 17460, lr = 0.0001
I0405 15:23:14.955806 18799 solver.cpp:218] Iteration 17472 (2.25324 iter/s, 5.32567s/12 iters), loss = 4.52202
I0405 15:23:14.955848 18799 solver.cpp:237]     Train net output #0: loss = 4.52202 (* 1 = 4.52202 loss)
I0405 15:23:14.955854 18799 sgd_solver.cpp:105] Iteration 17472, lr = 0.0001
I0405 15:23:20.613934 18799 solver.cpp:218] Iteration 17484 (2.12088 iter/s, 5.65804s/12 iters), loss = 4.55556
I0405 15:23:20.613978 18799 solver.cpp:237]     Train net output #0: loss = 4.55556 (* 1 = 4.55556 loss)
I0405 15:23:20.613983 18799 sgd_solver.cpp:105] Iteration 17484, lr = 0.0001
I0405 15:23:25.966066 18799 solver.cpp:218] Iteration 17496 (2.24213 iter/s, 5.35206s/12 iters), loss = 4.63465
I0405 15:23:25.966109 18799 solver.cpp:237]     Train net output #0: loss = 4.63465 (* 1 = 4.63465 loss)
I0405 15:23:25.966116 18799 sgd_solver.cpp:105] Iteration 17496, lr = 0.0001
I0405 15:23:27.319263 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:23:31.309423 18799 solver.cpp:218] Iteration 17508 (2.24581 iter/s, 5.34327s/12 iters), loss = 4.40205
I0405 15:23:31.309553 18799 solver.cpp:237]     Train net output #0: loss = 4.40205 (* 1 = 4.40205 loss)
I0405 15:23:31.309561 18799 sgd_solver.cpp:105] Iteration 17508, lr = 0.0001
I0405 15:23:36.572232 18799 solver.cpp:218] Iteration 17520 (2.28023 iter/s, 5.26264s/12 iters), loss = 4.64045
I0405 15:23:36.572285 18799 solver.cpp:237]     Train net output #0: loss = 4.64045 (* 1 = 4.64045 loss)
I0405 15:23:36.572293 18799 sgd_solver.cpp:105] Iteration 17520, lr = 0.0001
I0405 15:23:41.632405 18799 solver.cpp:218] Iteration 17532 (2.3715 iter/s, 5.06009s/12 iters), loss = 4.5153
I0405 15:23:41.632445 18799 solver.cpp:237]     Train net output #0: loss = 4.5153 (* 1 = 4.5153 loss)
I0405 15:23:41.632450 18799 sgd_solver.cpp:105] Iteration 17532, lr = 0.0001
I0405 15:23:46.195600 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17544.caffemodel
I0405 15:23:49.219065 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17544.solverstate
I0405 15:23:51.541539 18799 solver.cpp:330] Iteration 17544, Testing net (#0)
I0405 15:23:51.541559 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:23:53.706068 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:23:55.982183 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0569853
I0405 15:23:55.982219 18799 solver.cpp:397]     Test net output #1: loss = 4.73543 (* 1 = 4.73543 loss)
I0405 15:23:56.124114 18799 solver.cpp:218] Iteration 17544 (0.828066 iter/s, 14.4916s/12 iters), loss = 4.4939
I0405 15:23:56.124164 18799 solver.cpp:237]     Train net output #0: loss = 4.4939 (* 1 = 4.4939 loss)
I0405 15:23:56.124172 18799 sgd_solver.cpp:105] Iteration 17544, lr = 0.0001
I0405 15:24:00.570245 18799 solver.cpp:218] Iteration 17556 (2.69903 iter/s, 4.44605s/12 iters), loss = 4.39451
I0405 15:24:00.570286 18799 solver.cpp:237]     Train net output #0: loss = 4.39451 (* 1 = 4.39451 loss)
I0405 15:24:00.570291 18799 sgd_solver.cpp:105] Iteration 17556, lr = 0.0001
I0405 15:24:05.706745 18799 solver.cpp:218] Iteration 17568 (2.33626 iter/s, 5.13642s/12 iters), loss = 4.50997
I0405 15:24:05.706880 18799 solver.cpp:237]     Train net output #0: loss = 4.50997 (* 1 = 4.50997 loss)
I0405 15:24:05.706888 18799 sgd_solver.cpp:105] Iteration 17568, lr = 0.0001
I0405 15:24:10.863775 18799 solver.cpp:218] Iteration 17580 (2.327 iter/s, 5.15686s/12 iters), loss = 4.32723
I0405 15:24:10.863812 18799 solver.cpp:237]     Train net output #0: loss = 4.32723 (* 1 = 4.32723 loss)
I0405 15:24:10.863817 18799 sgd_solver.cpp:105] Iteration 17580, lr = 0.0001
I0405 15:24:15.955416 18799 solver.cpp:218] Iteration 17592 (2.35684 iter/s, 5.09156s/12 iters), loss = 4.51965
I0405 15:24:15.955473 18799 solver.cpp:237]     Train net output #0: loss = 4.51965 (* 1 = 4.51965 loss)
I0405 15:24:15.955482 18799 sgd_solver.cpp:105] Iteration 17592, lr = 0.0001
I0405 15:24:19.502420 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:24:21.101289 18799 solver.cpp:218] Iteration 17604 (2.33201 iter/s, 5.14578s/12 iters), loss = 4.45664
I0405 15:24:21.101331 18799 solver.cpp:237]     Train net output #0: loss = 4.45664 (* 1 = 4.45664 loss)
I0405 15:24:21.101337 18799 sgd_solver.cpp:105] Iteration 17604, lr = 0.0001
I0405 15:24:26.511927 18799 solver.cpp:218] Iteration 17616 (2.21789 iter/s, 5.41056s/12 iters), loss = 4.51149
I0405 15:24:26.511967 18799 solver.cpp:237]     Train net output #0: loss = 4.51149 (* 1 = 4.51149 loss)
I0405 15:24:26.511972 18799 sgd_solver.cpp:105] Iteration 17616, lr = 0.0001
I0405 15:24:31.683059 18799 solver.cpp:218] Iteration 17628 (2.32061 iter/s, 5.17106s/12 iters), loss = 4.64574
I0405 15:24:31.683107 18799 solver.cpp:237]     Train net output #0: loss = 4.64574 (* 1 = 4.64574 loss)
I0405 15:24:31.683115 18799 sgd_solver.cpp:105] Iteration 17628, lr = 0.0001
I0405 15:24:36.910813 18799 solver.cpp:218] Iteration 17640 (2.29548 iter/s, 5.22767s/12 iters), loss = 4.38618
I0405 15:24:36.910945 18799 solver.cpp:237]     Train net output #0: loss = 4.38618 (* 1 = 4.38618 loss)
I0405 15:24:36.910953 18799 sgd_solver.cpp:105] Iteration 17640, lr = 0.0001
I0405 15:24:38.954113 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17646.caffemodel
I0405 15:24:42.695967 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17646.solverstate
I0405 15:24:45.056345 18799 solver.cpp:330] Iteration 17646, Testing net (#0)
I0405 15:24:45.056363 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:24:47.071089 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:24:49.446707 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0588235
I0405 15:24:49.446734 18799 solver.cpp:397]     Test net output #1: loss = 4.72647 (* 1 = 4.72647 loss)
I0405 15:24:51.375996 18799 solver.cpp:218] Iteration 17652 (0.82959 iter/s, 14.465s/12 iters), loss = 4.66501
I0405 15:24:51.376057 18799 solver.cpp:237]     Train net output #0: loss = 4.66501 (* 1 = 4.66501 loss)
I0405 15:24:51.376066 18799 sgd_solver.cpp:105] Iteration 17652, lr = 0.0001
I0405 15:24:56.854534 18799 solver.cpp:218] Iteration 17664 (2.1904 iter/s, 5.47844s/12 iters), loss = 4.4327
I0405 15:24:56.854579 18799 solver.cpp:237]     Train net output #0: loss = 4.4327 (* 1 = 4.4327 loss)
I0405 15:24:56.854584 18799 sgd_solver.cpp:105] Iteration 17664, lr = 0.0001
I0405 15:25:01.889859 18799 solver.cpp:218] Iteration 17676 (2.3832 iter/s, 5.03524s/12 iters), loss = 4.5255
I0405 15:25:01.889899 18799 solver.cpp:237]     Train net output #0: loss = 4.5255 (* 1 = 4.5255 loss)
I0405 15:25:01.889904 18799 sgd_solver.cpp:105] Iteration 17676, lr = 0.0001
I0405 15:25:07.432436 18799 solver.cpp:218] Iteration 17688 (2.16509 iter/s, 5.54249s/12 iters), loss = 4.66258
I0405 15:25:07.432574 18799 solver.cpp:237]     Train net output #0: loss = 4.66258 (* 1 = 4.66258 loss)
I0405 15:25:07.432585 18799 sgd_solver.cpp:105] Iteration 17688, lr = 0.0001
I0405 15:25:12.735805 18799 solver.cpp:218] Iteration 17700 (2.26278 iter/s, 5.3032s/12 iters), loss = 4.56601
I0405 15:25:12.735860 18799 solver.cpp:237]     Train net output #0: loss = 4.56601 (* 1 = 4.56601 loss)
I0405 15:25:12.735869 18799 sgd_solver.cpp:105] Iteration 17700, lr = 0.0001
I0405 15:25:13.291982 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:25:18.166718 18799 solver.cpp:218] Iteration 17712 (2.20961 iter/s, 5.43082s/12 iters), loss = 4.46899
I0405 15:25:18.166764 18799 solver.cpp:237]     Train net output #0: loss = 4.46899 (* 1 = 4.46899 loss)
I0405 15:25:18.166770 18799 sgd_solver.cpp:105] Iteration 17712, lr = 0.0001
I0405 15:25:23.431587 18799 solver.cpp:218] Iteration 17724 (2.2793 iter/s, 5.26478s/12 iters), loss = 4.59658
I0405 15:25:23.431628 18799 solver.cpp:237]     Train net output #0: loss = 4.59658 (* 1 = 4.59658 loss)
I0405 15:25:23.431633 18799 sgd_solver.cpp:105] Iteration 17724, lr = 0.0001
I0405 15:25:28.771672 18799 solver.cpp:218] Iteration 17736 (2.24719 iter/s, 5.34s/12 iters), loss = 4.4795
I0405 15:25:28.771724 18799 solver.cpp:237]     Train net output #0: loss = 4.4795 (* 1 = 4.4795 loss)
I0405 15:25:28.771733 18799 sgd_solver.cpp:105] Iteration 17736, lr = 0.0001
I0405 15:25:33.646744 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17748.caffemodel
I0405 15:25:36.690654 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17748.solverstate
I0405 15:25:39.020622 18799 solver.cpp:330] Iteration 17748, Testing net (#0)
I0405 15:25:39.020709 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:25:41.059806 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:25:43.506810 18799 solver.cpp:397]     Test net output #0: accuracy = 0.060049
I0405 15:25:43.506839 18799 solver.cpp:397]     Test net output #1: loss = 4.71251 (* 1 = 4.71251 loss)
I0405 15:25:43.649021 18799 solver.cpp:218] Iteration 17748 (0.806602 iter/s, 14.8772s/12 iters), loss = 4.5703
I0405 15:25:43.649077 18799 solver.cpp:237]     Train net output #0: loss = 4.5703 (* 1 = 4.5703 loss)
I0405 15:25:43.649085 18799 sgd_solver.cpp:105] Iteration 17748, lr = 0.0001
I0405 15:25:48.177683 18799 solver.cpp:218] Iteration 17760 (2.64984 iter/s, 4.52858s/12 iters), loss = 4.4836
I0405 15:25:48.177723 18799 solver.cpp:237]     Train net output #0: loss = 4.4836 (* 1 = 4.4836 loss)
I0405 15:25:48.177729 18799 sgd_solver.cpp:105] Iteration 17760, lr = 0.0001
I0405 15:25:53.351531 18799 solver.cpp:218] Iteration 17772 (2.31939 iter/s, 5.17377s/12 iters), loss = 4.41982
I0405 15:25:53.351572 18799 solver.cpp:237]     Train net output #0: loss = 4.41982 (* 1 = 4.41982 loss)
I0405 15:25:53.351577 18799 sgd_solver.cpp:105] Iteration 17772, lr = 0.0001
I0405 15:25:58.638890 18799 solver.cpp:218] Iteration 17784 (2.2696 iter/s, 5.28728s/12 iters), loss = 4.52492
I0405 15:25:58.638942 18799 solver.cpp:237]     Train net output #0: loss = 4.52492 (* 1 = 4.52492 loss)
I0405 15:25:58.638952 18799 sgd_solver.cpp:105] Iteration 17784, lr = 0.0001
I0405 15:26:04.007925 18799 solver.cpp:218] Iteration 17796 (2.23508 iter/s, 5.36894s/12 iters), loss = 4.63663
I0405 15:26:04.007964 18799 solver.cpp:237]     Train net output #0: loss = 4.63663 (* 1 = 4.63663 loss)
I0405 15:26:04.007970 18799 sgd_solver.cpp:105] Iteration 17796, lr = 0.0001
I0405 15:26:06.722959 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:26:09.153223 18799 solver.cpp:218] Iteration 17808 (2.33226 iter/s, 5.14522s/12 iters), loss = 4.5416
I0405 15:26:09.153344 18799 solver.cpp:237]     Train net output #0: loss = 4.5416 (* 1 = 4.5416 loss)
I0405 15:26:09.153352 18799 sgd_solver.cpp:105] Iteration 17808, lr = 0.0001
I0405 15:26:14.705797 18799 solver.cpp:218] Iteration 17820 (2.16122 iter/s, 5.55242s/12 iters), loss = 4.46132
I0405 15:26:14.705835 18799 solver.cpp:237]     Train net output #0: loss = 4.46132 (* 1 = 4.46132 loss)
I0405 15:26:14.705840 18799 sgd_solver.cpp:105] Iteration 17820, lr = 0.0001
I0405 15:26:19.989459 18799 solver.cpp:218] Iteration 17832 (2.27119 iter/s, 5.28358s/12 iters), loss = 4.44558
I0405 15:26:19.989507 18799 solver.cpp:237]     Train net output #0: loss = 4.44558 (* 1 = 4.44558 loss)
I0405 15:26:19.989516 18799 sgd_solver.cpp:105] Iteration 17832, lr = 0.0001
I0405 15:26:25.684988 18799 solver.cpp:218] Iteration 17844 (2.10695 iter/s, 5.69544s/12 iters), loss = 4.48354
I0405 15:26:25.685034 18799 solver.cpp:237]     Train net output #0: loss = 4.48354 (* 1 = 4.48354 loss)
I0405 15:26:25.685041 18799 sgd_solver.cpp:105] Iteration 17844, lr = 0.0001
I0405 15:26:27.687480 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17850.caffemodel
I0405 15:26:30.736858 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17850.solverstate
I0405 15:26:33.048264 18799 solver.cpp:330] Iteration 17850, Testing net (#0)
I0405 15:26:33.048283 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:26:35.091286 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:26:37.512151 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0606618
I0405 15:26:37.512187 18799 solver.cpp:397]     Test net output #1: loss = 4.71546 (* 1 = 4.71546 loss)
I0405 15:26:39.441296 18799 solver.cpp:218] Iteration 17856 (0.872335 iter/s, 13.7562s/12 iters), loss = 4.52914
I0405 15:26:39.441444 18799 solver.cpp:237]     Train net output #0: loss = 4.52914 (* 1 = 4.52914 loss)
I0405 15:26:39.441452 18799 sgd_solver.cpp:105] Iteration 17856, lr = 0.0001
I0405 15:26:44.463600 18799 solver.cpp:218] Iteration 17868 (2.38943 iter/s, 5.02212s/12 iters), loss = 4.67918
I0405 15:26:44.463649 18799 solver.cpp:237]     Train net output #0: loss = 4.67918 (* 1 = 4.67918 loss)
I0405 15:26:44.463657 18799 sgd_solver.cpp:105] Iteration 17868, lr = 0.0001
I0405 15:26:49.662657 18799 solver.cpp:218] Iteration 17880 (2.30815 iter/s, 5.19897s/12 iters), loss = 4.41731
I0405 15:26:49.662706 18799 solver.cpp:237]     Train net output #0: loss = 4.41731 (* 1 = 4.41731 loss)
I0405 15:26:49.662715 18799 sgd_solver.cpp:105] Iteration 17880, lr = 0.0001
I0405 15:26:54.839737 18799 solver.cpp:218] Iteration 17892 (2.31795 iter/s, 5.17699s/12 iters), loss = 4.44786
I0405 15:26:54.839982 18799 solver.cpp:237]     Train net output #0: loss = 4.44786 (* 1 = 4.44786 loss)
I0405 15:26:54.839991 18799 sgd_solver.cpp:105] Iteration 17892, lr = 0.0001
I0405 15:26:59.877787 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:00.133230 18799 solver.cpp:218] Iteration 17904 (2.26705 iter/s, 5.29322s/12 iters), loss = 4.53495
I0405 15:27:00.133270 18799 solver.cpp:237]     Train net output #0: loss = 4.53495 (* 1 = 4.53495 loss)
I0405 15:27:00.133275 18799 sgd_solver.cpp:105] Iteration 17904, lr = 0.0001
I0405 15:27:05.243862 18799 solver.cpp:218] Iteration 17916 (2.34808 iter/s, 5.11055s/12 iters), loss = 4.46333
I0405 15:27:05.243906 18799 solver.cpp:237]     Train net output #0: loss = 4.46333 (* 1 = 4.46333 loss)
I0405 15:27:05.243914 18799 sgd_solver.cpp:105] Iteration 17916, lr = 0.0001
I0405 15:27:10.497293 18799 solver.cpp:218] Iteration 17928 (2.28426 iter/s, 5.25335s/12 iters), loss = 4.47952
I0405 15:27:10.497408 18799 solver.cpp:237]     Train net output #0: loss = 4.47952 (* 1 = 4.47952 loss)
I0405 15:27:10.497416 18799 sgd_solver.cpp:105] Iteration 17928, lr = 0.0001
I0405 15:27:15.754909 18799 solver.cpp:218] Iteration 17940 (2.28247 iter/s, 5.25746s/12 iters), loss = 4.59573
I0405 15:27:15.754948 18799 solver.cpp:237]     Train net output #0: loss = 4.59573 (* 1 = 4.59573 loss)
I0405 15:27:15.754954 18799 sgd_solver.cpp:105] Iteration 17940, lr = 0.0001
I0405 15:27:20.514158 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17952.caffemodel
I0405 15:27:23.546696 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17952.solverstate
I0405 15:27:25.850389 18799 solver.cpp:330] Iteration 17952, Testing net (#0)
I0405 15:27:25.850410 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:27:27.887102 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:30.467507 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0582108
I0405 15:27:30.467533 18799 solver.cpp:397]     Test net output #1: loss = 4.71225 (* 1 = 4.71225 loss)
I0405 15:27:30.609431 18799 solver.cpp:218] Iteration 17952 (0.807841 iter/s, 14.8544s/12 iters), loss = 4.50264
I0405 15:27:30.609478 18799 solver.cpp:237]     Train net output #0: loss = 4.50264 (* 1 = 4.50264 loss)
I0405 15:27:30.609483 18799 sgd_solver.cpp:105] Iteration 17952, lr = 0.0001
I0405 15:27:34.987396 18799 solver.cpp:218] Iteration 17964 (2.74105 iter/s, 4.37788s/12 iters), loss = 4.5545
I0405 15:27:34.987449 18799 solver.cpp:237]     Train net output #0: loss = 4.5545 (* 1 = 4.5545 loss)
I0405 15:27:34.987457 18799 sgd_solver.cpp:105] Iteration 17964, lr = 0.0001
I0405 15:27:40.391857 18799 solver.cpp:218] Iteration 17976 (2.22042 iter/s, 5.40437s/12 iters), loss = 4.42195
I0405 15:27:40.391896 18799 solver.cpp:237]     Train net output #0: loss = 4.42195 (* 1 = 4.42195 loss)
I0405 15:27:40.391901 18799 sgd_solver.cpp:105] Iteration 17976, lr = 0.0001
I0405 15:27:45.706269 18799 solver.cpp:218] Iteration 17988 (2.25804 iter/s, 5.31433s/12 iters), loss = 4.41828
I0405 15:27:45.706405 18799 solver.cpp:237]     Train net output #0: loss = 4.41828 (* 1 = 4.41828 loss)
I0405 15:27:45.706413 18799 sgd_solver.cpp:105] Iteration 17988, lr = 0.0001
I0405 15:27:51.116590 18799 solver.cpp:218] Iteration 18000 (2.21805 iter/s, 5.41015s/12 iters), loss = 4.44928
I0405 15:27:51.116628 18799 solver.cpp:237]     Train net output #0: loss = 4.44928 (* 1 = 4.44928 loss)
I0405 15:27:51.116633 18799 sgd_solver.cpp:105] Iteration 18000, lr = 0.0001
I0405 15:27:53.131808 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:56.158180 18799 solver.cpp:218] Iteration 18012 (2.38024 iter/s, 5.04151s/12 iters), loss = 4.34639
I0405 15:27:56.158229 18799 solver.cpp:237]     Train net output #0: loss = 4.34639 (* 1 = 4.34639 loss)
I0405 15:27:56.158238 18799 sgd_solver.cpp:105] Iteration 18012, lr = 0.0001
I0405 15:28:01.018863 18799 solver.cpp:218] Iteration 18024 (2.46883 iter/s, 4.8606s/12 iters), loss = 4.53774
I0405 15:28:01.018906 18799 solver.cpp:237]     Train net output #0: loss = 4.53774 (* 1 = 4.53774 loss)
I0405 15:28:01.018911 18799 sgd_solver.cpp:105] Iteration 18024, lr = 0.0001
I0405 15:28:06.368032 18799 solver.cpp:218] Iteration 18036 (2.24337 iter/s, 5.34909s/12 iters), loss = 4.45312
I0405 15:28:06.368074 18799 solver.cpp:237]     Train net output #0: loss = 4.45312 (* 1 = 4.45312 loss)
I0405 15:28:06.368079 18799 sgd_solver.cpp:105] Iteration 18036, lr = 0.0001
I0405 15:28:06.368271 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:28:11.568925 18799 solver.cpp:218] Iteration 18048 (2.30733 iter/s, 5.20081s/12 iters), loss = 4.40345
I0405 15:28:11.568962 18799 solver.cpp:237]     Train net output #0: loss = 4.40345 (* 1 = 4.40345 loss)
I0405 15:28:11.568969 18799 sgd_solver.cpp:105] Iteration 18048, lr = 0.0001
I0405 15:28:13.555552 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18054.caffemodel
I0405 15:28:16.596637 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18054.solverstate
I0405 15:28:18.919893 18799 solver.cpp:330] Iteration 18054, Testing net (#0)
I0405 15:28:18.919919 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:28:20.832587 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:28:23.251241 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0582108
I0405 15:28:23.251281 18799 solver.cpp:397]     Test net output #1: loss = 4.71181 (* 1 = 4.71181 loss)
I0405 15:28:25.155393 18799 solver.cpp:218] Iteration 18060 (0.883239 iter/s, 13.5864s/12 iters), loss = 4.38123
I0405 15:28:25.155454 18799 solver.cpp:237]     Train net output #0: loss = 4.38123 (* 1 = 4.38123 loss)
I0405 15:28:25.155462 18799 sgd_solver.cpp:105] Iteration 18060, lr = 0.0001
I0405 15:28:30.437952 18799 solver.cpp:218] Iteration 18072 (2.27167 iter/s, 5.28246s/12 iters), loss = 4.61369
I0405 15:28:30.437991 18799 solver.cpp:237]     Train net output #0: loss = 4.61369 (* 1 = 4.61369 loss)
I0405 15:28:30.437997 18799 sgd_solver.cpp:105] Iteration 18072, lr = 0.0001
I0405 15:28:35.900426 18799 solver.cpp:218] Iteration 18084 (2.19684 iter/s, 5.46239s/12 iters), loss = 4.72471
I0405 15:28:35.900463 18799 solver.cpp:237]     Train net output #0: loss = 4.72471 (* 1 = 4.72471 loss)
I0405 15:28:35.900468 18799 sgd_solver.cpp:105] Iteration 18084, lr = 0.0001
I0405 15:28:41.235316 18799 solver.cpp:218] Iteration 18096 (2.24937 iter/s, 5.33482s/12 iters), loss = 4.36257
I0405 15:28:41.235352 18799 solver.cpp:237]     Train net output #0: loss = 4.36257 (* 1 = 4.36257 loss)
I0405 15:28:41.235358 18799 sgd_solver.cpp:105] Iteration 18096, lr = 0.0001
I0405 15:28:45.457254 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:28:46.329524 18799 solver.cpp:218] Iteration 18108 (2.35565 iter/s, 5.09414s/12 iters), loss = 4.47095
I0405 15:28:46.329560 18799 solver.cpp:237]     Train net output #0: loss = 4.47095 (* 1 = 4.47095 loss)
I0405 15:28:46.329566 18799 sgd_solver.cpp:105] Iteration 18108, lr = 0.0001
I0405 15:28:51.657840 18799 solver.cpp:218] Iteration 18120 (2.25215 iter/s, 5.32823s/12 iters), loss = 4.48671
I0405 15:28:51.657999 18799 solver.cpp:237]     Train net output #0: loss = 4.48671 (* 1 = 4.48671 loss)
I0405 15:28:51.658010 18799 sgd_solver.cpp:105] Iteration 18120, lr = 0.0001
I0405 15:28:56.850378 18799 solver.cpp:218] Iteration 18132 (2.3111 iter/s, 5.19234s/12 iters), loss = 4.63409
I0405 15:28:56.850423 18799 solver.cpp:237]     Train net output #0: loss = 4.63409 (* 1 = 4.63409 loss)
I0405 15:28:56.850430 18799 sgd_solver.cpp:105] Iteration 18132, lr = 0.0001
I0405 15:29:02.085379 18799 solver.cpp:218] Iteration 18144 (2.2923 iter/s, 5.23492s/12 iters), loss = 4.46943
I0405 15:29:02.085419 18799 solver.cpp:237]     Train net output #0: loss = 4.46943 (* 1 = 4.46943 loss)
I0405 15:29:02.085425 18799 sgd_solver.cpp:105] Iteration 18144, lr = 0.0001
I0405 15:29:06.827431 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18156.caffemodel
I0405 15:29:09.874444 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18156.solverstate
I0405 15:29:12.175060 18799 solver.cpp:330] Iteration 18156, Testing net (#0)
I0405 15:29:12.175079 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:29:14.123240 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:29:16.578429 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0606618
I0405 15:29:16.578465 18799 solver.cpp:397]     Test net output #1: loss = 4.69733 (* 1 = 4.69733 loss)
I0405 15:29:16.720297 18799 solver.cpp:218] Iteration 18156 (0.819963 iter/s, 14.6348s/12 iters), loss = 4.48592
I0405 15:29:16.720347 18799 solver.cpp:237]     Train net output #0: loss = 4.48592 (* 1 = 4.48592 loss)
I0405 15:29:16.720355 18799 sgd_solver.cpp:105] Iteration 18156, lr = 0.0001
I0405 15:29:21.083145 18799 solver.cpp:218] Iteration 18168 (2.75055 iter/s, 4.36277s/12 iters), loss = 4.61501
I0405 15:29:21.083187 18799 solver.cpp:237]     Train net output #0: loss = 4.61501 (* 1 = 4.61501 loss)
I0405 15:29:21.083192 18799 sgd_solver.cpp:105] Iteration 18168, lr = 0.0001
I0405 15:29:26.443831 18799 solver.cpp:218] Iteration 18180 (2.23855 iter/s, 5.36061s/12 iters), loss = 4.41693
I0405 15:29:26.443928 18799 solver.cpp:237]     Train net output #0: loss = 4.41693 (* 1 = 4.41693 loss)
I0405 15:29:26.443934 18799 sgd_solver.cpp:105] Iteration 18180, lr = 0.0001
I0405 15:29:31.878141 18799 solver.cpp:218] Iteration 18192 (2.20825 iter/s, 5.43417s/12 iters), loss = 4.54739
I0405 15:29:31.878182 18799 solver.cpp:237]     Train net output #0: loss = 4.54739 (* 1 = 4.54739 loss)
I0405 15:29:31.878187 18799 sgd_solver.cpp:105] Iteration 18192, lr = 0.0001
I0405 15:29:37.343664 18799 solver.cpp:218] Iteration 18204 (2.19561 iter/s, 5.46544s/12 iters), loss = 4.56982
I0405 15:29:37.343709 18799 solver.cpp:237]     Train net output #0: loss = 4.56982 (* 1 = 4.56982 loss)
I0405 15:29:37.343715 18799 sgd_solver.cpp:105] Iteration 18204, lr = 0.0001
I0405 15:29:38.675324 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:29:42.616811 18799 solver.cpp:218] Iteration 18216 (2.27572 iter/s, 5.27306s/12 iters), loss = 4.45874
I0405 15:29:42.616875 18799 solver.cpp:237]     Train net output #0: loss = 4.45874 (* 1 = 4.45874 loss)
I0405 15:29:42.616901 18799 sgd_solver.cpp:105] Iteration 18216, lr = 0.0001
I0405 15:29:47.875380 18799 solver.cpp:218] Iteration 18228 (2.28203 iter/s, 5.25847s/12 iters), loss = 4.55436
I0405 15:29:47.875439 18799 solver.cpp:237]     Train net output #0: loss = 4.55436 (* 1 = 4.55436 loss)
I0405 15:29:47.875447 18799 sgd_solver.cpp:105] Iteration 18228, lr = 0.0001
I0405 15:29:53.017094 18799 solver.cpp:218] Iteration 18240 (2.33389 iter/s, 5.14162s/12 iters), loss = 4.31856
I0405 15:29:53.017135 18799 solver.cpp:237]     Train net output #0: loss = 4.31856 (* 1 = 4.31856 loss)
I0405 15:29:53.017141 18799 sgd_solver.cpp:105] Iteration 18240, lr = 0.0001
I0405 15:29:58.207170 18799 solver.cpp:218] Iteration 18252 (2.31214 iter/s, 5.18999s/12 iters), loss = 4.51422
I0405 15:29:58.207345 18799 solver.cpp:237]     Train net output #0: loss = 4.51422 (* 1 = 4.51422 loss)
I0405 15:29:58.207353 18799 sgd_solver.cpp:105] Iteration 18252, lr = 0.0001
I0405 15:30:00.258795 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18258.caffemodel
I0405 15:30:03.341794 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18258.solverstate
I0405 15:30:05.650527 18799 solver.cpp:330] Iteration 18258, Testing net (#0)
I0405 15:30:05.650543 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:30:07.552784 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:30:10.153141 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0557598
I0405 15:30:10.153172 18799 solver.cpp:397]     Test net output #1: loss = 4.70435 (* 1 = 4.70435 loss)
I0405 15:30:12.144691 18799 solver.cpp:218] Iteration 18264 (0.861001 iter/s, 13.9373s/12 iters), loss = 4.3659
I0405 15:30:12.144752 18799 solver.cpp:237]     Train net output #0: loss = 4.3659 (* 1 = 4.3659 loss)
I0405 15:30:12.144762 18799 sgd_solver.cpp:105] Iteration 18264, lr = 0.0001
I0405 15:30:17.512152 18799 solver.cpp:218] Iteration 18276 (2.23574 iter/s, 5.36736s/12 iters), loss = 4.41592
I0405 15:30:17.512205 18799 solver.cpp:237]     Train net output #0: loss = 4.41592 (* 1 = 4.41592 loss)
I0405 15:30:17.512212 18799 sgd_solver.cpp:105] Iteration 18276, lr = 0.0001
I0405 15:30:22.690667 18799 solver.cpp:218] Iteration 18288 (2.31731 iter/s, 5.17842s/12 iters), loss = 4.22131
I0405 15:30:22.690707 18799 solver.cpp:237]     Train net output #0: loss = 4.22131 (* 1 = 4.22131 loss)
I0405 15:30:22.690713 18799 sgd_solver.cpp:105] Iteration 18288, lr = 0.0001
I0405 15:30:27.894069 18799 solver.cpp:218] Iteration 18300 (2.30622 iter/s, 5.20332s/12 iters), loss = 4.48087
I0405 15:30:27.894124 18799 solver.cpp:237]     Train net output #0: loss = 4.48087 (* 1 = 4.48087 loss)
I0405 15:30:27.894132 18799 sgd_solver.cpp:105] Iteration 18300, lr = 0.0001
I0405 15:30:31.324327 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:30:33.046403 18799 solver.cpp:218] Iteration 18312 (2.32909 iter/s, 5.15224s/12 iters), loss = 4.46831
I0405 15:30:33.046447 18799 solver.cpp:237]     Train net output #0: loss = 4.46831 (* 1 = 4.46831 loss)
I0405 15:30:33.046452 18799 sgd_solver.cpp:105] Iteration 18312, lr = 0.0001
I0405 15:30:38.424171 18799 solver.cpp:218] Iteration 18324 (2.23144 iter/s, 5.37769s/12 iters), loss = 4.37016
I0405 15:30:38.424211 18799 solver.cpp:237]     Train net output #0: loss = 4.37016 (* 1 = 4.37016 loss)
I0405 15:30:38.424216 18799 sgd_solver.cpp:105] Iteration 18324, lr = 0.0001
I0405 15:30:43.887238 18799 solver.cpp:218] Iteration 18336 (2.1966 iter/s, 5.46299s/12 iters), loss = 4.59516
I0405 15:30:43.887288 18799 solver.cpp:237]     Train net output #0: loss = 4.59516 (* 1 = 4.59516 loss)
I0405 15:30:43.887296 18799 sgd_solver.cpp:105] Iteration 18336, lr = 0.0001
I0405 15:30:49.027321 18799 solver.cpp:218] Iteration 18348 (2.33463 iter/s, 5.14s/12 iters), loss = 4.35067
I0405 15:30:49.027359 18799 solver.cpp:237]     Train net output #0: loss = 4.35067 (* 1 = 4.35067 loss)
I0405 15:30:49.027364 18799 sgd_solver.cpp:105] Iteration 18348, lr = 0.0001
I0405 15:30:53.533756 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18360.caffemodel
I0405 15:30:56.543726 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18360.solverstate
I0405 15:30:58.869927 18799 solver.cpp:330] Iteration 18360, Testing net (#0)
I0405 15:30:58.869951 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:31:00.744266 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:31:03.294633 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0563725
I0405 15:31:03.294728 18799 solver.cpp:397]     Test net output #1: loss = 4.69141 (* 1 = 4.69141 loss)
I0405 15:31:03.438967 18799 solver.cpp:218] Iteration 18360 (0.832667 iter/s, 14.4115s/12 iters), loss = 4.61605
I0405 15:31:03.439021 18799 solver.cpp:237]     Train net output #0: loss = 4.61605 (* 1 = 4.61605 loss)
I0405 15:31:03.439030 18799 sgd_solver.cpp:105] Iteration 18360, lr = 0.0001
I0405 15:31:07.974704 18799 solver.cpp:218] Iteration 18372 (2.64571 iter/s, 4.53564s/12 iters), loss = 4.28001
I0405 15:31:07.974751 18799 solver.cpp:237]     Train net output #0: loss = 4.28001 (* 1 = 4.28001 loss)
I0405 15:31:07.974757 18799 sgd_solver.cpp:105] Iteration 18372, lr = 0.0001
I0405 15:31:13.196631 18799 solver.cpp:218] Iteration 18384 (2.29804 iter/s, 5.22184s/12 iters), loss = 4.39685
I0405 15:31:13.196676 18799 solver.cpp:237]     Train net output #0: loss = 4.39685 (* 1 = 4.39685 loss)
I0405 15:31:13.196681 18799 sgd_solver.cpp:105] Iteration 18384, lr = 0.0001
I0405 15:31:18.386193 18799 solver.cpp:218] Iteration 18396 (2.31237 iter/s, 5.18948s/12 iters), loss = 4.51431
I0405 15:31:18.386232 18799 solver.cpp:237]     Train net output #0: loss = 4.51431 (* 1 = 4.51431 loss)
I0405 15:31:18.386238 18799 sgd_solver.cpp:105] Iteration 18396, lr = 0.0001
I0405 15:31:23.843896 18799 solver.cpp:218] Iteration 18408 (2.19876 iter/s, 5.45762s/12 iters), loss = 4.35906
I0405 15:31:23.843941 18799 solver.cpp:237]     Train net output #0: loss = 4.35906 (* 1 = 4.35906 loss)
I0405 15:31:23.843947 18799 sgd_solver.cpp:105] Iteration 18408, lr = 0.0001
I0405 15:31:24.431087 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:31:29.017032 18799 solver.cpp:218] Iteration 18420 (2.31971 iter/s, 5.17305s/12 iters), loss = 4.32848
I0405 15:31:29.017081 18799 solver.cpp:237]     Train net output #0: loss = 4.32848 (* 1 = 4.32848 loss)
I0405 15:31:29.017091 18799 sgd_solver.cpp:105] Iteration 18420, lr = 0.0001
I0405 15:31:34.226424 18799 solver.cpp:218] Iteration 18432 (2.30357 iter/s, 5.2093s/12 iters), loss = 4.44374
I0405 15:31:34.226565 18799 solver.cpp:237]     Train net output #0: loss = 4.44374 (* 1 = 4.44374 loss)
I0405 15:31:34.226572 18799 sgd_solver.cpp:105] Iteration 18432, lr = 0.0001
I0405 15:31:39.308693 18799 solver.cpp:218] Iteration 18444 (2.36123 iter/s, 5.08209s/12 iters), loss = 4.57431
I0405 15:31:39.308737 18799 solver.cpp:237]     Train net output #0: loss = 4.57431 (* 1 = 4.57431 loss)
I0405 15:31:39.308743 18799 sgd_solver.cpp:105] Iteration 18444, lr = 0.0001
I0405 15:31:44.704072 18799 solver.cpp:218] Iteration 18456 (2.22416 iter/s, 5.3953s/12 iters), loss = 4.65711
I0405 15:31:44.704114 18799 solver.cpp:237]     Train net output #0: loss = 4.65711 (* 1 = 4.65711 loss)
I0405 15:31:44.704119 18799 sgd_solver.cpp:105] Iteration 18456, lr = 0.0001
I0405 15:31:46.890316 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18462.caffemodel
I0405 15:31:49.927397 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18462.solverstate
I0405 15:31:52.244191 18799 solver.cpp:330] Iteration 18462, Testing net (#0)
I0405 15:31:52.244213 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:31:54.045363 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:31:56.655781 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0618873
I0405 15:31:56.655809 18799 solver.cpp:397]     Test net output #1: loss = 4.68304 (* 1 = 4.68304 loss)
I0405 15:31:58.626556 18799 solver.cpp:218] Iteration 18468 (0.861923 iter/s, 13.9224s/12 iters), loss = 4.40803
I0405 15:31:58.626602 18799 solver.cpp:237]     Train net output #0: loss = 4.40803 (* 1 = 4.40803 loss)
I0405 15:31:58.626607 18799 sgd_solver.cpp:105] Iteration 18468, lr = 0.0001
I0405 15:32:03.817862 18799 solver.cpp:218] Iteration 18480 (2.3116 iter/s, 5.19122s/12 iters), loss = 4.0739
I0405 15:32:03.817912 18799 solver.cpp:237]     Train net output #0: loss = 4.0739 (* 1 = 4.0739 loss)
I0405 15:32:03.817920 18799 sgd_solver.cpp:105] Iteration 18480, lr = 0.0001
I0405 15:32:09.137570 18799 solver.cpp:218] Iteration 18492 (2.2558 iter/s, 5.31962s/12 iters), loss = 4.37992
I0405 15:32:09.137706 18799 solver.cpp:237]     Train net output #0: loss = 4.37992 (* 1 = 4.37992 loss)
I0405 15:32:09.137712 18799 sgd_solver.cpp:105] Iteration 18492, lr = 0.0001
I0405 15:32:14.321442 18799 solver.cpp:218] Iteration 18504 (2.31495 iter/s, 5.1837s/12 iters), loss = 4.46219
I0405 15:32:14.321486 18799 solver.cpp:237]     Train net output #0: loss = 4.46219 (* 1 = 4.46219 loss)
I0405 15:32:14.321492 18799 sgd_solver.cpp:105] Iteration 18504, lr = 0.0001
I0405 15:32:17.219542 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:32:19.768419 18799 solver.cpp:218] Iteration 18516 (2.20309 iter/s, 5.44689s/12 iters), loss = 4.28681
I0405 15:32:19.768473 18799 solver.cpp:237]     Train net output #0: loss = 4.28681 (* 1 = 4.28681 loss)
I0405 15:32:19.768482 18799 sgd_solver.cpp:105] Iteration 18516, lr = 0.0001
I0405 15:32:25.111579 18799 solver.cpp:218] Iteration 18528 (2.2459 iter/s, 5.34307s/12 iters), loss = 4.47359
I0405 15:32:25.111618 18799 solver.cpp:237]     Train net output #0: loss = 4.47359 (* 1 = 4.47359 loss)
I0405 15:32:25.111624 18799 sgd_solver.cpp:105] Iteration 18528, lr = 0.0001
I0405 15:32:30.280808 18799 solver.cpp:218] Iteration 18540 (2.32147 iter/s, 5.16915s/12 iters), loss = 4.36249
I0405 15:32:30.280849 18799 solver.cpp:237]     Train net output #0: loss = 4.36249 (* 1 = 4.36249 loss)
I0405 15:32:30.280856 18799 sgd_solver.cpp:105] Iteration 18540, lr = 0.0001
I0405 15:32:35.650797 18799 solver.cpp:218] Iteration 18552 (2.23468 iter/s, 5.3699s/12 iters), loss = 4.43385
I0405 15:32:35.650847 18799 solver.cpp:237]     Train net output #0: loss = 4.43385 (* 1 = 4.43385 loss)
I0405 15:32:35.650856 18799 sgd_solver.cpp:105] Iteration 18552, lr = 0.0001
I0405 15:32:40.392827 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18564.caffemodel
I0405 15:32:43.411705 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18564.solverstate
I0405 15:32:45.718753 18799 solver.cpp:330] Iteration 18564, Testing net (#0)
I0405 15:32:45.718776 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:32:47.533732 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:32:50.237650 18799 solver.cpp:397]     Test net output #0: accuracy = 0.060049
I0405 15:32:50.237685 18799 solver.cpp:397]     Test net output #1: loss = 4.68246 (* 1 = 4.68246 loss)
I0405 15:32:50.379439 18799 solver.cpp:218] Iteration 18564 (0.814746 iter/s, 14.7285s/12 iters), loss = 4.49911
I0405 15:32:50.379506 18799 solver.cpp:237]     Train net output #0: loss = 4.49911 (* 1 = 4.49911 loss)
I0405 15:32:50.379513 18799 sgd_solver.cpp:105] Iteration 18564, lr = 0.0001
I0405 15:32:55.030670 18799 solver.cpp:218] Iteration 18576 (2.58002 iter/s, 4.65112s/12 iters), loss = 4.64467
I0405 15:32:55.030719 18799 solver.cpp:237]     Train net output #0: loss = 4.64467 (* 1 = 4.64467 loss)
I0405 15:32:55.030726 18799 sgd_solver.cpp:105] Iteration 18576, lr = 0.0001
I0405 15:33:00.326225 18799 solver.cpp:218] Iteration 18588 (2.26609 iter/s, 5.29546s/12 iters), loss = 4.28297
I0405 15:33:00.326272 18799 solver.cpp:237]     Train net output #0: loss = 4.28297 (* 1 = 4.28297 loss)
I0405 15:33:00.326280 18799 sgd_solver.cpp:105] Iteration 18588, lr = 0.0001
I0405 15:33:05.557090 18799 solver.cpp:218] Iteration 18600 (2.29412 iter/s, 5.23078s/12 iters), loss = 4.48178
I0405 15:33:05.557143 18799 solver.cpp:237]     Train net output #0: loss = 4.48178 (* 1 = 4.48178 loss)
I0405 15:33:05.557152 18799 sgd_solver.cpp:105] Iteration 18600, lr = 0.0001
I0405 15:33:10.719051 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:33:10.940304 18799 solver.cpp:218] Iteration 18612 (2.22919 iter/s, 5.38312s/12 iters), loss = 4.61019
I0405 15:33:10.940358 18799 solver.cpp:237]     Train net output #0: loss = 4.61019 (* 1 = 4.61019 loss)
I0405 15:33:10.940366 18799 sgd_solver.cpp:105] Iteration 18612, lr = 0.0001
I0405 15:33:16.310814 18799 solver.cpp:218] Iteration 18624 (2.23446 iter/s, 5.37041s/12 iters), loss = 4.56477
I0405 15:33:16.310858 18799 solver.cpp:237]     Train net output #0: loss = 4.56477 (* 1 = 4.56477 loss)
I0405 15:33:16.310864 18799 sgd_solver.cpp:105] Iteration 18624, lr = 0.0001
I0405 15:33:21.669265 18799 solver.cpp:218] Iteration 18636 (2.23949 iter/s, 5.35836s/12 iters), loss = 4.43654
I0405 15:33:21.669304 18799 solver.cpp:237]     Train net output #0: loss = 4.43654 (* 1 = 4.43654 loss)
I0405 15:33:21.669309 18799 sgd_solver.cpp:105] Iteration 18636, lr = 0.0001
I0405 15:33:27.027691 18799 solver.cpp:218] Iteration 18648 (2.2395 iter/s, 5.35834s/12 iters), loss = 4.53257
I0405 15:33:27.027730 18799 solver.cpp:237]     Train net output #0: loss = 4.53257 (* 1 = 4.53257 loss)
I0405 15:33:27.027736 18799 sgd_solver.cpp:105] Iteration 18648, lr = 0.0001
I0405 15:33:32.360042 18799 solver.cpp:218] Iteration 18660 (2.25045 iter/s, 5.33227s/12 iters), loss = 4.3495
I0405 15:33:32.360085 18799 solver.cpp:237]     Train net output #0: loss = 4.3495 (* 1 = 4.3495 loss)
I0405 15:33:32.360090 18799 sgd_solver.cpp:105] Iteration 18660, lr = 0.0001
I0405 15:33:34.549335 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18666.caffemodel
I0405 15:33:37.560374 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18666.solverstate
I0405 15:33:39.875533 18799 solver.cpp:330] Iteration 18666, Testing net (#0)
I0405 15:33:39.875557 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:33:41.588116 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:33:44.232723 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0643382
I0405 15:33:44.232759 18799 solver.cpp:397]     Test net output #1: loss = 4.67496 (* 1 = 4.67496 loss)
I0405 15:33:46.140166 18799 solver.cpp:218] Iteration 18672 (0.870827 iter/s, 13.78s/12 iters), loss = 4.40738
I0405 15:33:46.140220 18799 solver.cpp:237]     Train net output #0: loss = 4.40738 (* 1 = 4.40738 loss)
I0405 15:33:46.140229 18799 sgd_solver.cpp:105] Iteration 18672, lr = 0.0001
I0405 15:33:51.513689 18799 solver.cpp:218] Iteration 18684 (2.23321 iter/s, 5.37343s/12 iters), loss = 4.39543
I0405 15:33:51.513731 18799 solver.cpp:237]     Train net output #0: loss = 4.39543 (* 1 = 4.39543 loss)
I0405 15:33:51.513737 18799 sgd_solver.cpp:105] Iteration 18684, lr = 0.0001
I0405 15:33:56.953007 18799 solver.cpp:218] Iteration 18696 (2.20619 iter/s, 5.43924s/12 iters), loss = 4.42066
I0405 15:33:56.953047 18799 solver.cpp:237]     Train net output #0: loss = 4.42066 (* 1 = 4.42066 loss)
I0405 15:33:56.953052 18799 sgd_solver.cpp:105] Iteration 18696, lr = 0.0001
I0405 15:34:02.235832 18799 solver.cpp:218] Iteration 18708 (2.27155 iter/s, 5.28274s/12 iters), loss = 4.30492
I0405 15:34:02.235870 18799 solver.cpp:237]     Train net output #0: loss = 4.30492 (* 1 = 4.30492 loss)
I0405 15:34:02.235877 18799 sgd_solver.cpp:105] Iteration 18708, lr = 0.0001
I0405 15:34:04.396196 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:34:07.723412 18799 solver.cpp:218] Iteration 18720 (2.18679 iter/s, 5.4875s/12 iters), loss = 4.44255
I0405 15:34:07.723451 18799 solver.cpp:237]     Train net output #0: loss = 4.44255 (* 1 = 4.44255 loss)
I0405 15:34:07.723456 18799 sgd_solver.cpp:105] Iteration 18720, lr = 0.0001
I0405 15:34:08.091344 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:34:12.910995 18799 solver.cpp:218] Iteration 18732 (2.31325 iter/s, 5.1875s/12 iters), loss = 4.56322
I0405 15:34:12.911078 18799 solver.cpp:237]     Train net output #0: loss = 4.56322 (* 1 = 4.56322 loss)
I0405 15:34:12.911084 18799 sgd_solver.cpp:105] Iteration 18732, lr = 0.0001
I0405 15:34:18.394894 18799 solver.cpp:218] Iteration 18744 (2.18827 iter/s, 5.48378s/12 iters), loss = 4.29734
I0405 15:34:18.394932 18799 solver.cpp:237]     Train net output #0: loss = 4.29734 (* 1 = 4.29734 loss)
I0405 15:34:18.394938 18799 sgd_solver.cpp:105] Iteration 18744, lr = 0.0001
I0405 15:34:23.714866 18799 solver.cpp:218] Iteration 18756 (2.25569 iter/s, 5.31989s/12 iters), loss = 4.47391
I0405 15:34:23.714922 18799 solver.cpp:237]     Train net output #0: loss = 4.47391 (* 1 = 4.47391 loss)
I0405 15:34:23.714931 18799 sgd_solver.cpp:105] Iteration 18756, lr = 0.0001
I0405 15:34:28.535681 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18768.caffemodel
I0405 15:34:31.973717 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18768.solverstate
I0405 15:34:34.640162 18799 solver.cpp:330] Iteration 18768, Testing net (#0)
I0405 15:34:34.640187 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:34:36.300438 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:34:39.012681 18799 solver.cpp:397]     Test net output #0: accuracy = 0.067402
I0405 15:34:39.012715 18799 solver.cpp:397]     Test net output #1: loss = 4.67047 (* 1 = 4.67047 loss)
I0405 15:34:39.150399 18799 solver.cpp:218] Iteration 18768 (0.777434 iter/s, 15.4354s/12 iters), loss = 4.48289
I0405 15:34:39.150451 18799 solver.cpp:237]     Train net output #0: loss = 4.48289 (* 1 = 4.48289 loss)
I0405 15:34:39.150460 18799 sgd_solver.cpp:105] Iteration 18768, lr = 0.0001
I0405 15:34:43.482029 18799 solver.cpp:218] Iteration 18780 (2.77038 iter/s, 4.33154s/12 iters), loss = 4.53242
I0405 15:34:43.482157 18799 solver.cpp:237]     Train net output #0: loss = 4.53242 (* 1 = 4.53242 loss)
I0405 15:34:43.482164 18799 sgd_solver.cpp:105] Iteration 18780, lr = 0.0001
I0405 15:34:48.803849 18799 solver.cpp:218] Iteration 18792 (2.25494 iter/s, 5.32166s/12 iters), loss = 4.60266
I0405 15:34:48.803885 18799 solver.cpp:237]     Train net output #0: loss = 4.60266 (* 1 = 4.60266 loss)
I0405 15:34:48.803890 18799 sgd_solver.cpp:105] Iteration 18792, lr = 0.0001
I0405 15:34:54.084066 18799 solver.cpp:218] Iteration 18804 (2.27267 iter/s, 5.28013s/12 iters), loss = 4.25292
I0405 15:34:54.084110 18799 solver.cpp:237]     Train net output #0: loss = 4.25292 (* 1 = 4.25292 loss)
I0405 15:34:54.084116 18799 sgd_solver.cpp:105] Iteration 18804, lr = 0.0001
I0405 15:34:58.316506 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:34:59.200906 18799 solver.cpp:218] Iteration 18816 (2.34524 iter/s, 5.11676s/12 iters), loss = 4.46442
I0405 15:34:59.200951 18799 solver.cpp:237]     Train net output #0: loss = 4.46442 (* 1 = 4.46442 loss)
I0405 15:34:59.200956 18799 sgd_solver.cpp:105] Iteration 18816, lr = 0.0001
I0405 15:35:04.535004 18799 solver.cpp:218] Iteration 18828 (2.24972 iter/s, 5.33401s/12 iters), loss = 4.4068
I0405 15:35:04.535054 18799 solver.cpp:237]     Train net output #0: loss = 4.4068 (* 1 = 4.4068 loss)
I0405 15:35:04.535060 18799 sgd_solver.cpp:105] Iteration 18828, lr = 0.0001
I0405 15:35:09.949936 18799 solver.cpp:218] Iteration 18840 (2.21613 iter/s, 5.41484s/12 iters), loss = 4.44397
I0405 15:35:09.949980 18799 solver.cpp:237]     Train net output #0: loss = 4.44397 (* 1 = 4.44397 loss)
I0405 15:35:09.949985 18799 sgd_solver.cpp:105] Iteration 18840, lr = 0.0001
I0405 15:35:15.259105 18799 solver.cpp:218] Iteration 18852 (2.26028 iter/s, 5.30907s/12 iters), loss = 4.21309
I0405 15:35:15.259243 18799 solver.cpp:237]     Train net output #0: loss = 4.21309 (* 1 = 4.21309 loss)
I0405 15:35:15.259253 18799 sgd_solver.cpp:105] Iteration 18852, lr = 0.0001
I0405 15:35:20.706235 18799 solver.cpp:218] Iteration 18864 (2.20307 iter/s, 5.44695s/12 iters), loss = 4.34306
I0405 15:35:20.706295 18799 solver.cpp:237]     Train net output #0: loss = 4.34306 (* 1 = 4.34306 loss)
I0405 15:35:20.706303 18799 sgd_solver.cpp:105] Iteration 18864, lr = 0.0001
I0405 15:35:22.851061 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18870.caffemodel
I0405 15:35:26.025080 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18870.solverstate
I0405 15:35:28.320257 18799 solver.cpp:330] Iteration 18870, Testing net (#0)
I0405 15:35:28.320279 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:35:29.895867 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:35:32.781004 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0655637
I0405 15:35:32.781044 18799 solver.cpp:397]     Test net output #1: loss = 4.66671 (* 1 = 4.66671 loss)
I0405 15:35:34.671018 18799 solver.cpp:218] Iteration 18876 (0.859313 iter/s, 13.9646s/12 iters), loss = 4.5046
I0405 15:35:34.671056 18799 solver.cpp:237]     Train net output #0: loss = 4.5046 (* 1 = 4.5046 loss)
I0405 15:35:34.671061 18799 sgd_solver.cpp:105] Iteration 18876, lr = 0.0001
I0405 15:35:39.870296 18799 solver.cpp:218] Iteration 18888 (2.30805 iter/s, 5.19919s/12 iters), loss = 4.35927
I0405 15:35:39.870340 18799 solver.cpp:237]     Train net output #0: loss = 4.35927 (* 1 = 4.35927 loss)
I0405 15:35:39.870347 18799 sgd_solver.cpp:105] Iteration 18888, lr = 0.0001
I0405 15:35:45.152357 18799 solver.cpp:218] Iteration 18900 (2.27188 iter/s, 5.28198s/12 iters), loss = 4.45478
I0405 15:35:45.152400 18799 solver.cpp:237]     Train net output #0: loss = 4.45478 (* 1 = 4.45478 loss)
I0405 15:35:45.152406 18799 sgd_solver.cpp:105] Iteration 18900, lr = 0.0001
I0405 15:35:50.626307 18799 solver.cpp:218] Iteration 18912 (2.19224 iter/s, 5.47386s/12 iters), loss = 4.51739
I0405 15:35:50.626416 18799 solver.cpp:237]     Train net output #0: loss = 4.51739 (* 1 = 4.51739 loss)
I0405 15:35:50.626423 18799 sgd_solver.cpp:105] Iteration 18912, lr = 0.0001
I0405 15:35:52.043495 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:35:56.103860 18799 solver.cpp:218] Iteration 18924 (2.19082 iter/s, 5.4774s/12 iters), loss = 4.3903
I0405 15:35:56.103906 18799 solver.cpp:237]     Train net output #0: loss = 4.3903 (* 1 = 4.3903 loss)
I0405 15:35:56.103912 18799 sgd_solver.cpp:105] Iteration 18924, lr = 0.0001
I0405 15:36:01.528266 18799 solver.cpp:218] Iteration 18936 (2.21226 iter/s, 5.42431s/12 iters), loss = 4.42034
I0405 15:36:01.528322 18799 solver.cpp:237]     Train net output #0: loss = 4.42034 (* 1 = 4.42034 loss)
I0405 15:36:01.528332 18799 sgd_solver.cpp:105] Iteration 18936, lr = 0.0001
I0405 15:36:06.711536 18799 solver.cpp:218] Iteration 18948 (2.31518 iter/s, 5.18318s/12 iters), loss = 4.43031
I0405 15:36:06.711576 18799 solver.cpp:237]     Train net output #0: loss = 4.43031 (* 1 = 4.43031 loss)
I0405 15:36:06.711582 18799 sgd_solver.cpp:105] Iteration 18948, lr = 0.0001
I0405 15:36:11.983557 18799 solver.cpp:218] Iteration 18960 (2.2762 iter/s, 5.27194s/12 iters), loss = 4.48392
I0405 15:36:11.983608 18799 solver.cpp:237]     Train net output #0: loss = 4.48392 (* 1 = 4.48392 loss)
I0405 15:36:11.983613 18799 sgd_solver.cpp:105] Iteration 18960, lr = 0.0001
I0405 15:36:16.751085 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18972.caffemodel
I0405 15:36:19.766131 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18972.solverstate
I0405 15:36:22.069450 18799 solver.cpp:330] Iteration 18972, Testing net (#0)
I0405 15:36:22.069528 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:36:23.584756 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:36:26.399693 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0655637
I0405 15:36:26.399721 18799 solver.cpp:397]     Test net output #1: loss = 4.65406 (* 1 = 4.65406 loss)
I0405 15:36:26.537274 18799 solver.cpp:218] Iteration 18972 (0.824539 iter/s, 14.5536s/12 iters), loss = 4.29287
I0405 15:36:26.537317 18799 solver.cpp:237]     Train net output #0: loss = 4.29287 (* 1 = 4.29287 loss)
I0405 15:36:26.537322 18799 sgd_solver.cpp:105] Iteration 18972, lr = 0.0001
I0405 15:36:30.997175 18799 solver.cpp:218] Iteration 18984 (2.69069 iter/s, 4.45982s/12 iters), loss = 4.31884
I0405 15:36:30.997221 18799 solver.cpp:237]     Train net output #0: loss = 4.31884 (* 1 = 4.31884 loss)
I0405 15:36:30.997228 18799 sgd_solver.cpp:105] Iteration 18984, lr = 0.0001
I0405 15:36:36.452512 18799 solver.cpp:218] Iteration 18996 (2.19972 iter/s, 5.45524s/12 iters), loss = 4.20829
I0405 15:36:36.452562 18799 solver.cpp:237]     Train net output #0: loss = 4.20829 (* 1 = 4.20829 loss)
I0405 15:36:36.452574 18799 sgd_solver.cpp:105] Iteration 18996, lr = 0.0001
I0405 15:36:41.616067 18799 solver.cpp:218] Iteration 19008 (2.32402 iter/s, 5.16347s/12 iters), loss = 4.44244
I0405 15:36:41.616109 18799 solver.cpp:237]     Train net output #0: loss = 4.44244 (* 1 = 4.44244 loss)
I0405 15:36:41.616114 18799 sgd_solver.cpp:105] Iteration 19008, lr = 0.0001
I0405 15:36:45.206178 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:36:46.789873 18799 solver.cpp:218] Iteration 19020 (2.31942 iter/s, 5.17372s/12 iters), loss = 4.27065
I0405 15:36:46.789924 18799 solver.cpp:237]     Train net output #0: loss = 4.27065 (* 1 = 4.27065 loss)
I0405 15:36:46.789933 18799 sgd_solver.cpp:105] Iteration 19020, lr = 0.0001
I0405 15:36:52.102686 18799 solver.cpp:218] Iteration 19032 (2.25873 iter/s, 5.31272s/12 iters), loss = 4.44593
I0405 15:36:52.102807 18799 solver.cpp:237]     Train net output #0: loss = 4.44593 (* 1 = 4.44593 loss)
I0405 15:36:52.102813 18799 sgd_solver.cpp:105] Iteration 19032, lr = 0.0001
I0405 15:36:57.181771 18799 solver.cpp:218] Iteration 19044 (2.3627 iter/s, 5.07893s/12 iters), loss = 4.47757
I0405 15:36:57.181811 18799 solver.cpp:237]     Train net output #0: loss = 4.47757 (* 1 = 4.47757 loss)
I0405 15:36:57.181816 18799 sgd_solver.cpp:105] Iteration 19044, lr = 0.0001
I0405 15:37:02.386277 18799 solver.cpp:218] Iteration 19056 (2.30573 iter/s, 5.20442s/12 iters), loss = 4.26485
I0405 15:37:02.386317 18799 solver.cpp:237]     Train net output #0: loss = 4.26485 (* 1 = 4.26485 loss)
I0405 15:37:02.386322 18799 sgd_solver.cpp:105] Iteration 19056, lr = 0.0001
I0405 15:37:07.628229 18799 solver.cpp:218] Iteration 19068 (2.28926 iter/s, 5.24187s/12 iters), loss = 4.45294
I0405 15:37:07.628268 18799 solver.cpp:237]     Train net output #0: loss = 4.45294 (* 1 = 4.45294 loss)
I0405 15:37:07.628273 18799 sgd_solver.cpp:105] Iteration 19068, lr = 0.0001
I0405 15:37:09.728801 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19074.caffemodel
I0405 15:37:12.734553 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19074.solverstate
I0405 15:37:15.029330 18799 solver.cpp:330] Iteration 19074, Testing net (#0)
I0405 15:37:15.029348 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:37:16.549017 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:37:19.350968 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0667892
I0405 15:37:19.351006 18799 solver.cpp:397]     Test net output #1: loss = 4.64921 (* 1 = 4.64921 loss)
I0405 15:37:21.248481 18799 solver.cpp:218] Iteration 19080 (0.881049 iter/s, 13.6201s/12 iters), loss = 4.23628
I0405 15:37:21.248533 18799 solver.cpp:237]     Train net output #0: loss = 4.23628 (* 1 = 4.23628 loss)
I0405 15:37:21.248540 18799 sgd_solver.cpp:105] Iteration 19080, lr = 0.0001
I0405 15:37:26.479714 18799 solver.cpp:218] Iteration 19092 (2.29395 iter/s, 5.23114s/12 iters), loss = 4.26836
I0405 15:37:26.479810 18799 solver.cpp:237]     Train net output #0: loss = 4.26836 (* 1 = 4.26836 loss)
I0405 15:37:26.479816 18799 sgd_solver.cpp:105] Iteration 19092, lr = 0.0001
I0405 15:37:31.710453 18799 solver.cpp:218] Iteration 19104 (2.29419 iter/s, 5.2306s/12 iters), loss = 4.46721
I0405 15:37:31.710496 18799 solver.cpp:237]     Train net output #0: loss = 4.46721 (* 1 = 4.46721 loss)
I0405 15:37:31.710503 18799 sgd_solver.cpp:105] Iteration 19104, lr = 0.0001
I0405 15:37:36.879886 18799 solver.cpp:218] Iteration 19116 (2.32138 iter/s, 5.16934s/12 iters), loss = 4.34093
I0405 15:37:36.879951 18799 solver.cpp:237]     Train net output #0: loss = 4.34093 (* 1 = 4.34093 loss)
I0405 15:37:36.879959 18799 sgd_solver.cpp:105] Iteration 19116, lr = 0.0001
I0405 15:37:37.408833 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:37:41.972623 18799 solver.cpp:218] Iteration 19128 (2.35635 iter/s, 5.09263s/12 iters), loss = 4.49125
I0405 15:37:41.972668 18799 solver.cpp:237]     Train net output #0: loss = 4.49125 (* 1 = 4.49125 loss)
I0405 15:37:41.972676 18799 sgd_solver.cpp:105] Iteration 19128, lr = 0.0001
I0405 15:37:47.358470 18799 solver.cpp:218] Iteration 19140 (2.2281 iter/s, 5.38576s/12 iters), loss = 4.52052
I0405 15:37:47.358520 18799 solver.cpp:237]     Train net output #0: loss = 4.52052 (* 1 = 4.52052 loss)
I0405 15:37:47.358528 18799 sgd_solver.cpp:105] Iteration 19140, lr = 0.0001
I0405 15:37:52.636503 18799 solver.cpp:218] Iteration 19152 (2.27361 iter/s, 5.27794s/12 iters), loss = 4.25181
I0405 15:37:52.636541 18799 solver.cpp:237]     Train net output #0: loss = 4.25181 (* 1 = 4.25181 loss)
I0405 15:37:52.636548 18799 sgd_solver.cpp:105] Iteration 19152, lr = 0.0001
I0405 15:37:57.970942 18799 solver.cpp:218] Iteration 19164 (2.24957 iter/s, 5.33435s/12 iters), loss = 4.35974
I0405 15:37:57.971109 18799 solver.cpp:237]     Train net output #0: loss = 4.35974 (* 1 = 4.35974 loss)
I0405 15:37:57.971118 18799 sgd_solver.cpp:105] Iteration 19164, lr = 0.0001
I0405 15:38:02.749887 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19176.caffemodel
I0405 15:38:05.770565 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19176.solverstate
I0405 15:38:08.115602 18799 solver.cpp:330] Iteration 19176, Testing net (#0)
I0405 15:38:08.115624 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:38:09.648609 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:38:12.666429 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0686275
I0405 15:38:12.666467 18799 solver.cpp:397]     Test net output #1: loss = 4.64392 (* 1 = 4.64392 loss)
I0405 15:38:12.808524 18799 solver.cpp:218] Iteration 19176 (0.808771 iter/s, 14.8373s/12 iters), loss = 4.31487
I0405 15:38:12.810086 18799 solver.cpp:237]     Train net output #0: loss = 4.31487 (* 1 = 4.31487 loss)
I0405 15:38:12.810094 18799 sgd_solver.cpp:105] Iteration 19176, lr = 0.0001
I0405 15:38:17.382247 18799 solver.cpp:218] Iteration 19188 (2.6246 iter/s, 4.57212s/12 iters), loss = 4.00963
I0405 15:38:17.382298 18799 solver.cpp:237]     Train net output #0: loss = 4.00963 (* 1 = 4.00963 loss)
I0405 15:38:17.382306 18799 sgd_solver.cpp:105] Iteration 19188, lr = 0.0001
I0405 15:38:22.849678 18799 solver.cpp:218] Iteration 19200 (2.19486 iter/s, 5.46733s/12 iters), loss = 4.30228
I0405 15:38:22.849735 18799 solver.cpp:237]     Train net output #0: loss = 4.30228 (* 1 = 4.30228 loss)
I0405 15:38:22.849740 18799 sgd_solver.cpp:105] Iteration 19200, lr = 0.0001
I0405 15:38:28.072675 18799 solver.cpp:218] Iteration 19212 (2.29758 iter/s, 5.2229s/12 iters), loss = 4.45089
I0405 15:38:28.072764 18799 solver.cpp:237]     Train net output #0: loss = 4.45089 (* 1 = 4.45089 loss)
I0405 15:38:28.072770 18799 sgd_solver.cpp:105] Iteration 19212, lr = 0.0001
I0405 15:38:31.189054 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:38:33.699106 18799 solver.cpp:218] Iteration 19224 (2.13284 iter/s, 5.6263s/12 iters), loss = 4.19402
I0405 15:38:33.699146 18799 solver.cpp:237]     Train net output #0: loss = 4.19402 (* 1 = 4.19402 loss)
I0405 15:38:33.699151 18799 sgd_solver.cpp:105] Iteration 19224, lr = 0.0001
I0405 15:38:38.887123 18799 solver.cpp:218] Iteration 19236 (2.31306 iter/s, 5.18793s/12 iters), loss = 4.46338
I0405 15:38:38.887174 18799 solver.cpp:237]     Train net output #0: loss = 4.46338 (* 1 = 4.46338 loss)
I0405 15:38:38.887181 18799 sgd_solver.cpp:105] Iteration 19236, lr = 0.0001
I0405 15:38:44.236405 18799 solver.cpp:218] Iteration 19248 (2.24333 iter/s, 5.34919s/12 iters), loss = 4.44803
I0405 15:38:44.236456 18799 solver.cpp:237]     Train net output #0: loss = 4.44803 (* 1 = 4.44803 loss)
I0405 15:38:44.236464 18799 sgd_solver.cpp:105] Iteration 19248, lr = 0.0001
I0405 15:38:49.534011 18799 solver.cpp:218] Iteration 19260 (2.26521 iter/s, 5.29751s/12 iters), loss = 4.34113
I0405 15:38:49.534054 18799 solver.cpp:237]     Train net output #0: loss = 4.34113 (* 1 = 4.34113 loss)
I0405 15:38:49.534060 18799 sgd_solver.cpp:105] Iteration 19260, lr = 0.0001
I0405 15:38:54.919065 18799 solver.cpp:218] Iteration 19272 (2.22843 iter/s, 5.38496s/12 iters), loss = 4.45771
I0405 15:38:54.919111 18799 solver.cpp:237]     Train net output #0: loss = 4.45771 (* 1 = 4.45771 loss)
I0405 15:38:54.919116 18799 sgd_solver.cpp:105] Iteration 19272, lr = 0.0001
I0405 15:38:57.134192 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19278.caffemodel
I0405 15:39:00.158799 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19278.solverstate
I0405 15:39:03.239601 18799 solver.cpp:330] Iteration 19278, Testing net (#0)
I0405 15:39:03.239625 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:39:04.824879 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:39:07.727454 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0643382
I0405 15:39:07.727490 18799 solver.cpp:397]     Test net output #1: loss = 4.64609 (* 1 = 4.64609 loss)
I0405 15:39:09.665606 18799 solver.cpp:218] Iteration 19284 (0.813758 iter/s, 14.7464s/12 iters), loss = 4.44858
I0405 15:39:09.665647 18799 solver.cpp:237]     Train net output #0: loss = 4.44858 (* 1 = 4.44858 loss)
I0405 15:39:09.665652 18799 sgd_solver.cpp:105] Iteration 19284, lr = 0.0001
I0405 15:39:15.420173 18799 solver.cpp:218] Iteration 19296 (2.08533 iter/s, 5.75448s/12 iters), loss = 4.40489
I0405 15:39:15.420213 18799 solver.cpp:237]     Train net output #0: loss = 4.40489 (* 1 = 4.40489 loss)
I0405 15:39:15.420220 18799 sgd_solver.cpp:105] Iteration 19296, lr = 0.0001
I0405 15:39:20.894032 18799 solver.cpp:218] Iteration 19308 (2.19227 iter/s, 5.47378s/12 iters), loss = 4.40885
I0405 15:39:20.894074 18799 solver.cpp:237]     Train net output #0: loss = 4.40885 (* 1 = 4.40885 loss)
I0405 15:39:20.894081 18799 sgd_solver.cpp:105] Iteration 19308, lr = 0.0001
I0405 15:39:26.090807 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:39:26.284055 18799 solver.cpp:218] Iteration 19320 (2.22637 iter/s, 5.38994s/12 iters), loss = 4.39446
I0405 15:39:26.284099 18799 solver.cpp:237]     Train net output #0: loss = 4.39446 (* 1 = 4.39446 loss)
I0405 15:39:26.284106 18799 sgd_solver.cpp:105] Iteration 19320, lr = 0.0001
I0405 15:39:31.732934 18799 solver.cpp:218] Iteration 19332 (2.20232 iter/s, 5.44879s/12 iters), loss = 4.46766
I0405 15:39:31.733055 18799 solver.cpp:237]     Train net output #0: loss = 4.46766 (* 1 = 4.46766 loss)
I0405 15:39:31.733064 18799 sgd_solver.cpp:105] Iteration 19332, lr = 0.0001
I0405 15:39:36.927637 18799 solver.cpp:218] Iteration 19344 (2.31012 iter/s, 5.19454s/12 iters), loss = 4.40608
I0405 15:39:36.927687 18799 solver.cpp:237]     Train net output #0: loss = 4.40608 (* 1 = 4.40608 loss)
I0405 15:39:36.927695 18799 sgd_solver.cpp:105] Iteration 19344, lr = 0.0001
I0405 15:39:42.279670 18799 solver.cpp:218] Iteration 19356 (2.24217 iter/s, 5.35195s/12 iters), loss = 4.34956
I0405 15:39:42.279711 18799 solver.cpp:237]     Train net output #0: loss = 4.34956 (* 1 = 4.34956 loss)
I0405 15:39:42.279717 18799 sgd_solver.cpp:105] Iteration 19356, lr = 0.0001
I0405 15:39:47.770753 18799 solver.cpp:218] Iteration 19368 (2.1854 iter/s, 5.491s/12 iters), loss = 4.19138
I0405 15:39:47.770797 18799 solver.cpp:237]     Train net output #0: loss = 4.19138 (* 1 = 4.19138 loss)
I0405 15:39:47.770802 18799 sgd_solver.cpp:105] Iteration 19368, lr = 0.0001
I0405 15:39:52.613152 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19380.caffemodel
I0405 15:39:56.445353 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19380.solverstate
I0405 15:39:58.826665 18799 solver.cpp:330] Iteration 19380, Testing net (#0)
I0405 15:39:58.826689 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:40:00.295064 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:40:03.262229 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0698529
I0405 15:40:03.262320 18799 solver.cpp:397]     Test net output #1: loss = 4.64377 (* 1 = 4.64377 loss)
I0405 15:40:03.407482 18799 solver.cpp:218] Iteration 19380 (0.76743 iter/s, 15.6366s/12 iters), loss = 4.42581
I0405 15:40:03.407538 18799 solver.cpp:237]     Train net output #0: loss = 4.42581 (* 1 = 4.42581 loss)
I0405 15:40:03.407546 18799 sgd_solver.cpp:105] Iteration 19380, lr = 0.0001
I0405 15:40:07.967229 18799 solver.cpp:218] Iteration 19392 (2.63178 iter/s, 4.55965s/12 iters), loss = 4.29624
I0405 15:40:07.967279 18799 solver.cpp:237]     Train net output #0: loss = 4.29624 (* 1 = 4.29624 loss)
I0405 15:40:07.967288 18799 sgd_solver.cpp:105] Iteration 19392, lr = 0.0001
I0405 15:40:13.530530 18799 solver.cpp:218] Iteration 19404 (2.15703 iter/s, 5.56321s/12 iters), loss = 4.35167
I0405 15:40:13.530577 18799 solver.cpp:237]     Train net output #0: loss = 4.35167 (* 1 = 4.35167 loss)
I0405 15:40:13.530583 18799 sgd_solver.cpp:105] Iteration 19404, lr = 0.0001
I0405 15:40:14.377205 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:40:18.907553 18799 solver.cpp:218] Iteration 19416 (2.23175 iter/s, 5.37694s/12 iters), loss = 4.32561
I0405 15:40:18.907591 18799 solver.cpp:237]     Train net output #0: loss = 4.32561 (* 1 = 4.32561 loss)
I0405 15:40:18.907596 18799 sgd_solver.cpp:105] Iteration 19416, lr = 0.0001
I0405 15:40:21.142704 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:40:24.497098 18799 solver.cpp:218] Iteration 19428 (2.1469 iter/s, 5.58946s/12 iters), loss = 4.29704
I0405 15:40:24.497151 18799 solver.cpp:237]     Train net output #0: loss = 4.29704 (* 1 = 4.29704 loss)
I0405 15:40:24.497159 18799 sgd_solver.cpp:105] Iteration 19428, lr = 0.0001
I0405 15:40:29.863662 18799 solver.cpp:218] Iteration 19440 (2.23611 iter/s, 5.36647s/12 iters), loss = 4.52947
I0405 15:40:29.863720 18799 solver.cpp:237]     Train net output #0: loss = 4.52947 (* 1 = 4.52947 loss)
I0405 15:40:29.863729 18799 sgd_solver.cpp:105] Iteration 19440, lr = 0.0001
I0405 15:40:35.078511 18799 solver.cpp:218] Iteration 19452 (2.30116 iter/s, 5.21475s/12 iters), loss = 4.29694
I0405 15:40:35.079056 18799 solver.cpp:237]     Train net output #0: loss = 4.29694 (* 1 = 4.29694 loss)
I0405 15:40:35.079063 18799 sgd_solver.cpp:105] Iteration 19452, lr = 0.0001
I0405 15:40:40.438576 18799 solver.cpp:218] Iteration 19464 (2.23902 iter/s, 5.35948s/12 iters), loss = 4.37712
I0405 15:40:40.438624 18799 solver.cpp:237]     Train net output #0: loss = 4.37712 (* 1 = 4.37712 loss)
I0405 15:40:40.438630 18799 sgd_solver.cpp:105] Iteration 19464, lr = 0.0001
I0405 15:40:45.625021 18799 solver.cpp:218] Iteration 19476 (2.31376 iter/s, 5.18636s/12 iters), loss = 4.31741
I0405 15:40:45.625063 18799 solver.cpp:237]     Train net output #0: loss = 4.31741 (* 1 = 4.31741 loss)
I0405 15:40:45.625069 18799 sgd_solver.cpp:105] Iteration 19476, lr = 0.0001
I0405 15:40:47.853806 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19482.caffemodel
I0405 15:40:50.898633 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19482.solverstate
I0405 15:40:53.205056 18799 solver.cpp:330] Iteration 19482, Testing net (#0)
I0405 15:40:53.205075 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:40:54.537842 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:40:57.730453 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0655637
I0405 15:40:57.730489 18799 solver.cpp:397]     Test net output #1: loss = 4.63718 (* 1 = 4.63718 loss)
I0405 15:40:59.581157 18799 solver.cpp:218] Iteration 19488 (0.859845 iter/s, 13.956s/12 iters), loss = 4.55263
I0405 15:40:59.581213 18799 solver.cpp:237]     Train net output #0: loss = 4.55263 (* 1 = 4.55263 loss)
I0405 15:40:59.581220 18799 sgd_solver.cpp:105] Iteration 19488, lr = 0.0001
I0405 15:41:04.780741 18799 solver.cpp:218] Iteration 19500 (2.30792 iter/s, 5.19948s/12 iters), loss = 4.50783
I0405 15:41:04.780792 18799 solver.cpp:237]     Train net output #0: loss = 4.50783 (* 1 = 4.50783 loss)
I0405 15:41:04.780800 18799 sgd_solver.cpp:105] Iteration 19500, lr = 0.0001
I0405 15:41:10.140122 18799 solver.cpp:218] Iteration 19512 (2.2391 iter/s, 5.35929s/12 iters), loss = 4.21045
I0405 15:41:10.140246 18799 solver.cpp:237]     Train net output #0: loss = 4.21045 (* 1 = 4.21045 loss)
I0405 15:41:10.140254 18799 sgd_solver.cpp:105] Iteration 19512, lr = 0.0001
I0405 15:41:14.628368 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:41:15.487203 18799 solver.cpp:218] Iteration 19524 (2.24428 iter/s, 5.34692s/12 iters), loss = 4.38252
I0405 15:41:15.487258 18799 solver.cpp:237]     Train net output #0: loss = 4.38252 (* 1 = 4.38252 loss)
I0405 15:41:15.487267 18799 sgd_solver.cpp:105] Iteration 19524, lr = 0.0001
I0405 15:41:21.007604 18799 solver.cpp:218] Iteration 19536 (2.17379 iter/s, 5.5203s/12 iters), loss = 4.42273
I0405 15:41:21.007652 18799 solver.cpp:237]     Train net output #0: loss = 4.42273 (* 1 = 4.42273 loss)
I0405 15:41:21.007661 18799 sgd_solver.cpp:105] Iteration 19536, lr = 0.0001
I0405 15:41:26.252002 18799 solver.cpp:218] Iteration 19548 (2.28819 iter/s, 5.24431s/12 iters), loss = 4.30365
I0405 15:41:26.252039 18799 solver.cpp:237]     Train net output #0: loss = 4.30365 (* 1 = 4.30365 loss)
I0405 15:41:26.252044 18799 sgd_solver.cpp:105] Iteration 19548, lr = 0.0001
I0405 15:41:31.720548 18799 solver.cpp:218] Iteration 19560 (2.1944 iter/s, 5.46846s/12 iters), loss = 4.31757
I0405 15:41:31.726912 18799 solver.cpp:237]     Train net output #0: loss = 4.31757 (* 1 = 4.31757 loss)
I0405 15:41:31.726933 18799 sgd_solver.cpp:105] Iteration 19560, lr = 0.0001
I0405 15:41:37.079633 18799 solver.cpp:218] Iteration 19572 (2.24186 iter/s, 5.35269s/12 iters), loss = 4.29975
I0405 15:41:37.079682 18799 solver.cpp:237]     Train net output #0: loss = 4.29975 (* 1 = 4.29975 loss)
I0405 15:41:37.079689 18799 sgd_solver.cpp:105] Iteration 19572, lr = 0.0001
I0405 15:41:41.821002 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19584.caffemodel
I0405 15:41:44.845890 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19584.solverstate
I0405 15:41:47.188410 18799 solver.cpp:330] Iteration 19584, Testing net (#0)
I0405 15:41:47.188436 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:41:48.682790 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:41:51.998394 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0655637
I0405 15:41:51.998433 18799 solver.cpp:397]     Test net output #1: loss = 4.63554 (* 1 = 4.63554 loss)
I0405 15:41:52.142045 18799 solver.cpp:218] Iteration 19584 (0.796692 iter/s, 15.0623s/12 iters), loss = 4.42725
I0405 15:41:52.142087 18799 solver.cpp:237]     Train net output #0: loss = 4.42725 (* 1 = 4.42725 loss)
I0405 15:41:52.142093 18799 sgd_solver.cpp:105] Iteration 19584, lr = 0.0001
I0405 15:41:56.422417 18799 solver.cpp:218] Iteration 19596 (2.80355 iter/s, 4.28029s/12 iters), loss = 4.2996
I0405 15:41:56.422467 18799 solver.cpp:237]     Train net output #0: loss = 4.2996 (* 1 = 4.2996 loss)
I0405 15:41:56.422474 18799 sgd_solver.cpp:105] Iteration 19596, lr = 0.0001
I0405 15:42:01.756361 18799 solver.cpp:218] Iteration 19608 (2.24978 iter/s, 5.33385s/12 iters), loss = 4.48645
I0405 15:42:01.756408 18799 solver.cpp:237]     Train net output #0: loss = 4.48645 (* 1 = 4.48645 loss)
I0405 15:42:01.756414 18799 sgd_solver.cpp:105] Iteration 19608, lr = 0.0001
I0405 15:42:07.151676 18799 solver.cpp:218] Iteration 19620 (2.22419 iter/s, 5.39523s/12 iters), loss = 4.4758
I0405 15:42:07.151719 18799 solver.cpp:237]     Train net output #0: loss = 4.4758 (* 1 = 4.4758 loss)
I0405 15:42:07.151726 18799 sgd_solver.cpp:105] Iteration 19620, lr = 0.0001
I0405 15:42:08.632985 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:42:12.810024 18799 solver.cpp:218] Iteration 19632 (2.12079 iter/s, 5.65826s/12 iters), loss = 4.27749
I0405 15:42:12.810118 18799 solver.cpp:237]     Train net output #0: loss = 4.27749 (* 1 = 4.27749 loss)
I0405 15:42:12.810124 18799 sgd_solver.cpp:105] Iteration 19632, lr = 0.0001
I0405 15:42:18.306804 18799 solver.cpp:218] Iteration 19644 (2.18315 iter/s, 5.49664s/12 iters), loss = 4.3757
I0405 15:42:18.306854 18799 solver.cpp:237]     Train net output #0: loss = 4.3757 (* 1 = 4.3757 loss)
I0405 15:42:18.306860 18799 sgd_solver.cpp:105] Iteration 19644, lr = 0.0001
I0405 15:42:23.853404 18799 solver.cpp:218] Iteration 19656 (2.16353 iter/s, 5.5465s/12 iters), loss = 4.33613
I0405 15:42:23.853461 18799 solver.cpp:237]     Train net output #0: loss = 4.33613 (* 1 = 4.33613 loss)
I0405 15:42:23.853469 18799 sgd_solver.cpp:105] Iteration 19656, lr = 0.0001
I0405 15:42:29.384368 18799 solver.cpp:218] Iteration 19668 (2.16964 iter/s, 5.53086s/12 iters), loss = 4.35214
I0405 15:42:29.384411 18799 solver.cpp:237]     Train net output #0: loss = 4.35214 (* 1 = 4.35214 loss)
I0405 15:42:29.384416 18799 sgd_solver.cpp:105] Iteration 19668, lr = 0.0001
I0405 15:42:34.660697 18799 solver.cpp:218] Iteration 19680 (2.27435 iter/s, 5.27624s/12 iters), loss = 4.22178
I0405 15:42:34.660755 18799 solver.cpp:237]     Train net output #0: loss = 4.22178 (* 1 = 4.22178 loss)
I0405 15:42:34.660764 18799 sgd_solver.cpp:105] Iteration 19680, lr = 0.0001
I0405 15:42:36.824295 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19686.caffemodel
I0405 15:42:39.895531 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19686.solverstate
I0405 15:42:42.206336 18799 solver.cpp:330] Iteration 19686, Testing net (#0)
I0405 15:42:42.206355 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:42:43.476869 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:42:46.745420 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0753676
I0405 15:42:46.745455 18799 solver.cpp:397]     Test net output #1: loss = 4.6377 (* 1 = 4.6377 loss)
I0405 15:42:48.827656 18799 solver.cpp:218] Iteration 19692 (0.84705 iter/s, 14.1668s/12 iters), loss = 4.29023
I0405 15:42:48.827710 18799 solver.cpp:237]     Train net output #0: loss = 4.29023 (* 1 = 4.29023 loss)
I0405 15:42:48.827718 18799 sgd_solver.cpp:105] Iteration 19692, lr = 0.0001
I0405 15:42:54.213712 18799 solver.cpp:218] Iteration 19704 (2.22801 iter/s, 5.38596s/12 iters), loss = 4.07701
I0405 15:42:54.213758 18799 solver.cpp:237]     Train net output #0: loss = 4.07701 (* 1 = 4.07701 loss)
I0405 15:42:54.213763 18799 sgd_solver.cpp:105] Iteration 19704, lr = 0.0001
I0405 15:42:59.378365 18799 solver.cpp:218] Iteration 19716 (2.32353 iter/s, 5.16456s/12 iters), loss = 4.42332
I0405 15:42:59.378412 18799 solver.cpp:237]     Train net output #0: loss = 4.42332 (* 1 = 4.42332 loss)
I0405 15:42:59.378418 18799 sgd_solver.cpp:105] Iteration 19716, lr = 0.0001
I0405 15:43:03.302251 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:43:04.975203 18799 solver.cpp:218] Iteration 19728 (2.1441 iter/s, 5.59675s/12 iters), loss = 4.3234
I0405 15:43:04.975244 18799 solver.cpp:237]     Train net output #0: loss = 4.3234 (* 1 = 4.3234 loss)
I0405 15:43:04.975248 18799 sgd_solver.cpp:105] Iteration 19728, lr = 0.0001
I0405 15:43:10.301858 18799 solver.cpp:218] Iteration 19740 (2.25286 iter/s, 5.32657s/12 iters), loss = 4.42555
I0405 15:43:10.301895 18799 solver.cpp:237]     Train net output #0: loss = 4.42555 (* 1 = 4.42555 loss)
I0405 15:43:10.301903 18799 sgd_solver.cpp:105] Iteration 19740, lr = 0.0001
I0405 15:43:15.520016 18799 solver.cpp:218] Iteration 19752 (2.2997 iter/s, 5.21808s/12 iters), loss = 4.37067
I0405 15:43:15.520108 18799 solver.cpp:237]     Train net output #0: loss = 4.37067 (* 1 = 4.37067 loss)
I0405 15:43:15.520115 18799 sgd_solver.cpp:105] Iteration 19752, lr = 0.0001
I0405 15:43:20.896049 18799 solver.cpp:218] Iteration 19764 (2.23218 iter/s, 5.3759s/12 iters), loss = 4.16724
I0405 15:43:20.896088 18799 solver.cpp:237]     Train net output #0: loss = 4.16724 (* 1 = 4.16724 loss)
I0405 15:43:20.896093 18799 sgd_solver.cpp:105] Iteration 19764, lr = 0.0001
I0405 15:43:26.363916 18799 solver.cpp:218] Iteration 19776 (2.19467 iter/s, 5.46778s/12 iters), loss = 4.26704
I0405 15:43:26.363962 18799 solver.cpp:237]     Train net output #0: loss = 4.26704 (* 1 = 4.26704 loss)
I0405 15:43:26.363970 18799 sgd_solver.cpp:105] Iteration 19776, lr = 0.0001
I0405 15:43:31.316138 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19788.caffemodel
I0405 15:43:34.350955 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19788.solverstate
I0405 15:43:36.650110 18799 solver.cpp:330] Iteration 19788, Testing net (#0)
I0405 15:43:36.650133 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:43:38.014992 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:43:41.183507 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0692402
I0405 15:43:41.183542 18799 solver.cpp:397]     Test net output #1: loss = 4.62975 (* 1 = 4.62975 loss)
I0405 15:43:41.325852 18799 solver.cpp:218] Iteration 19788 (0.802042 iter/s, 14.9618s/12 iters), loss = 4.1176
I0405 15:43:41.325937 18799 solver.cpp:237]     Train net output #0: loss = 4.1176 (* 1 = 4.1176 loss)
I0405 15:43:41.325946 18799 sgd_solver.cpp:105] Iteration 19788, lr = 0.0001
I0405 15:43:45.711688 18799 solver.cpp:218] Iteration 19800 (2.73615 iter/s, 4.38572s/12 iters), loss = 4.10303
I0405 15:43:45.712224 18799 solver.cpp:237]     Train net output #0: loss = 4.10303 (* 1 = 4.10303 loss)
I0405 15:43:45.712230 18799 sgd_solver.cpp:105] Iteration 19800, lr = 0.0001
I0405 15:43:51.178578 18799 solver.cpp:218] Iteration 19812 (2.19526 iter/s, 5.46632s/12 iters), loss = 4.21524
I0405 15:43:51.178629 18799 solver.cpp:237]     Train net output #0: loss = 4.21524 (* 1 = 4.21524 loss)
I0405 15:43:51.178637 18799 sgd_solver.cpp:105] Iteration 19812, lr = 0.0001
I0405 15:43:56.503444 18799 solver.cpp:218] Iteration 19824 (2.25362 iter/s, 5.32477s/12 iters), loss = 4.21799
I0405 15:43:56.503489 18799 solver.cpp:237]     Train net output #0: loss = 4.21799 (* 1 = 4.21799 loss)
I0405 15:43:56.503494 18799 sgd_solver.cpp:105] Iteration 19824, lr = 0.0001
I0405 15:43:57.215368 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:44:02.126962 18799 solver.cpp:218] Iteration 19836 (2.13393 iter/s, 5.62343s/12 iters), loss = 4.3424
I0405 15:44:02.127002 18799 solver.cpp:237]     Train net output #0: loss = 4.3424 (* 1 = 4.3424 loss)
I0405 15:44:02.127007 18799 sgd_solver.cpp:105] Iteration 19836, lr = 0.0001
I0405 15:44:07.331925 18799 solver.cpp:218] Iteration 19848 (2.30553 iter/s, 5.20488s/12 iters), loss = 4.29316
I0405 15:44:07.331974 18799 solver.cpp:237]     Train net output #0: loss = 4.29316 (* 1 = 4.29316 loss)
I0405 15:44:07.331981 18799 sgd_solver.cpp:105] Iteration 19848, lr = 0.0001
I0405 15:44:13.026013 18799 solver.cpp:218] Iteration 19860 (2.10748 iter/s, 5.69399s/12 iters), loss = 4.3577
I0405 15:44:13.026072 18799 solver.cpp:237]     Train net output #0: loss = 4.3577 (* 1 = 4.3577 loss)
I0405 15:44:13.026082 18799 sgd_solver.cpp:105] Iteration 19860, lr = 0.0001
I0405 15:44:18.477751 18799 solver.cpp:218] Iteration 19872 (2.20117 iter/s, 5.45164s/12 iters), loss = 4.37101
I0405 15:44:18.477856 18799 solver.cpp:237]     Train net output #0: loss = 4.37101 (* 1 = 4.37101 loss)
I0405 15:44:18.477865 18799 sgd_solver.cpp:105] Iteration 19872, lr = 0.0001
I0405 15:44:23.643070 18799 solver.cpp:218] Iteration 19884 (2.32325 iter/s, 5.16517s/12 iters), loss = 4.33684
I0405 15:44:23.643110 18799 solver.cpp:237]     Train net output #0: loss = 4.33684 (* 1 = 4.33684 loss)
I0405 15:44:23.643115 18799 sgd_solver.cpp:105] Iteration 19884, lr = 0.0001
I0405 15:44:25.898404 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19890.caffemodel
I0405 15:44:28.927695 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19890.solverstate
I0405 15:44:31.232218 18799 solver.cpp:330] Iteration 19890, Testing net (#0)
I0405 15:44:31.232241 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:44:32.490123 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:44:35.740765 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0710784
I0405 15:44:35.740799 18799 solver.cpp:397]     Test net output #1: loss = 4.62284 (* 1 = 4.62284 loss)
I0405 15:44:37.686967 18799 solver.cpp:218] Iteration 19896 (0.854471 iter/s, 14.0438s/12 iters), loss = 3.98795
I0405 15:44:37.687021 18799 solver.cpp:237]     Train net output #0: loss = 3.98795 (* 1 = 3.98795 loss)
I0405 15:44:37.687031 18799 sgd_solver.cpp:105] Iteration 19896, lr = 0.0001
I0405 15:44:43.261937 18799 solver.cpp:218] Iteration 19908 (2.15251 iter/s, 5.57487s/12 iters), loss = 4.20653
I0405 15:44:43.261976 18799 solver.cpp:237]     Train net output #0: loss = 4.20653 (* 1 = 4.20653 loss)
I0405 15:44:43.261982 18799 sgd_solver.cpp:105] Iteration 19908, lr = 0.0001
I0405 15:44:48.831460 18799 solver.cpp:218] Iteration 19920 (2.15462 iter/s, 5.56944s/12 iters), loss = 4.2938
I0405 15:44:48.831609 18799 solver.cpp:237]     Train net output #0: loss = 4.2938 (* 1 = 4.2938 loss)
I0405 15:44:48.831619 18799 sgd_solver.cpp:105] Iteration 19920, lr = 0.0001
I0405 15:44:51.700680 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:44:54.233258 18799 solver.cpp:218] Iteration 19932 (2.22156 iter/s, 5.40161s/12 iters), loss = 4.33835
I0405 15:44:54.233302 18799 solver.cpp:237]     Train net output #0: loss = 4.33835 (* 1 = 4.33835 loss)
I0405 15:44:54.233307 18799 sgd_solver.cpp:105] Iteration 19932, lr = 0.0001
I0405 15:44:59.594908 18799 solver.cpp:218] Iteration 19944 (2.23815 iter/s, 5.36156s/12 iters), loss = 4.3271
I0405 15:44:59.594959 18799 solver.cpp:237]     Train net output #0: loss = 4.3271 (* 1 = 4.3271 loss)
I0405 15:44:59.594967 18799 sgd_solver.cpp:105] Iteration 19944, lr = 0.0001
I0405 15:45:05.168746 18799 solver.cpp:218] Iteration 19956 (2.15295 iter/s, 5.57374s/12 iters), loss = 4.40604
I0405 15:45:05.168784 18799 solver.cpp:237]     Train net output #0: loss = 4.40604 (* 1 = 4.40604 loss)
I0405 15:45:05.168789 18799 sgd_solver.cpp:105] Iteration 19956, lr = 0.0001
I0405 15:45:10.435832 18799 solver.cpp:218] Iteration 19968 (2.27833 iter/s, 5.267s/12 iters), loss = 4.28582
I0405 15:45:10.435871 18799 solver.cpp:237]     Train net output #0: loss = 4.28582 (* 1 = 4.28582 loss)
I0405 15:45:10.435878 18799 sgd_solver.cpp:105] Iteration 19968, lr = 0.0001
I0405 15:45:15.897156 18799 solver.cpp:218] Iteration 19980 (2.1973 iter/s, 5.46124s/12 iters), loss = 4.35582
I0405 15:45:15.897208 18799 solver.cpp:237]     Train net output #0: loss = 4.35582 (* 1 = 4.35582 loss)
I0405 15:45:15.897215 18799 sgd_solver.cpp:105] Iteration 19980, lr = 0.0001
I0405 15:45:20.831198 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19992.caffemodel
I0405 15:45:23.873814 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19992.solverstate
I0405 15:45:26.244149 18799 solver.cpp:330] Iteration 19992, Testing net (#0)
I0405 15:45:26.244172 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:45:27.445003 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:45:30.739660 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0680147
I0405 15:45:30.739687 18799 solver.cpp:397]     Test net output #1: loss = 4.61785 (* 1 = 4.61785 loss)
I0405 15:45:30.881381 18799 solver.cpp:218] Iteration 19992 (0.80085 iter/s, 14.9841s/12 iters), loss = 4.4508
I0405 15:45:30.881426 18799 solver.cpp:237]     Train net output #0: loss = 4.4508 (* 1 = 4.4508 loss)
I0405 15:45:30.881431 18799 sgd_solver.cpp:105] Iteration 19992, lr = 0.0001
I0405 15:45:35.325475 18799 solver.cpp:218] Iteration 20004 (2.70027 iter/s, 4.44401s/12 iters), loss = 4.33289
I0405 15:45:35.325527 18799 solver.cpp:237]     Train net output #0: loss = 4.33289 (* 1 = 4.33289 loss)
I0405 15:45:35.325536 18799 sgd_solver.cpp:105] Iteration 20004, lr = 0.0001
I0405 15:45:40.687235 18799 solver.cpp:218] Iteration 20016 (2.23811 iter/s, 5.36166s/12 iters), loss = 4.20004
I0405 15:45:40.687274 18799 solver.cpp:237]     Train net output #0: loss = 4.20004 (* 1 = 4.20004 loss)
I0405 15:45:40.687280 18799 sgd_solver.cpp:105] Iteration 20016, lr = 0.0001
I0405 15:45:46.259230 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:45:46.425719 18799 solver.cpp:218] Iteration 20028 (2.09118 iter/s, 5.7384s/12 iters), loss = 4.26688
I0405 15:45:46.425755 18799 solver.cpp:237]     Train net output #0: loss = 4.26688 (* 1 = 4.26688 loss)
I0405 15:45:46.425761 18799 sgd_solver.cpp:105] Iteration 20028, lr = 0.0001
I0405 15:45:52.051782 18799 solver.cpp:218] Iteration 20040 (2.13296 iter/s, 5.62598s/12 iters), loss = 4.34413
I0405 15:45:52.051930 18799 solver.cpp:237]     Train net output #0: loss = 4.34413 (* 1 = 4.34413 loss)
I0405 15:45:52.051939 18799 sgd_solver.cpp:105] Iteration 20040, lr = 0.0001
I0405 15:45:57.575886 18799 solver.cpp:218] Iteration 20052 (2.17237 iter/s, 5.52391s/12 iters), loss = 4.18371
I0405 15:45:57.575937 18799 solver.cpp:237]     Train net output #0: loss = 4.18371 (* 1 = 4.18371 loss)
I0405 15:45:57.575944 18799 sgd_solver.cpp:105] Iteration 20052, lr = 0.0001
I0405 15:46:02.945055 18799 solver.cpp:218] Iteration 20064 (2.23502 iter/s, 5.36907s/12 iters), loss = 4.25276
I0405 15:46:02.945109 18799 solver.cpp:237]     Train net output #0: loss = 4.25276 (* 1 = 4.25276 loss)
I0405 15:46:02.945118 18799 sgd_solver.cpp:105] Iteration 20064, lr = 0.0001
I0405 15:46:08.368866 18799 solver.cpp:218] Iteration 20076 (2.21251 iter/s, 5.42371s/12 iters), loss = 4.18026
I0405 15:46:08.368937 18799 solver.cpp:237]     Train net output #0: loss = 4.18026 (* 1 = 4.18026 loss)
I0405 15:46:08.368947 18799 sgd_solver.cpp:105] Iteration 20076, lr = 0.0001
I0405 15:46:13.990356 18799 solver.cpp:218] Iteration 20088 (2.13471 iter/s, 5.62138s/12 iters), loss = 4.38448
I0405 15:46:13.990396 18799 solver.cpp:237]     Train net output #0: loss = 4.38448 (* 1 = 4.38448 loss)
I0405 15:46:13.990401 18799 sgd_solver.cpp:105] Iteration 20088, lr = 0.0001
I0405 15:46:16.374590 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20094.caffemodel
I0405 15:46:19.487617 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20094.solverstate
I0405 15:46:21.787137 18799 solver.cpp:330] Iteration 20094, Testing net (#0)
I0405 15:46:21.787154 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:46:22.900815 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:46:25.865468 18799 blocking_queue.cpp:49] Waiting for data
I0405 15:46:26.404419 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0692402
I0405 15:46:26.404453 18799 solver.cpp:397]     Test net output #1: loss = 4.6165 (* 1 = 4.6165 loss)
I0405 15:46:28.227883 18799 solver.cpp:218] Iteration 20100 (0.842851 iter/s, 14.2374s/12 iters), loss = 4.23775
I0405 15:46:28.227942 18799 solver.cpp:237]     Train net output #0: loss = 4.23775 (* 1 = 4.23775 loss)
I0405 15:46:28.227949 18799 sgd_solver.cpp:105] Iteration 20100, lr = 0.0001
I0405 15:46:33.680573 18799 solver.cpp:218] Iteration 20112 (2.20079 iter/s, 5.45259s/12 iters), loss = 4.17158
I0405 15:46:33.680611 18799 solver.cpp:237]     Train net output #0: loss = 4.17158 (* 1 = 4.17158 loss)
I0405 15:46:33.680617 18799 sgd_solver.cpp:105] Iteration 20112, lr = 0.0001
I0405 15:46:38.695188 18799 solver.cpp:218] Iteration 20124 (2.39305 iter/s, 5.01453s/12 iters), loss = 4.212
I0405 15:46:38.695235 18799 solver.cpp:237]     Train net output #0: loss = 4.212 (* 1 = 4.212 loss)
I0405 15:46:38.695241 18799 sgd_solver.cpp:105] Iteration 20124, lr = 0.0001
I0405 15:46:41.008973 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:46:44.061435 18799 solver.cpp:218] Iteration 20136 (2.23624 iter/s, 5.36616s/12 iters), loss = 4.23458
I0405 15:46:44.061475 18799 solver.cpp:237]     Train net output #0: loss = 4.23458 (* 1 = 4.23458 loss)
I0405 15:46:44.061480 18799 sgd_solver.cpp:105] Iteration 20136, lr = 0.0001
I0405 15:46:49.511615 18799 solver.cpp:218] Iteration 20148 (2.2018 iter/s, 5.4501s/12 iters), loss = 4.42534
I0405 15:46:49.511656 18799 solver.cpp:237]     Train net output #0: loss = 4.42534 (* 1 = 4.42534 loss)
I0405 15:46:49.511662 18799 sgd_solver.cpp:105] Iteration 20148, lr = 0.0001
I0405 15:46:55.004958 18799 solver.cpp:218] Iteration 20160 (2.1845 iter/s, 5.49326s/12 iters), loss = 4.36309
I0405 15:46:55.005076 18799 solver.cpp:237]     Train net output #0: loss = 4.36309 (* 1 = 4.36309 loss)
I0405 15:46:55.005085 18799 sgd_solver.cpp:105] Iteration 20160, lr = 0.0001
I0405 15:47:00.380367 18799 solver.cpp:218] Iteration 20172 (2.23245 iter/s, 5.37525s/12 iters), loss = 4.29156
I0405 15:47:00.380406 18799 solver.cpp:237]     Train net output #0: loss = 4.29156 (* 1 = 4.29156 loss)
I0405 15:47:00.380411 18799 sgd_solver.cpp:105] Iteration 20172, lr = 0.0001
I0405 15:47:05.961172 18799 solver.cpp:218] Iteration 20184 (2.15026 iter/s, 5.58072s/12 iters), loss = 4.29959
I0405 15:47:05.961216 18799 solver.cpp:237]     Train net output #0: loss = 4.29959 (* 1 = 4.29959 loss)
I0405 15:47:05.961222 18799 sgd_solver.cpp:105] Iteration 20184, lr = 0.0001
I0405 15:47:10.836825 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20196.caffemodel
I0405 15:47:13.893923 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20196.solverstate
I0405 15:47:16.184967 18799 solver.cpp:330] Iteration 20196, Testing net (#0)
I0405 15:47:16.184988 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:47:17.298288 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:47:20.702626 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0747549
I0405 15:47:20.702666 18799 solver.cpp:397]     Test net output #1: loss = 4.61003 (* 1 = 4.61003 loss)
I0405 15:47:20.840936 18799 solver.cpp:218] Iteration 20196 (0.806472 iter/s, 14.8796s/12 iters), loss = 4.43536
I0405 15:47:20.840988 18799 solver.cpp:237]     Train net output #0: loss = 4.43536 (* 1 = 4.43536 loss)
I0405 15:47:20.840996 18799 sgd_solver.cpp:105] Iteration 20196, lr = 0.0001
I0405 15:47:25.261227 18799 solver.cpp:218] Iteration 20208 (2.71481 iter/s, 4.4202s/12 iters), loss = 4.52868
I0405 15:47:25.261358 18799 solver.cpp:237]     Train net output #0: loss = 4.52868 (* 1 = 4.52868 loss)
I0405 15:47:25.261364 18799 sgd_solver.cpp:105] Iteration 20208, lr = 0.0001
I0405 15:47:30.743772 18799 solver.cpp:218] Iteration 20220 (2.18884 iter/s, 5.48237s/12 iters), loss = 4.22903
I0405 15:47:30.743829 18799 solver.cpp:237]     Train net output #0: loss = 4.22903 (* 1 = 4.22903 loss)
I0405 15:47:30.743836 18799 sgd_solver.cpp:105] Iteration 20220, lr = 0.0001
I0405 15:47:35.365090 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:47:36.214495 18799 solver.cpp:218] Iteration 20232 (2.19353 iter/s, 5.47062s/12 iters), loss = 4.26945
I0405 15:47:36.214540 18799 solver.cpp:237]     Train net output #0: loss = 4.26945 (* 1 = 4.26945 loss)
I0405 15:47:36.214545 18799 sgd_solver.cpp:105] Iteration 20232, lr = 0.0001
I0405 15:47:41.470458 18799 solver.cpp:218] Iteration 20244 (2.28316 iter/s, 5.25587s/12 iters), loss = 4.40872
I0405 15:47:41.470502 18799 solver.cpp:237]     Train net output #0: loss = 4.40872 (* 1 = 4.40872 loss)
I0405 15:47:41.470510 18799 sgd_solver.cpp:105] Iteration 20244, lr = 0.0001
I0405 15:47:46.827668 18799 solver.cpp:218] Iteration 20256 (2.24001 iter/s, 5.35712s/12 iters), loss = 4.26015
I0405 15:47:46.827719 18799 solver.cpp:237]     Train net output #0: loss = 4.26015 (* 1 = 4.26015 loss)
I0405 15:47:46.827728 18799 sgd_solver.cpp:105] Iteration 20256, lr = 0.0001
I0405 15:47:52.296350 18799 solver.cpp:218] Iteration 20268 (2.19435 iter/s, 5.46859s/12 iters), loss = 4.24624
I0405 15:47:52.296402 18799 solver.cpp:237]     Train net output #0: loss = 4.24624 (* 1 = 4.24624 loss)
I0405 15:47:52.296411 18799 sgd_solver.cpp:105] Iteration 20268, lr = 0.0001
I0405 15:47:57.773103 18799 solver.cpp:218] Iteration 20280 (2.19112 iter/s, 5.47666s/12 iters), loss = 4.25315
I0405 15:47:57.773250 18799 solver.cpp:237]     Train net output #0: loss = 4.25315 (* 1 = 4.25315 loss)
I0405 15:47:57.773262 18799 sgd_solver.cpp:105] Iteration 20280, lr = 0.0001
I0405 15:48:03.141783 18799 solver.cpp:218] Iteration 20292 (2.23526 iter/s, 5.36851s/12 iters), loss = 4.38411
I0405 15:48:03.141834 18799 solver.cpp:237]     Train net output #0: loss = 4.38411 (* 1 = 4.38411 loss)
I0405 15:48:03.141841 18799 sgd_solver.cpp:105] Iteration 20292, lr = 0.0001
I0405 15:48:05.331699 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20298.caffemodel
I0405 15:48:08.426234 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20298.solverstate
I0405 15:48:10.906873 18799 solver.cpp:330] Iteration 20298, Testing net (#0)
I0405 15:48:10.906896 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:48:12.032754 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:48:15.514571 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0716912
I0405 15:48:15.514607 18799 solver.cpp:397]     Test net output #1: loss = 4.60806 (* 1 = 4.60806 loss)
I0405 15:48:17.529443 18799 solver.cpp:218] Iteration 20304 (0.834056 iter/s, 14.3875s/12 iters), loss = 4.22623
I0405 15:48:17.529479 18799 solver.cpp:237]     Train net output #0: loss = 4.22623 (* 1 = 4.22623 loss)
I0405 15:48:17.529484 18799 sgd_solver.cpp:105] Iteration 20304, lr = 0.0001
I0405 15:48:23.040932 18799 solver.cpp:218] Iteration 20316 (2.1773 iter/s, 5.51141s/12 iters), loss = 4.46145
I0405 15:48:23.040973 18799 solver.cpp:237]     Train net output #0: loss = 4.46145 (* 1 = 4.46145 loss)
I0405 15:48:23.040978 18799 sgd_solver.cpp:105] Iteration 20316, lr = 0.0001
I0405 15:48:28.410365 18799 solver.cpp:218] Iteration 20328 (2.23491 iter/s, 5.36934s/12 iters), loss = 4.39662
I0405 15:48:28.410523 18799 solver.cpp:237]     Train net output #0: loss = 4.39662 (* 1 = 4.39662 loss)
I0405 15:48:28.410532 18799 sgd_solver.cpp:105] Iteration 20328, lr = 0.0001
I0405 15:48:29.857398 18818 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:48:33.864594 18799 solver.cpp:218] Iteration 20340 (2.20021 iter/s, 5.45403s/12 iters), loss = 4.15864
I0405 15:48:33.864634 18799 solver.cpp:237]     Train net output #0: loss = 4.15864 (* 1 = 4.15864 loss)
I0405 15:48:33.864639 18799 sgd_solver.cpp:105] Iteration 20340, lr = 0.0001
I0405 15:48:39.269899 18799 solver.cpp:218] Iteration 20352 (2.22008 iter/s, 5.40522s/12 iters), loss = 4.25249
I0405 15:48:39.269942 18799 solver.cpp:237]     Train net output #0: loss = 4.25249 (* 1 = 4.25249 loss)
I0405 15:48:39.269948 18799 sgd_solver.cpp:105] Iteration 20352, lr = 0.0001
I0405 15:48:44.531469 18799 solver.cpp:218] Iteration 20364 (2.28073 iter/s, 5.26148s/12 iters), loss = 4.20336
I0405 15:48:44.531509 18799 solver.cpp:237]     Train net output #0: loss = 4.20336 (* 1 = 4.20336 loss)
I0405 15:48:44.531515 18799 sgd_solver.cpp:105] Iteration 20364, lr = 0.0001
I0405 15:48:49.967113 18799 solver.cpp:218] Iteration 20376 (2.20769 iter/s, 5.43555s/12 iters), loss = 4.22424
I0405 15:48:49.967164 18799 solver.cpp:237]     Train net output #0: loss = 4.22424 (* 1 = 4.22424 loss)
I0405 15:48:49.967170 18799 sgd_solver.cpp:105] Iteration 20376, lr = 0.0001
I0405 15:48:55.629609 18799 solver.cpp:218] Iteration 20388 (2.11924 iter/s, 5.6624s/12 iters), loss = 4.21179
I0405 15:48:55.629652 18799 solver.cpp:237]     Train net output #0: loss = 4.21179 (* 1 = 4.21179 loss)
I0405 15:48:55.629657 18799 sgd_solver.cpp:105] Iteration 20388, lr = 0.0001
I0405 15:49:00.563836 18799 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20400.caffemodel
I0405 15:49:03.647567 18799 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20400.solverstate
I0405 15:49:05.994256 18799 solver.cpp:310] Iteration 20400, loss = 4.12796
I0405 15:49:05.994277 18799 solver.cpp:330] Iteration 20400, Testing net (#0)
I0405 15:49:05.994282 18799 net.cpp:676] Ignoring source layer train-data
I0405 15:49:07.105829 18850 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:49:10.650645 18799 solver.cpp:397]     Test net output #0: accuracy = 0.0741422
I0405 15:49:10.650669 18799 solver.cpp:397]     Test net output #1: loss = 4.60048 (* 1 = 4.60048 loss)
I0405 15:49:10.650673 18799 solver.cpp:315] Optimization Done.
I0405 15:49:10.650676 18799 caffe.cpp:259] Optimization Done.