Can't start trianing : blob.cpp:133] Check failed: data_

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n1ma Sh1

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Sep 28, 2022, 6:43:18 AM9/28/22

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Ubuntu1804

I'm testing a table edge detection project，the original data img size is 1280*720.But i can't start training process.

Error message

```
I0928 17:49:53.488544 30253 layer_factory.hpp:77] Creating layer data
I0928 17:49:53.488591 30253 db_lmdb.cpp:35] Opened lmdb /home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_lmdb
I0928 17:49:53.488602 30253 net.cpp:86] Creating Layer data
I0928 17:49:53.488607 30253 net.cpp:382] data -> data
I0928 17:49:53.488624 30253 net.cpp:382] data -> label
I0928 17:49:53.488631 30253 data_transformer.cpp:25] Loading mean file from: /home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_mean.binaryproto
F0928 17:49:53.488655 30253 blob.cpp:133] Check failed: data_
*** Check failure stack trace: ***
@ 0x7fc5b9e070cd google::LogMessage::Fail()
@ 0x7fc5b9e08f33 google::LogMessage::SendToLog()
@ 0x7fc5b9e06c28 google::LogMessage::Flush()
@ 0x7fc5b9e09999 google::LogMessageFatal::~LogMessageFatal()
@ 0x7fc5ba2c83db caffe::Blob<>::mutable_cpu_data()
@ 0x7fc5ba2d1db7 caffe::Blob<>::FromProto()
@ 0x7fc5ba2f7632 caffe::DataTransformer<>::DataTransformer()
@ 0x7fc5ba2239a5 caffe::BaseDataLayer<>::LayerSetUp()
@ 0x7fc5ba223abc caffe::BasePrefetchingDataLayer<>::LayerSetUp()
@ 0x7fc5ba2e6eb3 caffe::Net<>::Init()
@ 0x7fc5ba2e861e caffe::Net<>::Net()
@ 0x7fc5ba1ae0c4 caffe::Solver<>::InitTrainNet()
@ 0x7fc5ba1ae673 caffe::Solver<>::Init()
@ 0x7fc5ba1ae99f caffe::Solver<>::Solver()
@ 0x7fc5ba1940f1 caffe::Creator_AdamSolver<>()
@ 0x55b980d7aec7 (unknown)
@ 0x55b980d76f80 (unknown)
@ 0x7fc5b8413c87 __libc_start_main
@ 0x55b980d77a3a (unknown)
```

full log:

I0928 17:49:53.486743 30253 caffe.cpp:197] Use CPU.
I0928 17:49:53.486958 30253 solver.cpp:45] Initializing solver from parameters:
test_iter: 75
test_interval: 640
base_lr: 0.0001
display: 200
max_iter: 50000
lr_policy: "fixed"
power: 1
momentum: 0.9
weight_decay: 0.0005
snapshot: 2000
snapshot_prefix: "./collision_avoidance"
solver_mode: CPU
net: "/home/lhy/Downloads/code/Algorithm-collision_anti-drop/algorithm/Resnet18_classification/Resnet18_classification_train.prototxt"
train_state {
level: 0
stage: ""
}
type: "Adam"
I0928 17:49:53.487066 30253 solver.cpp:102] Creating training net from net file: /home/lhy/Downloads/code/Algorithm-collision_anti-drop/algorithm/Resnet18_classification/Resnet18_classification_train.prototxt
I0928 17:49:53.487984 30253 net.cpp:296] The NetState phase (0) differed from the phase (1) specified by a rule in layer data
I0928 17:49:53.488020 30253 net.cpp:53] Initializing net from parameters:
name: "ResNet-18"
state {
phase: TRAIN
level: 0
stage: ""
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
mean_file: "/home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_mean.binaryproto"
}
data_param {
source: "/home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_lmdb"
batch_size: 32
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 64
bias_term: false
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn_conv1"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale_conv1"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
bias_term: true
}
}
layer {
name: "conv1_relu"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "res2a_branch1"
type: "Convolution"
bottom: "pool1"
top: "res2a_branch1"
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn2a_branch1"
type: "BatchNorm"
bottom: "res2a_branch1"
top: "res2a_branch1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale2a_branch1"
type: "Scale"
bottom: "res2a_branch1"
top: "res2a_branch1"
scale_param {
bias_term: true
}
}
layer {
name: "res2a_branch2a"
type: "Convolution"
bottom: "pool1"
top: "res2a_branch2a"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn2a_branch2a"
type: "BatchNorm"
bottom: "res2a_branch2a"
top: "res2a_branch2a"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale2a_branch2a"
type: "Scale"
bottom: "res2a_branch2a"
top: "res2a_branch2a"
scale_param {
bias_term: true
}
}
layer {
name: "res2a_branch2a_relu"
type: "ReLU"
bottom: "res2a_branch2a"
top: "res2a_branch2a"
}
layer {
name: "res2a_branch2b"
type: "Convolution"
bottom: "res2a_branch2a"
top: "res2a_branch2b"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn2a_branch2b"
type: "BatchNorm"
bottom: "res2a_branch2b"
top: "res2a_branch2b"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale2a_branch2b"
type: "Scale"
bottom: "res2a_branch2b"
top: "res2a_branch2b"
scale_param {
bias_term: true
}
}
layer {
name: "res2a"
type: "Eltwise"
bottom: "res2a_branch1"
bottom: "res2a_branch2b"
top: "res2a"
eltwise_param {
operation: SUM
}
}
layer {
name: "res2a_relu"
type: "ReLU"
bottom: "res2a"
top: "res2a"
}
layer {
name: "res2b_branch2a"
type: "Convolution"
bottom: "res2a"
top: "res2b_branch2a"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn2b_branch2a"
type: "BatchNorm"
bottom: "res2b_branch2a"
top: "res2b_branch2a"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale2b_branch2a"
type: "Scale"
bottom: "res2b_branch2a"
top: "res2b_branch2a"
scale_param {
bias_term: true
}
}
layer {
name: "res2b_branch2a_relu"
type: "ReLU"
bottom: "res2b_branch2a"
top: "res2b_branch2a"
}
layer {
name: "res2b_branch2b"
type: "Convolution"
bottom: "res2b_branch2a"
top: "res2b_branch2b"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn2b_branch2b"
type: "BatchNorm"
bottom: "res2b_branch2b"
top: "res2b_branch2b"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale2b_branch2b"
type: "Scale"
bottom: "res2b_branch2b"
top: "res2b_branch2b"
scale_param {
bias_term: true
}
}
layer {
name: "res2b"
type: "Eltwise"
bottom: "res2a"
bottom: "res2b_branch2b"
top: "res2b"
eltwise_param {
operation: SUM
}
}
layer {
name: "res2b_relu"
type: "ReLU"
bottom: "res2b"
top: "res2b"
}
layer {
name: "res3a_branch1"
type: "Convolution"
bottom: "res2b"
top: "res3a_branch1"
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn3a_branch1"
type: "BatchNorm"
bottom: "res3a_branch1"
top: "res3a_branch1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale3a_branch1"
type: "Scale"
bottom: "res3a_branch1"
top: "res3a_branch1"
scale_param {
bias_term: true
}
}
layer {
name: "res3a_branch2a"
type: "Convolution"
bottom: "res2b"
top: "res3a_branch2a"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn3a_branch2a"
type: "BatchNorm"
bottom: "res3a_branch2a"
top: "res3a_branch2a"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale3a_branch2a"
type: "Scale"
bottom: "res3a_branch2a"
top: "res3a_branch2a"
scale_param {
bias_term: true
}
}
layer {
name: "res3a_branch2a_relu"
type: "ReLU"
bottom: "res3a_branch2a"
top: "res3a_branch2a"
}
layer {
name: "res3a_branch2b"
type: "Convolution"
bottom: "res3a_branch2a"
top: "res3a_branch2b"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn3a_branch2b"
type: "BatchNorm"
bottom: "res3a_branch2b"
top: "res3a_branch2b"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale3a_branch2b"
type: "Scale"
bottom: "res3a_branch2b"
top: "res3a_branch2b"
scale_param {
bias_term: true
}
}
layer {
name: "res3a"
type: "Eltwise"
bottom: "res3a_branch1"
bottom: "res3a_branch2b"
top: "res3a"
eltwise_param {
operation: SUM
}
}
layer {
name: "res3a_relu"
type: "ReLU"
bottom: "res3a"
top: "res3a"
}
layer {
name: "res3b_branch2a"
type: "Convolution"
bottom: "res3a"
top: "res3b_branch2a"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn3b_branch2a"
type: "BatchNorm"
bottom: "res3b_branch2a"
top: "res3b_branch2a"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale3b_branch2a"
type: "Scale"
bottom: "res3b_branch2a"
top: "res3b_branch2a"
scale_param {
bias_term: true
}
}
layer {
name: "res3b_branch2a_relu"
type: "ReLU"
bottom: "res3b_branch2a"
top: "res3b_branch2a"
}
layer {
name: "res3b_branch2b"
type: "Convolution"
bottom: "res3b_branch2a"
top: "res3b_branch2b"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn3b_branch2b"
type: "BatchNorm"
bottom: "res3b_branch2b"
top: "res3b_branch2b"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale3b_branch2b"
type: "Scale"
bottom: "res3b_branch2b"
top: "res3b_branch2b"
scale_param {
bias_term: true
}
}
layer {
name: "res3b"
type: "Eltwise"
bottom: "res3a"
bottom: "res3b_branch2b"
top: "res3b"
eltwise_param {
operation: SUM
}
}
layer {
name: "res3b_relu"
type: "ReLU"
bottom: "res3b"
top: "res3b"
}
layer {
name: "res4a_branch1"
type: "Convolution"
bottom: "res3b"
top: "res4a_branch1"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn4a_branch1"
type: "BatchNorm"
bottom: "res4a_branch1"
top: "res4a_branch1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale4a_branch1"
type: "Scale"
bottom: "res4a_branch1"
top: "res4a_branch1"
scale_param {
bias_term: true
}
}
layer {
name: "res4a_branch2a"
type: "Convolution"
bottom: "res3b"
top: "res4a_branch2a"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "bn4a_branch2a"
type: "BatchNorm"
bottom: "res4a_branch2a"
top: "res4a_branch2a"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale4a_branch2a"
type: "Scale"
bottom: "res4a_branch2a"
top: "res4a_branch2a"
scale_param {
bias_term: true
}
}
layer {
name: "res4a_branch2a_relu"
type: "ReLU"
bottom: "res4a_branch2a"
top: "res4a_branch2a"
}
layer {
name: "res4a_branch2b-1"
type: "Convolution"
bottom: "res4a_branch2a"
top: "res4a_branch2b-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn4a_branch2b"
type: "BatchNorm"
bottom: "res4a_branch2b-1"
top: "res4a_branch2b-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale4a_branch2b"
type: "Scale"
bottom: "res4a_branch2b-1"
top: "res4a_branch2b-1"
scale_param {
bias_term: true
}
}
layer {
name: "res4a"
type: "Eltwise"
bottom: "res4a_branch1"
bottom: "res4a_branch2b-1"
top: "res4a"
eltwise_param {
operation: SUM
}
}
layer {
name: "res4a_relu"
type: "ReLU"
bottom: "res4a"
top: "res4a"
}
layer {
name: "res4b_branch2a-1"
type: "Convolution"
bottom: "res4a"
top: "res4b_branch2a-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn4b_branch2a"
type: "BatchNorm"
bottom: "res4b_branch2a-1"
top: "res4b_branch2a-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale4b_branch2a"
type: "Scale"
bottom: "res4b_branch2a-1"
top: "res4b_branch2a-1"
scale_param {
bias_term: true
}
}
layer {
name: "res4b_branch2a_relu"
type: "ReLU"
bottom: "res4b_branch2a-1"
top: "res4b_branch2a-1"
}
layer {
name: "res4b_branch2b-1"
type: "Convolution"
bottom: "res4b_branch2a-1"
top: "res4b_branch2b-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn4b_branch2b"
type: "BatchNorm"
bottom: "res4b_branch2b-1"
top: "res4b_branch2b-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale4b_branch2b"
type: "Scale"
bottom: "res4b_branch2b-1"
top: "res4b_branch2b-1"
scale_param {
bias_term: true
}
}
layer {
name: "res4b"
type: "Eltwise"
bottom: "res4a"
bottom: "res4b_branch2b-1"
top: "res4b"
eltwise_param {
operation: SUM
}
}
layer {
name: "res4b_relu"
type: "ReLU"
bottom: "res4b"
top: "res4b"
}
layer {
name: "res5a_branch1-1"
type: "Convolution"
bottom: "res4b"
top: "res5a_branch1-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn5a_branch1"
type: "BatchNorm"
bottom: "res5a_branch1-1"
top: "res5a_branch1-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale5a_branch1"
type: "Scale"
bottom: "res5a_branch1-1"
top: "res5a_branch1-1"
scale_param {
bias_term: true
}
}
layer {
name: "res5a_branch2a-1"
type: "Convolution"
bottom: "res4b"
top: "res5a_branch2a-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn5a_branch2a"
type: "BatchNorm"
bottom: "res5a_branch2a-1"
top: "res5a_branch2a-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale5a_branch2a"
type: "Scale"
bottom: "res5a_branch2a-1"
top: "res5a_branch2a-1"
scale_param {
bias_term: true
}
}
layer {
name: "res5a_branch2a_relu"
type: "ReLU"
bottom: "res5a_branch2a-1"
top: "res5a_branch2a-1"
}
layer {
name: "res5a_branch2b-1"
type: "Convolution"
bottom: "res5a_branch2a-1"
top: "res5a_branch2b-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn5a_branch2b"
type: "BatchNorm"
bottom: "res5a_branch2b-1"
top: "res5a_branch2b-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale5a_branch2b"
type: "Scale"
bottom: "res5a_branch2b-1"
top: "res5a_branch2b-1"
scale_param {
bias_term: true
}
}
layer {
name: "res5a"
type: "Eltwise"
bottom: "res5a_branch1-1"
bottom: "res5a_branch2b-1"
top: "res5a"
eltwise_param {
operation: SUM
}
}
layer {
name: "res5a_relu"
type: "ReLU"
bottom: "res5a"
top: "res5a"
}
layer {
name: "res5b_branch2a-1"
type: "Convolution"
bottom: "res5a"
top: "res5b_branch2a-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn5b_branch2a"
type: "BatchNorm"
bottom: "res5b_branch2a-1"
top: "res5b_branch2a-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale5b_branch2a"
type: "Scale"
bottom: "res5b_branch2a-1"
top: "res5b_branch2a-1"
scale_param {
bias_term: true
}
}
layer {
name: "res5b_branch2a_relu"
type: "ReLU"
bottom: "res5b_branch2a-1"
top: "res5b_branch2a-1"
}
layer {
name: "res5b_branch2b-1"
type: "Convolution"
bottom: "res5b_branch2a-1"
top: "res5b_branch2b-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn5b_branch2b"
type: "BatchNorm"
bottom: "res5b_branch2b-1"
top: "res5b_branch2b-1"
batch_norm_param {
moving_average_fraction: 0.9
}
}
layer {
name: "scale5b_branch2b"
type: "Scale"
bottom: "res5b_branch2b-1"
top: "res5b_branch2b-1"
scale_param {
bias_term: true
}
}
layer {
name: "res5b"
type: "Eltwise"
bottom: "res5a"
bottom: "res5b_branch2b-1"
top: "res5b"
eltwise_param {
operation: SUM
}
}
layer {
name: "res5b_relu"
type: "ReLU"
bottom: "res5b"
top: "res5b"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "res5b"
top: "pool5"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
}
}
layer {
name: "fc2"
type: "InnerProduct"
bottom: "pool5"
top: "fc2"
param {
lr_mult: 50
decay_mult: 1
}
param {
lr_mult: 100
decay_mult: 1
}
inner_product_param {
num_output: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc2"
bottom: "label"
top: "loss"
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fc2"
bottom: "label"
top: "accuracy"
}
I0928 17:49:53.488544 30253 layer_factory.hpp:77] Creating layer data
I0928 17:49:53.488591 30253 db_lmdb.cpp:35] Opened lmdb /home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_lmdb
I0928 17:49:53.488602 30253 net.cpp:86] Creating Layer data
I0928 17:49:53.488607 30253 net.cpp:382] data -> data
I0928 17:49:53.488624 30253 net.cpp:382] data -> label
I0928 17:49:53.488631 30253 data_transformer.cpp:25] Loading mean file from: /home/lhy/Downloads/code/Algorithm-collision_anti-drop/data_preprocess/dataset/whole_dataset_train_mean.binaryproto
F0928 17:49:53.488655 30253 blob.cpp:133] Check failed: data_
*** Check failure stack trace: ***
@ 0x7fc5b9e070cd google::LogMessage::Fail()
@ 0x7fc5b9e08f33 google::LogMessage::SendToLog()
@ 0x7fc5b9e06c28 google::LogMessage::Flush()
@ 0x7fc5b9e09999 google::LogMessageFatal::~LogMessageFatal()
@ 0x7fc5ba2c83db caffe::Blob<>::mutable_cpu_data()
@ 0x7fc5ba2d1db7 caffe::Blob<>::FromProto()
@ 0x7fc5ba2f7632 caffe::DataTransformer<>::DataTransformer()
@ 0x7fc5ba2239a5 caffe::BaseDataLayer<>::LayerSetUp()
@ 0x7fc5ba223abc caffe::BasePrefetchingDataLayer<>::LayerSetUp()
@ 0x7fc5ba2e6eb3 caffe::Net<>::Init()
@ 0x7fc5ba2e861e caffe::Net<>::Net()
@ 0x7fc5ba1ae0c4 caffe::Solver<>::InitTrainNet()
@ 0x7fc5ba1ae673 caffe::Solver<>::Init()
@ 0x7fc5ba1ae99f caffe::Solver<>::Solver()
@ 0x7fc5ba1940f1 caffe::Creator_AdamSolver<>()
@ 0x55b980d7aec7 (unknown)
@ 0x55b980d76f80 (unknown)
@ 0x7fc5b8413c87 __libc_start_main
@ 0x55b980d77a3a (unknown)

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