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loss err when enable ComputeLibrary on ACLCAFFE #13

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haolongzhangm opened this issue Oct 10, 2017 · 2 comments
Open

loss err when enable ComputeLibrary on ACLCAFFE #13

haolongzhangm opened this issue Oct 10, 2017 · 2 comments

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@haolongzhangm
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Issue summary

loss err when enable ComputeLibrary on ACLCAFFE

Steps to reproduce

1:build https://github.com/ARM-software/ComputeLibrary by command:
scons Werror=1 -j8 debug=0 asserts=1 neon=1 opencl=1 embed_kernels=1 os=android arch=arm64-v8a
2:build ACLCAFFE to android platform by enable env:
export ACL_DIR=${ANDROID_LIB_ROOT}/ComputeLibrary
-DCPU_ONLY=ON
-DUSE_PROFILING=ON
-DUSE_ACL=ON \

3: run caffe on android MTK/QCOM arm platform by test mnist
4: use the same model and protobuf,

Err result loss :
loss = 2.30261 (* 1 = 2.30261 loss)

ps : at the same code , only set -DUSE_ACL=OFF \

the loss will be right:
loss = 0.0486609 (* 1 = 0.0486609 loss)

Your system configuration

Operating system: ubuntu 16.04
Compiler: aarch64-linux-android-
CUDA version (if applicable):
CUDNN version (if applicable):
BLAS:open
Python or MATLAB version (for pycaffe and matcaffe respectively):
@haolongzhangm
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Author

mtk_disable_acl.log ============================

WARNING: Logging before InitGoogleLogging() is written to STDERR
I0112 18:18:59.234746 4927 caffe.cpp:288] Use CPU.
I0112 18:18:59.248070 4927 net.cpp:296] The NetState phase (1) differed from the phase (0) specified by a rule in layer mnist
I0112 18:18:59.248433 4927 net.cpp:53] Initializing net from parameters:
name: "LeNet"
state {
phase: TEST
level: 0
stage: ""
}
layer {
name: "mnist"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
scale: 0.00390625
}
data_param {
source: "/data/caffe_eg/mnist/mnist_test_lmdb"
batch_size: 100
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
convolution_param {
num_output: 20
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
convolution_param {
num_output: 50
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "ip1"
type: "InnerProduct"
bottom: "pool2"
top: "ip1"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
inner_product_param {
num_output: 500
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "ip1"
top: "ip1"
}
layer {
name: "ip2"
type: "InnerProduct"
bottom: "ip1"
top: "ip2"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
inner_product_param {
num_output: 10
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "ip2"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip2"
bottom: "label"
top: "loss"
}
I0112 18:18:59.250512 4927 layer_factory.hpp:77] Creating layer mnist
I0112 18:18:59.251114 4927 db_lmdb.cpp:35] Opened lmdb /data/caffe_eg/mnist/mnist_test_lmdb
I0112 18:18:59.251270 4927 net.cpp:86] Creating Layer mnist
I0112 18:18:59.251361 4927 net.cpp:382] mnist -> data
I0112 18:18:59.251541 4927 net.cpp:382] mnist -> label
I0112 18:18:59.251770 4927 data_layer.cpp:45] output data size: 100,1,28,28
I0112 18:18:59.253125 4927 base_data_layer.cpp:72] Initializing prefetch
I0112 18:18:59.254364 4927 base_data_layer.cpp:75] Prefetch initialized.
I0112 18:18:59.254442 4927 net.cpp:124] Setting up mnist
I0112 18:18:59.254505 4927 net.cpp:131] Top shape: 100 1 28 28 (78400)
I0112 18:18:59.254591 4927 net.cpp:131] Top shape: 100 (100)
I0112 18:18:59.254644 4927 net.cpp:139] Memory required for data: 314000
I0112 18:18:59.254716 4927 layer_factory.hpp:77] Creating layer label_mnist_1_split
I0112 18:18:59.254834 4927 net.cpp:86] Creating Layer label_mnist_1_split
I0112 18:18:59.254896 4927 net.cpp:408] label_mnist_1_split <- label
I0112 18:18:59.254997 4927 net.cpp:382] label_mnist_1_split -> label_mnist_1_split_0
I0112 18:18:59.255122 4927 net.cpp:382] label_mnist_1_split -> label_mnist_1_split_1
I0112 18:18:59.255219 4927 net.cpp:124] Setting up label_mnist_1_split
I0112 18:18:59.255280 4927 net.cpp:131] Top shape: 100 (100)
I0112 18:18:59.255338 4927 net.cpp:131] Top shape: 100 (100)
I0112 18:18:59.255391 4927 net.cpp:139] Memory required for data: 314800
I0112 18:18:59.255445 4927 layer_factory.hpp:77] Creating layer conv1
I0112 18:18:59.255570 4927 net.cpp:86] Creating Layer conv1
I0112 18:18:59.255625 4927 net.cpp:408] conv1 <- data
I0112 18:18:59.255730 4927 net.cpp:382] conv1 -> conv1
I0112 18:18:59.256273 4927 net.cpp:124] Setting up conv1
I0112 18:18:59.256342 4927 net.cpp:131] Top shape: 100 20 24 24 (1152000)
I0112 18:18:59.256402 4927 net.cpp:139] Memory required for data: 4922800
I0112 18:18:59.256543 4927 layer_factory.hpp:77] Creating layer pool1
I0112 18:18:59.256656 4927 net.cpp:86] Creating Layer pool1
I0112 18:18:59.256715 4927 net.cpp:408] pool1 <- conv1
I0112 18:18:59.256790 4927 net.cpp:382] pool1 -> pool1
I0112 18:18:59.256947 4927 net.cpp:124] Setting up pool1
I0112 18:18:59.257004 4927 net.cpp:131] Top shape: 100 20 12 12 (288000)
I0112 18:18:59.257063 4927 net.cpp:139] Memory required for data: 6074800
I0112 18:18:59.257137 4927 layer_factory.hpp:77] Creating layer conv2
I0112 18:18:59.257249 4927 net.cpp:86] Creating Layer conv2
I0112 18:18:59.257304 4927 net.cpp:408] conv2 <- pool1
I0112 18:18:59.257387 4927 net.cpp:382] conv2 -> conv2
I0112 18:18:59.265692 4928 data_layer.cpp:128] Prefetch batch: 10 ms.
I0112 18:18:59.266127 4928 data_layer.cpp:129] Read time: 0.97 ms.
I0112 18:18:59.266190 4928 data_layer.cpp:130] Transform time: 8.74 ms.
I0112 18:18:59.267087 4927 net.cpp:124] Setting up conv2
I0112 18:18:59.267189 4927 net.cpp:131] Top shape: 100 50 8 8 (320000)
I0112 18:18:59.267253 4927 net.cpp:139] Memory required for data: 7354800
I0112 18:18:59.267407 4927 layer_factory.hpp:77] Creating layer pool2
I0112 18:18:59.267520 4927 net.cpp:86] Creating Layer pool2
I0112 18:18:59.267583 4927 net.cpp:408] pool2 <- conv2
I0112 18:18:59.267673 4927 net.cpp:382] pool2 -> pool2
I0112 18:18:59.267827 4927 net.cpp:124] Setting up pool2
I0112 18:18:59.267879 4927 net.cpp:131] Top shape: 100 50 4 4 (80000)
I0112 18:18:59.267937 4927 net.cpp:139] Memory required for data: 7674800
I0112 18:18:59.267990 4927 layer_factory.hpp:77] Creating layer ip1
I0112 18:18:59.268086 4927 net.cpp:86] Creating Layer ip1
I0112 18:18:59.268161 4927 net.cpp:408] ip1 <- pool2
I0112 18:18:59.268246 4927 net.cpp:382] ip1 -> ip1
I0112 18:18:59.277564 4928 data_layer.cpp:128] Prefetch batch: 11 ms.
I0112 18:18:59.277770 4928 data_layer.cpp:129] Read time: 1.834 ms.
I0112 18:18:59.277832 4928 data_layer.cpp:130] Transform time: 8.357 ms.
I0112 18:18:59.287046 4928 data_layer.cpp:128] Prefetch batch: 9 ms.
I0112 18:18:59.287221 4928 data_layer.cpp:129] Read time: 0.851 ms.
I0112 18:18:59.287283 4928 data_layer.cpp:130] Transform time: 7.232 ms.
I0112 18:18:59.296427 4928 data_layer.cpp:128] Prefetch batch: 9 ms.
I0112 18:18:59.296596 4928 data_layer.cpp:129] Read time: 0.844 ms.
I0112 18:18:59.296668 4928 data_layer.cpp:130] Transform time: 7.216 ms.
I0112 18:18:59.394999 4927 net.cpp:124] Setting up ip1
I0112 18:18:59.395175 4927 net.cpp:131] Top shape: 100 500 (50000)
I0112 18:18:59.395232 4927 net.cpp:139] Memory required for data: 7874800
I0112 18:18:59.395395 4927 layer_factory.hpp:77] Creating layer relu1
I0112 18:18:59.395499 4927 net.cpp:86] Creating Layer relu1
I0112 18:18:59.395555 4927 net.cpp:408] relu1 <- ip1
I0112 18:18:59.395621 4927 net.cpp:369] relu1 -> ip1 (in-place)
I0112 18:18:59.395695 4927 net.cpp:124] Setting up relu1
I0112 18:18:59.395731 4927 net.cpp:131] Top shape: 100 500 (50000)
I0112 18:18:59.395773 4927 net.cpp:139] Memory required for data: 8074800
I0112 18:18:59.395812 4927 layer_factory.hpp:77] Creating layer ip2
I0112 18:18:59.395889 4927 net.cpp:86] Creating Layer ip2
I0112 18:18:59.395927 4927 net.cpp:408] ip2 <- ip1
I0112 18:18:59.395985 4927 net.cpp:382] ip2 -> ip2
I0112 18:18:59.397521 4927 net.cpp:124] Setting up ip2
I0112 18:18:59.397605 4927 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:18:59.397651 4927 net.cpp:139] Memory required for data: 8078800
I0112 18:18:59.397737 4927 layer_factory.hpp:77] Creating layer ip2_ip2_0_split
I0112 18:18:59.397806 4927 net.cpp:86] Creating Layer ip2_ip2_0_split
I0112 18:18:59.397848 4927 net.cpp:408] ip2_ip2_0_split <- ip2
I0112 18:18:59.397905 4927 net.cpp:382] ip2_ip2_0_split -> ip2_ip2_0_split_0
I0112 18:18:59.397965 4927 net.cpp:382] ip2_ip2_0_split -> ip2_ip2_0_split_1
I0112 18:18:59.398030 4927 net.cpp:124] Setting up ip2_ip2_0_split
I0112 18:18:59.398069 4927 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:18:59.398114 4927 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:18:59.398154 4927 net.cpp:139] Memory required for data: 8086800
I0112 18:18:59.398195 4927 layer_factory.hpp:77] Creating layer accuracy
I0112 18:18:59.398280 4927 net.cpp:86] Creating Layer accuracy
I0112 18:18:59.398319 4927 net.cpp:408] accuracy <- ip2_ip2_0_split_0
I0112 18:18:59.398378 4927 net.cpp:408] accuracy <- label_mnist_1_split_0
I0112 18:18:59.398430 4927 net.cpp:382] accuracy -> accuracy
I0112 18:18:59.398494 4927 net.cpp:124] Setting up accuracy
I0112 18:18:59.398531 4927 net.cpp:131] Top shape: (1)
I0112 18:18:59.398570 4927 net.cpp:139] Memory required for data: 8086804
I0112 18:18:59.398607 4927 layer_factory.hpp:77] Creating layer loss
I0112 18:18:59.398658 4927 net.cpp:86] Creating Layer loss
I0112 18:18:59.398697 4927 net.cpp:408] loss <- ip2_ip2_0_split_1
I0112 18:18:59.398746 4927 net.cpp:408] loss <- label_mnist_1_split_1
I0112 18:18:59.398797 4927 net.cpp:382] loss -> loss
I0112 18:18:59.398874 4927 layer_factory.hpp:77] Creating layer loss
I0112 18:18:59.399009 4927 net.cpp:124] Setting up loss
I0112 18:18:59.399049 4927 net.cpp:131] Top shape: (1)
I0112 18:18:59.399091 4927 net.cpp:134] with loss weight 1
I0112 18:18:59.399163 4927 net.cpp:139] Memory required for data: 8086808
I0112 18:18:59.399206 4927 net.cpp:200] loss needs backward computation.
I0112 18:18:59.399247 4927 net.cpp:202] accuracy does not need backward computation.
I0112 18:18:59.399293 4927 net.cpp:200] ip2_ip2_0_split needs backward computation.
I0112 18:18:59.399335 4927 net.cpp:200] ip2 needs backward computation.
I0112 18:18:59.399373 4927 net.cpp:200] relu1 needs backward computation.
I0112 18:18:59.399410 4927 net.cpp:200] ip1 needs backward computation.
I0112 18:18:59.399449 4927 net.cpp:200] pool2 needs backward computation.
I0112 18:18:59.399488 4927 net.cpp:200] conv2 needs backward computation.
I0112 18:18:59.399616 4927 net.cpp:200] pool1 needs backward computation.
I0112 18:18:59.399658 4927 net.cpp:200] conv1 needs backward computation.
I0112 18:18:59.399703 4927 net.cpp:202] label_mnist_1_split does not need backward computation.
I0112 18:18:59.399745 4927 net.cpp:202] mnist does not need backward computation.
I0112 18:18:59.399791 4927 net.cpp:244] This network produces output accuracy
I0112 18:18:59.399834 4927 net.cpp:244] This network produces output loss
I0112 18:18:59.399955 4927 net.cpp:257] Network initialization done.
I0112 18:18:59.444804 4927 net.cpp:749] Copying source layer mnist
I0112 18:18:59.445011 4927 net.cpp:749] Copying source layer conv1
I0112 18:18:59.445123 4927 net.cpp:749] Copying source layer pool1
I0112 18:18:59.445164 4927 net.cpp:749] Copying source layer conv2
I0112 18:18:59.446504 4927 net.cpp:749] Copying source layer pool2
I0112 18:18:59.446604 4927 net.cpp:749] Copying source layer ip1
I0112 18:18:59.465939 4927 net.cpp:749] Copying source layer relu1
I0112 18:18:59.466148 4927 net.cpp:749] Copying source layer ip2
I0112 18:18:59.466502 4927 net.cpp:749] Copying source layer loss
I0112 18:18:59.469476 4927 caffe.cpp:294] Running for 30 iterations.
I0112 18:18:59.975335 4927 caffe.cpp:317] Batch 0, accuracy = 1
I0112 18:18:59.975615 4927 caffe.cpp:317] Batch 0, loss = 0.0135883
I0112 18:18:59.982455 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:18:59.982668 4928 data_layer.cpp:129] Read time: 0.68 ms.
I0112 18:18:59.982718 4928 data_layer.cpp:130] Transform time: 5.255 ms.
I0112 18:19:00.474658 4927 caffe.cpp:317] Batch 1, accuracy = 0.99
I0112 18:19:00.474936 4927 caffe.cpp:317] Batch 1, loss = 0.0130389
I0112 18:19:00.481828 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:00.482044 4928 data_layer.cpp:129] Read time: 0.739 ms.
I0112 18:19:00.482094 4928 data_layer.cpp:130] Transform time: 5.229 ms.
I0112 18:19:00.973535 4927 caffe.cpp:317] Batch 2, accuracy = 0.99
I0112 18:19:00.973796 4927 caffe.cpp:317] Batch 2, loss = 0.0159064
I0112 18:19:00.980622 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:00.980806 4928 data_layer.cpp:129] Read time: 0.641 ms.
I0112 18:19:00.980851 4928 data_layer.cpp:130] Transform time: 5.224 ms.
I0112 18:19:01.472671 4927 caffe.cpp:317] Batch 3, accuracy = 0.99
I0112 18:19:01.472934 4927 caffe.cpp:317] Batch 3, loss = 0.025398
I0112 18:19:01.479765 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:01.479969 4928 data_layer.cpp:129] Read time: 0.642 ms.
I0112 18:19:01.480016 4928 data_layer.cpp:130] Transform time: 5.286 ms.
I0112 18:19:01.971870 4927 caffe.cpp:317] Batch 4, accuracy = 0.99
I0112 18:19:01.972134 4927 caffe.cpp:317] Batch 4, loss = 0.0665555
I0112 18:19:01.978899 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:01.979137 4928 data_layer.cpp:129] Read time: 0.674 ms.
I0112 18:19:01.979188 4928 data_layer.cpp:130] Transform time: 5.194 ms.
I0112 18:19:02.471039 4927 caffe.cpp:317] Batch 5, accuracy = 0.99
I0112 18:19:02.471273 4927 caffe.cpp:317] Batch 5, loss = 0.0517147
I0112 18:19:02.478014 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:02.478255 4928 data_layer.cpp:129] Read time: 0.664 ms.
I0112 18:19:02.478307 4928 data_layer.cpp:130] Transform time: 5.194 ms.
I0112 18:19:02.969833 4927 caffe.cpp:317] Batch 6, accuracy = 0.98
I0112 18:19:02.970077 4927 caffe.cpp:317] Batch 6, loss = 0.0685784
I0112 18:19:02.976835 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:02.977072 4928 data_layer.cpp:129] Read time: 0.638 ms.
I0112 18:19:02.977123 4928 data_layer.cpp:130] Transform time: 5.194 ms.
I0112 18:19:03.468849 4927 caffe.cpp:317] Batch 7, accuracy = 0.99
I0112 18:19:03.469127 4927 caffe.cpp:317] Batch 7, loss = 0.016397
I0112 18:19:03.475927 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:03.476166 4928 data_layer.cpp:129] Read time: 0.637 ms.
I0112 18:19:03.476215 4928 data_layer.cpp:130] Transform time: 5.258 ms.
I0112 18:19:03.967943 4927 caffe.cpp:317] Batch 8, accuracy = 1
I0112 18:19:03.968226 4927 caffe.cpp:317] Batch 8, loss = 0.010708
I0112 18:19:03.975049 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:03.975281 4928 data_layer.cpp:129] Read time: 0.642 ms.
I0112 18:19:03.975332 4928 data_layer.cpp:130] Transform time: 5.239 ms.
I0112 18:19:04.467239 4927 caffe.cpp:317] Batch 9, accuracy = 0.99
I0112 18:19:04.467501 4927 caffe.cpp:317] Batch 9, loss = 0.0439754
I0112 18:19:04.474278 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:04.474514 4928 data_layer.cpp:129] Read time: 0.636 ms.
I0112 18:19:04.474563 4928 data_layer.cpp:130] Transform time: 5.235 ms.
I0112 18:19:04.965932 4927 caffe.cpp:317] Batch 10, accuracy = 0.98
I0112 18:19:04.966205 4927 caffe.cpp:317] Batch 10, loss = 0.0561715
I0112 18:19:04.973026 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:04.973227 4928 data_layer.cpp:129] Read time: 0.641 ms.
I0112 18:19:04.973274 4928 data_layer.cpp:130] Transform time: 5.268 ms.
I0112 18:19:05.464938 4927 caffe.cpp:317] Batch 11, accuracy = 0.97
I0112 18:19:05.465180 4927 caffe.cpp:317] Batch 11, loss = 0.0499199
I0112 18:19:05.472012 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:05.472225 4928 data_layer.cpp:129] Read time: 0.642 ms.
I0112 18:19:05.472275 4928 data_layer.cpp:130] Transform time: 5.277 ms.
I0112 18:19:05.963747 4927 caffe.cpp:317] Batch 12, accuracy = 0.96
I0112 18:19:05.963994 4927 caffe.cpp:317] Batch 12, loss = 0.126818
I0112 18:19:05.970829 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:05.971026 4928 data_layer.cpp:129] Read time: 0.644 ms.
I0112 18:19:05.971075 4928 data_layer.cpp:130] Transform time: 5.245 ms.
I0112 18:19:06.462350 4927 caffe.cpp:317] Batch 13, accuracy = 0.98
I0112 18:19:06.462580 4927 caffe.cpp:317] Batch 13, loss = 0.042856
I0112 18:19:06.469331 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:06.469631 4928 data_layer.cpp:129] Read time: 0.63 ms.
I0112 18:19:06.469693 4928 data_layer.cpp:130] Transform time: 5.201 ms.
I0112 18:19:06.961202 4927 caffe.cpp:317] Batch 14, accuracy = 0.99
I0112 18:19:06.961447 4927 caffe.cpp:317] Batch 14, loss = 0.0221329
I0112 18:19:06.968205 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:06.968438 4928 data_layer.cpp:129] Read time: 0.634 ms.
I0112 18:19:06.968489 4928 data_layer.cpp:130] Transform time: 5.235 ms.
I0112 18:19:07.459849 4927 caffe.cpp:317] Batch 15, accuracy = 0.97
I0112 18:19:07.460063 4927 caffe.cpp:317] Batch 15, loss = 0.0545126
I0112 18:19:07.466822 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:07.467059 4928 data_layer.cpp:129] Read time: 0.632 ms.
I0112 18:19:07.467108 4928 data_layer.cpp:130] Transform time: 5.219 ms.
I0112 18:19:07.958456 4927 caffe.cpp:317] Batch 16, accuracy = 0.99
I0112 18:19:07.958734 4927 caffe.cpp:317] Batch 16, loss = 0.0278128
I0112 18:19:07.965502 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:07.965739 4928 data_layer.cpp:129] Read time: 0.642 ms.
I0112 18:19:07.965790 4928 data_layer.cpp:130] Transform time: 5.226 ms.
I0112 18:19:08.456940 4927 caffe.cpp:317] Batch 17, accuracy = 0.99
I0112 18:19:08.457226 4927 caffe.cpp:317] Batch 17, loss = 0.0294755
I0112 18:19:08.464036 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:08.464251 4928 data_layer.cpp:129] Read time: 0.692 ms.
I0112 18:19:08.464300 4928 data_layer.cpp:130] Transform time: 5.191 ms.
I0112 18:19:08.955890 4927 caffe.cpp:317] Batch 18, accuracy = 1
I0112 18:19:08.956151 4927 caffe.cpp:317] Batch 18, loss = 0.00674172
I0112 18:19:08.962944 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:08.963161 4928 data_layer.cpp:129] Read time: 0.635 ms.
I0112 18:19:08.963212 4928 data_layer.cpp:130] Transform time: 5.268 ms.
I0112 18:19:09.454437 4927 caffe.cpp:317] Batch 19, accuracy = 0.99
I0112 18:19:09.454717 4927 caffe.cpp:317] Batch 19, loss = 0.0572211
I0112 18:19:09.461544 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:09.461732 4928 data_layer.cpp:129] Read time: 0.644 ms.
I0112 18:19:09.461781 4928 data_layer.cpp:130] Transform time: 5.27 ms.
I0112 18:19:09.953292 4927 caffe.cpp:317] Batch 20, accuracy = 0.98
I0112 18:19:09.953536 4927 caffe.cpp:317] Batch 20, loss = 0.0989483
I0112 18:19:09.960389 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:09.960572 4928 data_layer.cpp:129] Read time: 0.641 ms.
I0112 18:19:09.960616 4928 data_layer.cpp:130] Transform time: 5.229 ms.
I0112 18:19:10.452282 4927 caffe.cpp:317] Batch 21, accuracy = 0.98
I0112 18:19:10.452569 4927 caffe.cpp:317] Batch 21, loss = 0.046975
I0112 18:19:10.459321 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:10.459615 4928 data_layer.cpp:129] Read time: 0.639 ms.
I0112 18:19:10.459681 4928 data_layer.cpp:130] Transform time: 5.216 ms.
I0112 18:19:10.950994 4927 caffe.cpp:317] Batch 22, accuracy = 0.99
I0112 18:19:10.951226 4927 caffe.cpp:317] Batch 22, loss = 0.039
I0112 18:19:10.957927 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:10.958166 4928 data_layer.cpp:129] Read time: 0.627 ms.
I0112 18:19:10.958217 4928 data_layer.cpp:130] Transform time: 5.197 ms.
I0112 18:19:11.449833 4927 caffe.cpp:317] Batch 23, accuracy = 0.98
I0112 18:19:11.450093 4927 caffe.cpp:317] Batch 23, loss = 0.0288257
I0112 18:19:11.456837 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:11.457073 4928 data_layer.cpp:129] Read time: 0.636 ms.
I0112 18:19:11.457124 4928 data_layer.cpp:130] Transform time: 5.221 ms.
I0112 18:19:11.948463 4927 caffe.cpp:317] Batch 24, accuracy = 0.98
I0112 18:19:11.948744 4927 caffe.cpp:317] Batch 24, loss = 0.0627499
I0112 18:19:11.955555 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:11.955797 4928 data_layer.cpp:129] Read time: 0.635 ms.
I0112 18:19:11.955847 4928 data_layer.cpp:130] Transform time: 5.236 ms.
I0112 18:19:12.447453 4927 caffe.cpp:317] Batch 25, accuracy = 0.99
I0112 18:19:12.447733 4927 caffe.cpp:317] Batch 25, loss = 0.0770601
I0112 18:19:12.454560 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:12.454789 4928 data_layer.cpp:129] Read time: 0.634 ms.
I0112 18:19:12.454840 4928 data_layer.cpp:130] Transform time: 5.269 ms.
I0112 18:19:12.946315 4927 caffe.cpp:317] Batch 26, accuracy = 0.99
I0112 18:19:12.946588 4927 caffe.cpp:317] Batch 26, loss = 0.0888426
I0112 18:19:12.953423 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:12.953652 4928 data_layer.cpp:129] Read time: 0.641 ms.
I0112 18:19:12.953701 4928 data_layer.cpp:130] Transform time: 5.254 ms.
I0112 18:19:13.445303 4927 caffe.cpp:317] Batch 27, accuracy = 0.99
I0112 18:19:13.445560 4927 caffe.cpp:317] Batch 27, loss = 0.0210676
I0112 18:19:13.452410 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:13.452630 4928 data_layer.cpp:129] Read time: 0.643 ms.
I0112 18:19:13.452678 4928 data_layer.cpp:130] Transform time: 5.299 ms.
I0112 18:19:13.944241 4927 caffe.cpp:317] Batch 28, accuracy = 0.99
I0112 18:19:13.944494 4927 caffe.cpp:317] Batch 28, loss = 0.0455608
I0112 18:19:13.951339 4928 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:19:13.951529 4928 data_layer.cpp:129] Read time: 0.63 ms.
I0112 18:19:13.951577 4928 data_layer.cpp:130] Transform time: 5.203 ms.
I0112 18:19:14.443364 4927 caffe.cpp:317] Batch 29, accuracy = 0.97
I0112 18:19:14.443640 4927 caffe.cpp:317] Batch 29, loss = 0.151275
I0112 18:19:14.443702 4927 caffe.cpp:322] Loss: 0.0486609
I0112 18:19:14.443778 4927 caffe.cpp:334] accuracy = 0.985667
I0112 18:19:14.443860 4927 caffe.cpp:334] loss = 0.0486609 (* 1 = 0.0486609 loss)
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mtk_open_acl.log =======================================
WARNING: Logging before InitGoogleLogging() is written to STDERR
I0112 18:21:03.084941 4939 caffe.cpp:288] Use CPU.
I0112 18:21:03.168365 4939 net.cpp:296] The NetState phase (1) differed from the phase (0) specified by a rule in layer mnist
I0112 18:21:03.168673 4939 net.cpp:53] Initializing net from parameters:
name: "LeNet"
state {
phase: TEST
level: 0
stage: ""
}
layer {
name: "mnist"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
scale: 0.00390625
}
data_param {
source: "/data/caffe_eg/mnist/mnist_test_lmdb"
batch_size: 100
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
convolution_param {
num_output: 20
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
convolution_param {
num_output: 50
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "ip1"
type: "InnerProduct"
bottom: "pool2"
top: "ip1"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
inner_product_param {
num_output: 500
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "ip1"
top: "ip1"
}
layer {
name: "ip2"
type: "InnerProduct"
bottom: "ip1"
top: "ip2"
param {
lr_mult: 1
}
param {
lr_mult: 2
}
inner_product_param {
num_output: 10
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "ip2"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip2"
bottom: "label"
top: "loss"
}
I0112 18:21:03.172957 4939 layer_factory.hpp:77] Creating layer mnist
I0112 18:21:03.173509 4939 db_lmdb.cpp:35] Opened lmdb /data/caffe_eg/mnist/mnist_test_lmdb
I0112 18:21:03.173676 4939 net.cpp:86] Creating Layer mnist
I0112 18:21:03.173784 4939 net.cpp:382] mnist -> data
I0112 18:21:03.173940 4939 net.cpp:382] mnist -> label
I0112 18:21:03.174170 4939 data_layer.cpp:45] output data size: 100,1,28,28
I0112 18:21:03.175276 4939 base_data_layer.cpp:72] Initializing prefetch
I0112 18:21:03.176249 4939 base_data_layer.cpp:75] Prefetch initialized.
I0112 18:21:03.176307 4939 net.cpp:124] Setting up mnist
I0112 18:21:03.176363 4939 net.cpp:131] Top shape: 100 1 28 28 (78400)
I0112 18:21:03.176442 4939 net.cpp:131] Top shape: 100 (100)
I0112 18:21:03.176482 4939 net.cpp:139] Memory required for data: 314000
I0112 18:21:03.176545 4939 layer_factory.hpp:77] Creating layer label_mnist_1_split
I0112 18:21:03.176658 4939 net.cpp:86] Creating Layer label_mnist_1_split
I0112 18:21:03.176712 4939 net.cpp:408] label_mnist_1_split <- label
I0112 18:21:03.176803 4939 net.cpp:382] label_mnist_1_split -> label_mnist_1_split_0
I0112 18:21:03.176892 4939 net.cpp:382] label_mnist_1_split -> label_mnist_1_split_1
I0112 18:21:03.176998 4939 net.cpp:124] Setting up label_mnist_1_split
I0112 18:21:03.177047 4939 net.cpp:131] Top shape: 100 (100)
I0112 18:21:03.177098 4939 net.cpp:131] Top shape: 100 (100)
I0112 18:21:03.177137 4939 net.cpp:139] Memory required for data: 314800
I0112 18:21:03.177180 4939 layer_factory.hpp:77] Creating layer conv1
I0112 18:21:03.177312 4939 net.cpp:86] Creating Layer conv1
I0112 18:21:03.177353 4939 net.cpp:408] conv1 <- data
I0112 18:21:03.177441 4939 net.cpp:382] conv1 -> conv1
I0112 18:21:03.177877 4939 net.cpp:124] Setting up conv1
I0112 18:21:03.177945 4939 net.cpp:131] Top shape: 100 20 24 24 (1152000)
I0112 18:21:03.177994 4939 net.cpp:139] Memory required for data: 4922800
I0112 18:21:03.178120 4939 layer_factory.hpp:77] Creating layer pool1
I0112 18:21:03.178225 4939 net.cpp:86] Creating Layer pool1
I0112 18:21:03.178276 4939 net.cpp:408] pool1 <- conv1
I0112 18:21:03.178340 4939 net.cpp:382] pool1 -> pool1
I0112 18:21:03.178478 4939 net.cpp:124] Setting up pool1
I0112 18:21:03.178521 4939 net.cpp:131] Top shape: 100 20 12 12 (288000)
I0112 18:21:03.178563 4939 net.cpp:139] Memory required for data: 6074800
I0112 18:21:03.178606 4939 layer_factory.hpp:77] Creating layer conv2
I0112 18:21:03.178714 4939 net.cpp:86] Creating Layer conv2
I0112 18:21:03.178757 4939 net.cpp:408] conv2 <- pool1
I0112 18:21:03.178824 4939 net.cpp:382] conv2 -> conv2
I0112 18:21:03.184686 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:03.184856 4955 data_layer.cpp:129] Read time: 0.668 ms.
I0112 18:21:03.184902 4955 data_layer.cpp:130] Transform time: 5.281 ms.
I0112 18:21:03.186022 4939 net.cpp:124] Setting up conv2
I0112 18:21:03.186111 4939 net.cpp:131] Top shape: 100 50 8 8 (320000)
I0112 18:21:03.186163 4939 net.cpp:139] Memory required for data: 7354800
I0112 18:21:03.186282 4939 layer_factory.hpp:77] Creating layer pool2
I0112 18:21:03.186383 4939 net.cpp:86] Creating Layer pool2
I0112 18:21:03.186434 4939 net.cpp:408] pool2 <- conv2
I0112 18:21:03.186506 4939 net.cpp:382] pool2 -> pool2
I0112 18:21:03.186645 4939 net.cpp:124] Setting up pool2
I0112 18:21:03.186691 4939 net.cpp:131] Top shape: 100 50 4 4 (80000)
I0112 18:21:03.186730 4939 net.cpp:139] Memory required for data: 7674800
I0112 18:21:03.186770 4939 layer_factory.hpp:77] Creating layer ip1
I0112 18:21:03.186858 4939 net.cpp:86] Creating Layer ip1
I0112 18:21:03.186902 4939 net.cpp:408] ip1 <- pool2
I0112 18:21:03.186993 4939 net.cpp:382] ip1 -> ip1
I0112 18:21:03.191673 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:03.191824 4955 data_layer.cpp:129] Read time: 0.646 ms.
I0112 18:21:03.191906 4955 data_layer.cpp:130] Transform time: 5.255 ms.
I0112 18:21:03.198546 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:03.198689 4955 data_layer.cpp:129] Read time: 0.625 ms.
I0112 18:21:03.198783 4955 data_layer.cpp:130] Transform time: 5.175 ms.
I0112 18:21:03.205486 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:03.205641 4955 data_layer.cpp:129] Read time: 0.647 ms.
I0112 18:21:03.205684 4955 data_layer.cpp:130] Transform time: 5.238 ms.
I0112 18:21:03.293665 4939 net.cpp:124] Setting up ip1
I0112 18:21:03.293856 4939 net.cpp:131] Top shape: 100 500 (50000)
I0112 18:21:03.293913 4939 net.cpp:139] Memory required for data: 7874800
I0112 18:21:03.294035 4939 layer_factory.hpp:77] Creating layer relu1
I0112 18:21:03.294142 4939 net.cpp:86] Creating Layer relu1
I0112 18:21:03.294204 4939 net.cpp:408] relu1 <- ip1
I0112 18:21:03.294270 4939 net.cpp:369] relu1 -> ip1 (in-place)
I0112 18:21:03.294345 4939 net.cpp:124] Setting up relu1
I0112 18:21:03.294383 4939 net.cpp:131] Top shape: 100 500 (50000)
I0112 18:21:03.294422 4939 net.cpp:139] Memory required for data: 8074800
I0112 18:21:03.294461 4939 layer_factory.hpp:77] Creating layer ip2
I0112 18:21:03.294545 4939 net.cpp:86] Creating Layer ip2
I0112 18:21:03.294636 4939 net.cpp:408] ip2 <- ip1
I0112 18:21:03.294733 4939 net.cpp:382] ip2 -> ip2
I0112 18:21:03.296279 4939 net.cpp:124] Setting up ip2
I0112 18:21:03.296366 4939 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:21:03.296411 4939 net.cpp:139] Memory required for data: 8078800
I0112 18:21:03.296516 4939 layer_factory.hpp:77] Creating layer ip2_ip2_0_split
I0112 18:21:03.296587 4939 net.cpp:86] Creating Layer ip2_ip2_0_split
I0112 18:21:03.296633 4939 net.cpp:408] ip2_ip2_0_split <- ip2
I0112 18:21:03.296696 4939 net.cpp:382] ip2_ip2_0_split -> ip2_ip2_0_split_0
I0112 18:21:03.296766 4939 net.cpp:382] ip2_ip2_0_split -> ip2_ip2_0_split_1
I0112 18:21:03.296836 4939 net.cpp:124] Setting up ip2_ip2_0_split
I0112 18:21:03.296880 4939 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:21:03.296924 4939 net.cpp:131] Top shape: 100 10 (1000)
I0112 18:21:03.296967 4939 net.cpp:139] Memory required for data: 8086800
I0112 18:21:03.297004 4939 layer_factory.hpp:77] Creating layer accuracy
I0112 18:21:03.297101 4939 net.cpp:86] Creating Layer accuracy
I0112 18:21:03.297140 4939 net.cpp:408] accuracy <- ip2_ip2_0_split_0
I0112 18:21:03.297191 4939 net.cpp:408] accuracy <- label_mnist_1_split_0
I0112 18:21:03.297245 4939 net.cpp:382] accuracy -> accuracy
I0112 18:21:03.297317 4939 net.cpp:124] Setting up accuracy
I0112 18:21:03.297360 4939 net.cpp:131] Top shape: (1)
I0112 18:21:03.297404 4939 net.cpp:139] Memory required for data: 8086804
I0112 18:21:03.297446 4939 layer_factory.hpp:77] Creating layer loss
I0112 18:21:03.297502 4939 net.cpp:86] Creating Layer loss
I0112 18:21:03.297545 4939 net.cpp:408] loss <- ip2_ip2_0_split_1
I0112 18:21:03.297596 4939 net.cpp:408] loss <- label_mnist_1_split_1
I0112 18:21:03.297657 4939 net.cpp:382] loss -> loss
I0112 18:21:03.297744 4939 layer_factory.hpp:77] Creating layer loss
I0112 18:21:03.297914 4939 net.cpp:124] Setting up loss
I0112 18:21:03.297960 4939 net.cpp:131] Top shape: (1)
I0112 18:21:03.298003 4939 net.cpp:134] with loss weight 1
I0112 18:21:03.298074 4939 net.cpp:139] Memory required for data: 8086808
I0112 18:21:03.298121 4939 net.cpp:200] loss needs backward computation.
I0112 18:21:03.298168 4939 net.cpp:202] accuracy does not need backward computation.
I0112 18:21:03.298210 4939 net.cpp:200] ip2_ip2_0_split needs backward computation.
I0112 18:21:03.298261 4939 net.cpp:200] ip2 needs backward computation.
I0112 18:21:03.298301 4939 net.cpp:200] relu1 needs backward computation.
I0112 18:21:03.298341 4939 net.cpp:200] ip1 needs backward computation.
I0112 18:21:03.298380 4939 net.cpp:200] pool2 needs backward computation.
I0112 18:21:03.298420 4939 net.cpp:200] conv2 needs backward computation.
I0112 18:21:03.298464 4939 net.cpp:200] pool1 needs backward computation.
I0112 18:21:03.298506 4939 net.cpp:200] conv1 needs backward computation.
I0112 18:21:03.298550 4939 net.cpp:202] label_mnist_1_split does not need backward computation.
I0112 18:21:03.298594 4939 net.cpp:202] mnist does not need backward computation.
I0112 18:21:03.298630 4939 net.cpp:244] This network produces output accuracy
I0112 18:21:03.298676 4939 net.cpp:244] This network produces output loss
I0112 18:21:03.298787 4939 net.cpp:257] Network initialization done.
I0112 18:21:03.343601 4939 net.cpp:749] Copying source layer mnist
I0112 18:21:03.343785 4939 net.cpp:749] Copying source layer conv1
I0112 18:21:03.343896 4939 net.cpp:749] Copying source layer pool1
I0112 18:21:03.343936 4939 net.cpp:749] Copying source layer conv2
I0112 18:21:03.345243 4939 net.cpp:749] Copying source layer pool2
I0112 18:21:03.345346 4939 net.cpp:749] Copying source layer ip1
I0112 18:21:03.364862 4939 net.cpp:749] Copying source layer relu1
I0112 18:21:03.365064 4939 net.cpp:749] Copying source layer ip2
I0112 18:21:03.365422 4939 net.cpp:749] Copying source layer loss
I0112 18:21:03.368325 4939 caffe.cpp:294] Running for 30 iterations.
I0112 18:21:03.991498 4939 caffe.cpp:317] Batch 0, accuracy = 0.11
I0112 18:21:03.991700 4939 caffe.cpp:317] Batch 0, loss = 2.30272
I0112 18:21:03.999531 4955 data_layer.cpp:128] Prefetch batch: 7 ms.
I0112 18:21:04.000589 4955 data_layer.cpp:129] Read time: 0.742 ms.
I0112 18:21:04.000680 4955 data_layer.cpp:130] Transform time: 5.978 ms.
I0112 18:21:04.656731 4939 caffe.cpp:317] Batch 1, accuracy = 0.1
I0112 18:21:04.656937 4939 caffe.cpp:317] Batch 1, loss = 2.30298
I0112 18:21:04.683619 4955 data_layer.cpp:128] Prefetch batch: 26 ms.
I0112 18:21:04.684185 4955 data_layer.cpp:129] Read time: 1.041 ms.
I0112 18:21:04.684267 4955 data_layer.cpp:130] Transform time: 24.223 ms.
I0112 18:21:05.298616 4939 caffe.cpp:317] Batch 2, accuracy = 0.13
I0112 18:21:05.298820 4939 caffe.cpp:317] Batch 2, loss = 2.30277
I0112 18:21:05.307432 4955 data_layer.cpp:128] Prefetch batch: 8 ms.
I0112 18:21:05.307773 4955 data_layer.cpp:129] Read time: 0.819 ms.
I0112 18:21:05.307845 4955 data_layer.cpp:130] Transform time: 6.679 ms.
I0112 18:21:06.068819 4939 caffe.cpp:317] Batch 3, accuracy = 0.07
I0112 18:21:06.069010 4939 caffe.cpp:317] Batch 3, loss = 2.3027
I0112 18:21:06.076590 4955 data_layer.cpp:128] Prefetch batch: 7 ms.
I0112 18:21:06.076782 4955 data_layer.cpp:129] Read time: 0.764 ms.
I0112 18:21:06.076832 4955 data_layer.cpp:130] Transform time: 5.796 ms.
I0112 18:21:06.706459 4939 caffe.cpp:317] Batch 4, accuracy = 0.13
I0112 18:21:06.706658 4939 caffe.cpp:317] Batch 4, loss = 2.3028
I0112 18:21:06.714949 4955 data_layer.cpp:128] Prefetch batch: 8 ms.
I0112 18:21:06.715394 4955 data_layer.cpp:129] Read time: 0.776 ms.
I0112 18:21:06.715461 4955 data_layer.cpp:130] Transform time: 6.29 ms.
I0112 18:21:07.454897 4939 caffe.cpp:317] Batch 5, accuracy = 0.1
I0112 18:21:07.455111 4939 caffe.cpp:317] Batch 5, loss = 2.30277
I0112 18:21:07.465002 4955 data_layer.cpp:128] Prefetch batch: 9 ms.
I0112 18:21:07.465601 4955 data_layer.cpp:129] Read time: 1.033 ms.
I0112 18:21:07.465689 4955 data_layer.cpp:130] Transform time: 7.558 ms.
I0112 18:21:08.191756 4939 caffe.cpp:317] Batch 6, accuracy = 0.1
I0112 18:21:08.191975 4939 caffe.cpp:317] Batch 6, loss = 2.30298
I0112 18:21:08.207046 4955 data_layer.cpp:128] Prefetch batch: 14 ms.
I0112 18:21:08.222504 4955 data_layer.cpp:129] Read time: 1.081 ms.
I0112 18:21:08.222916 4955 data_layer.cpp:130] Transform time: 12.428 ms.
I0112 18:21:08.888784 4939 caffe.cpp:317] Batch 7, accuracy = 0.06
I0112 18:21:08.888995 4939 caffe.cpp:317] Batch 7, loss = 2.30239
I0112 18:21:08.895900 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:08.896087 4955 data_layer.cpp:129] Read time: 0.685 ms.
I0112 18:21:08.896133 4955 data_layer.cpp:130] Transform time: 5.234 ms.
I0112 18:21:09.563263 4939 caffe.cpp:317] Batch 8, accuracy = 0.07
I0112 18:21:09.563482 4939 caffe.cpp:317] Batch 8, loss = 2.30192
I0112 18:21:09.571055 4955 data_layer.cpp:128] Prefetch batch: 7 ms.
I0112 18:21:09.571507 4955 data_layer.cpp:129] Read time: 0.698 ms.
I0112 18:21:09.571594 4955 data_layer.cpp:130] Transform time: 5.899 ms.
I0112 18:21:10.166699 4939 caffe.cpp:317] Batch 9, accuracy = 0.08
I0112 18:21:10.166920 4939 caffe.cpp:317] Batch 9, loss = 2.30239
I0112 18:21:10.195009 4955 data_layer.cpp:128] Prefetch batch: 27 ms.
I0112 18:21:10.195531 4955 data_layer.cpp:129] Read time: 0.988 ms.
I0112 18:21:10.195607 4955 data_layer.cpp:130] Transform time: 21.669 ms.
I0112 18:21:10.862153 4939 caffe.cpp:317] Batch 10, accuracy = 0.1
I0112 18:21:10.862344 4939 caffe.cpp:317] Batch 10, loss = 2.30258
I0112 18:21:10.870364 4955 data_layer.cpp:128] Prefetch batch: 7 ms.
I0112 18:21:10.870573 4955 data_layer.cpp:129] Read time: 0.772 ms.
I0112 18:21:10.870626 4955 data_layer.cpp:130] Transform time: 6.116 ms.
I0112 18:21:11.482462 4939 caffe.cpp:317] Batch 11, accuracy = 0.08
I0112 18:21:11.482668 4939 caffe.cpp:317] Batch 11, loss = 2.30272
I0112 18:21:11.493033 4955 data_layer.cpp:128] Prefetch batch: 10 ms.
I0112 18:21:11.493221 4955 data_layer.cpp:129] Read time: 0.69 ms.
I0112 18:21:11.493271 4955 data_layer.cpp:130] Transform time: 5.18 ms.
I0112 18:21:12.040501 4939 caffe.cpp:317] Batch 12, accuracy = 0.08
I0112 18:21:12.040684 4939 caffe.cpp:317] Batch 12, loss = 2.30192
I0112 18:21:12.047759 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:12.047948 4955 data_layer.cpp:129] Read time: 0.687 ms.
I0112 18:21:12.047999 4955 data_layer.cpp:130] Transform time: 5.362 ms.
I0112 18:21:12.656080 4939 caffe.cpp:317] Batch 13, accuracy = 0.1
I0112 18:21:12.656268 4939 caffe.cpp:317] Batch 13, loss = 2.3027
I0112 18:21:12.665878 4955 data_layer.cpp:128] Prefetch batch: 9 ms.
I0112 18:21:12.675768 4955 data_layer.cpp:129] Read time: 0.702 ms.
I0112 18:21:12.675890 4955 data_layer.cpp:130] Transform time: 7.881 ms.
I0112 18:21:13.254046 4939 caffe.cpp:317] Batch 14, accuracy = 0.14
I0112 18:21:13.254243 4939 caffe.cpp:317] Batch 14, loss = 2.30298
I0112 18:21:13.274111 4955 data_layer.cpp:128] Prefetch batch: 19 ms.
I0112 18:21:13.274307 4955 data_layer.cpp:129] Read time: 0.752 ms.
I0112 18:21:13.274359 4955 data_layer.cpp:130] Transform time: 5.89 ms.
I0112 18:21:13.991847 4939 caffe.cpp:317] Batch 15, accuracy = 0.11
I0112 18:21:13.992028 4939 caffe.cpp:317] Batch 15, loss = 2.30272
I0112 18:21:13.998821 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:14.001773 4955 data_layer.cpp:129] Read time: 0.656 ms.
I0112 18:21:14.013264 4955 data_layer.cpp:130] Transform time: 5.163 ms.
I0112 18:21:14.627467 4939 caffe.cpp:317] Batch 16, accuracy = 0.12
I0112 18:21:14.627679 4939 caffe.cpp:317] Batch 16, loss = 2.30277
I0112 18:21:14.634605 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:14.634816 4955 data_layer.cpp:129] Read time: 0.763 ms.
I0112 18:21:14.634865 4955 data_layer.cpp:130] Transform time: 5.192 ms.
I0112 18:21:15.336454 4939 caffe.cpp:317] Batch 17, accuracy = 0.09
I0112 18:21:15.336684 4939 caffe.cpp:317] Batch 17, loss = 2.30263
I0112 18:21:15.364289 4955 data_layer.cpp:128] Prefetch batch: 27 ms.
I0112 18:21:15.367653 4955 data_layer.cpp:129] Read time: 1.084 ms.
I0112 18:21:15.367790 4955 data_layer.cpp:130] Transform time: 24.891 ms.
I0112 18:21:15.972120 4939 caffe.cpp:317] Batch 18, accuracy = 0.1
I0112 18:21:15.972316 4939 caffe.cpp:317] Batch 18, loss = 2.30298
I0112 18:21:15.979261 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:15.979476 4955 data_layer.cpp:129] Read time: 0.689 ms.
I0112 18:21:15.979526 4955 data_layer.cpp:130] Transform time: 5.273 ms.
I0112 18:21:16.715196 4939 caffe.cpp:317] Batch 19, accuracy = 0.08
I0112 18:21:16.715435 4939 caffe.cpp:317] Batch 19, loss = 2.30239
I0112 18:21:16.728497 4955 data_layer.cpp:128] Prefetch batch: 12 ms.
I0112 18:21:16.729202 4955 data_layer.cpp:129] Read time: 1.376 ms.
I0112 18:21:16.729313 4955 data_layer.cpp:130] Transform time: 9.945 ms.
I0112 18:21:17.464715 4939 caffe.cpp:317] Batch 20, accuracy = 0.08
I0112 18:21:17.464930 4939 caffe.cpp:317] Batch 20, loss = 2.30298
I0112 18:21:17.478517 4955 data_layer.cpp:128] Prefetch batch: 13 ms.
I0112 18:21:17.495019 4955 data_layer.cpp:129] Read time: 0.975 ms.
I0112 18:21:17.495159 4955 data_layer.cpp:130] Transform time: 11.185 ms.
I0112 18:21:18.143924 4939 caffe.cpp:317] Batch 21, accuracy = 0.06
I0112 18:21:18.144124 4939 caffe.cpp:317] Batch 21, loss = 2.30238
I0112 18:21:18.151165 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:18.151368 4955 data_layer.cpp:129] Read time: 0.703 ms.
I0112 18:21:18.151417 4955 data_layer.cpp:130] Transform time: 5.361 ms.
I0112 18:21:18.796382 4939 caffe.cpp:317] Batch 22, accuracy = 0.12
I0112 18:21:18.796591 4939 caffe.cpp:317] Batch 22, loss = 2.3028
I0112 18:21:18.803570 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:18.803819 4955 data_layer.cpp:129] Read time: 0.704 ms.
I0112 18:21:18.803884 4955 data_layer.cpp:130] Transform time: 5.277 ms.
I0112 18:21:19.395406 4939 caffe.cpp:317] Batch 23, accuracy = 0.1
I0112 18:21:19.395613 4939 caffe.cpp:317] Batch 23, loss = 2.30277
I0112 18:21:19.408810 4955 data_layer.cpp:128] Prefetch batch: 12 ms.
I0112 18:21:19.418444 4955 data_layer.cpp:129] Read time: 0.9 ms.
I0112 18:21:19.418576 4955 data_layer.cpp:130] Transform time: 10.966 ms.
I0112 18:21:20.104066 4939 caffe.cpp:317] Batch 24, accuracy = 0.14
I0112 18:21:20.104279 4939 caffe.cpp:317] Batch 24, loss = 2.30238
I0112 18:21:20.116556 4955 data_layer.cpp:128] Prefetch batch: 12 ms.
I0112 18:21:20.130146 4955 data_layer.cpp:129] Read time: 0.898 ms.
I0112 18:21:20.130306 4955 data_layer.cpp:130] Transform time: 10.063 ms.
I0112 18:21:20.777202 4939 caffe.cpp:317] Batch 25, accuracy = 0.09
I0112 18:21:20.777466 4939 caffe.cpp:317] Batch 25, loss = 2.3028
I0112 18:21:20.788323 4955 data_layer.cpp:128] Prefetch batch: 10 ms.
I0112 18:21:20.788925 4955 data_layer.cpp:129] Read time: 0.949 ms.
I0112 18:21:20.789021 4955 data_layer.cpp:130] Transform time: 8.491 ms.
I0112 18:21:21.450106 4939 caffe.cpp:317] Batch 26, accuracy = 0.1
I0112 18:21:21.450218 4939 caffe.cpp:317] Batch 26, loss = 2.30192
I0112 18:21:21.457077 4955 data_layer.cpp:128] Prefetch batch: 6 ms.
I0112 18:21:21.457684 4955 data_layer.cpp:129] Read time: 0.71 ms.
I0112 18:21:21.457792 4955 data_layer.cpp:130] Transform time: 5.218 ms.
I0112 18:21:22.026882 4939 caffe.cpp:317] Batch 27, accuracy = 0.09
I0112 18:21:22.027078 4939 caffe.cpp:317] Batch 27, loss = 2.30272
I0112 18:21:22.038611 4955 data_layer.cpp:128] Prefetch batch: 11 ms.
I0112 18:21:22.049075 4955 data_layer.cpp:129] Read time: 1.194 ms.
I0112 18:21:22.049204 4955 data_layer.cpp:130] Transform time: 9.116 ms.
I0112 18:21:22.654046 4939 caffe.cpp:317] Batch 28, accuracy = 0.11
I0112 18:21:22.654257 4939 caffe.cpp:317] Batch 28, loss = 2.30192
I0112 18:21:22.673635 4955 data_layer.cpp:128] Prefetch batch: 19 ms.
I0112 18:21:22.678758 4955 data_layer.cpp:129] Read time: 0.882 ms.
I0112 18:21:22.678890 4955 data_layer.cpp:130] Transform time: 17.162 ms.
I0112 18:21:23.337829 4939 caffe.cpp:317] Batch 29, accuracy = 0.14
I0112 18:21:23.338044 4939 caffe.cpp:317] Batch 29, loss = 2.3027
I0112 18:21:23.338109 4939 caffe.cpp:322] Loss: 2.30261
I0112 18:21:23.338199 4939 caffe.cpp:334] accuracy = 0.0993333
I0112 18:21:23.338338 4939 caffe.cpp:334] loss = 2.30261 (* 1 = 2.30261 loss)
0m20.48s real 0m20.73s user 0m12.44s system

@ymotola ymotola mentioned this issue Jan 18, 2018
Closed
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