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./train.sh results got aborted (core dumped) #180

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Rheza001 opened this issue Apr 6, 2020 · 3 comments
Open

./train.sh results got aborted (core dumped) #180

Rheza001 opened this issue Apr 6, 2020 · 3 comments

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@Rheza001
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Rheza001 commented Apr 6, 2020 •
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Please help me. i'm stuck in this problem. when i tried to run ./train.sh, i got this error:

rheza@rheza-pc:~/Documents/BirdWatcher/caffe/examples/MobileNet-SSD$ ./train.sh
I0407 01:31:07.614326 5755 caffe.cpp:210] Use CPU.
I0407 01:31:07.615535 5755 solver.cpp:63] Initializing solver from parameters:
train_net: "example/MobileNetSSD_train.prototxt"
test_net: "example/MobileNetSSD_test.prototxt"
test_iter: 673
test_interval: 10000
base_lr: 0.0005
display: 10
max_iter: 120000
lr_policy: "multistep"
gamma: 0.5
weight_decay: 5e-05
snapshot: 1000
snapshot_prefix: "snapshot/mobilenet"
solver_mode: CPU
debug_info: false
train_state {
level: 0
stage: ""
}
snapshot_after_train: true
test_initialization: false
average_loss: 10
stepvalue: 20000
stepvalue: 40000
iter_size: 1
type: "RMSProp"
eval_type: "detection"
ap_version: "11point"
I0407 01:31:07.615903 5755 solver.cpp:96] Creating training net from train_net file: example/MobileNetSSD_train.prototxt
I0407 01:31:07.618894 5755 upgrade_proto.cpp:77] Attempting to upgrade batch norm layers using deprecated params: example/MobileNetSSD_train.prototxt
I0407 01:31:07.618934 5755 upgrade_proto.cpp:80] Successfully upgraded batch norm layers using deprecated params.
I0407 01:31:07.619567 5755 net.cpp:58] Initializing net from parameters:
name: "MobileNet-SSD"
state {
phase: TRAIN
level: 0
stage: ""
}
layer {
name: "data"
type: "AnnotatedData"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
scale: 0.007843
mirror: true
mean_value: 127.5
mean_value: 127.5
mean_value: 127.5
resize_param {
prob: 1
resize_mode: WARP
height: 300
width: 300
interp_mode: LINEAR
interp_mode: AREA
interp_mode: NEAREST
interp_mode: CUBIC
interp_mode: LANCZOS4
}
emit_constraint {
emit_type: CENTER
}
distort_param {
brightness_prob: 0.5
brightness_delta: 32
contrast_prob: 0.5
contrast_lower: 0.5
contrast_upper: 1.5
hue_prob: 0.5
hue_delta: 18
saturation_prob: 0.5
saturation_lower: 0.5
saturation_upper: 1.5
random_order_prob: 0
}
expand_param {
prob: 0.5
max_expand_ratio: 4
}
}
data_param {
source: "trainval_lmdb/"
batch_size: 24
backend: LMDB
}
annotated_data_param {
batch_sampler {
max_sample: 1
max_trials: 1
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
min_jaccard_overlap: 0.1
}
max_sample: 1
max_trials: 50
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
min_jaccard_overlap: 0.3
}
max_sample: 1
max_trials: 50
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
min_jaccard_overlap: 0.5
}
max_sample: 1
max_trials: 50
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
min_jaccard_overlap: 0.7
}
max_sample: 1
max_trials: 50
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
min_jaccard_overlap: 0.9
}
max_sample: 1
max_trials: 50
}
batch_sampler {
sampler {
min_scale: 0.3
max_scale: 1
min_aspect_ratio: 0.5
max_aspect_ratio: 2
}
sample_constraint {
max_jaccard_overlap: 1
}
max_sample: 1
max_trials: 50
}
label_map_file: "labelmap.prototxt"
}
}
layer {
name: "conv0"
type: "Convolution"
bottom: "data"
top: "conv0"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv0/bn"
type: "BatchNorm"
bottom: "conv0"
top: "conv0"
}
layer {
name: "conv0/scale"
type: "Scale"
bottom: "conv0"
top: "conv0"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv0/relu"
type: "ReLU"
bottom: "conv0"
top: "conv0"
}
layer {
name: "conv1/dw"
type: "Convolution"
bottom: "conv0"
top: "conv1/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
group: 32
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv1/dw/bn"
type: "BatchNorm"
bottom: "conv1/dw"
top: "conv1/dw"
}
layer {
name: "conv1/dw/scale"
type: "Scale"
bottom: "conv1/dw"
top: "conv1/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv1/dw/relu"
type: "ReLU"
bottom: "conv1/dw"
top: "conv1/dw"
}
layer {
name: "conv1"
type: "Convolution"
bottom: "conv1/dw"
top: "conv1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv1/bn"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv1/scale"
type: "Scale"
bottom: "conv1"
top: "conv1"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv1/relu"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv2/dw"
type: "Convolution"
bottom: "conv1"
top: "conv2/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
group: 64
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv2/dw/bn"
type: "BatchNorm"
bottom: "conv2/dw"
top: "conv2/dw"
}
layer {
name: "conv2/dw/scale"
type: "Scale"
bottom: "conv2/dw"
top: "conv2/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv2/dw/relu"
type: "ReLU"
bottom: "conv2/dw"
top: "conv2/dw"
}
layer {
name: "conv2"
type: "Convolution"
bottom: "conv2/dw"
top: "conv2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2/bn"
type: "BatchNorm"
bottom: "conv2"
top: "conv2"
}
layer {
name: "conv2/scale"
type: "Scale"
bottom: "conv2"
top: "conv2"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv2/relu"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "conv3/dw"
type: "Convolution"
bottom: "conv2"
top: "conv3/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv3/dw/bn"
type: "BatchNorm"
bottom: "conv3/dw"
top: "conv3/dw"
}
layer {
name: "conv3/dw/scale"
type: "Scale"
bottom: "conv3/dw"
top: "conv3/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv3/dw/relu"
type: "ReLU"
bottom: "conv3/dw"
top: "conv3/dw"
}
layer {
name: "conv3"
type: "Convolution"
bottom: "conv3/dw"
top: "conv3"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3/bn"
type: "BatchNorm"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv3/scale"
type: "Scale"
bottom: "conv3"
top: "conv3"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv3/relu"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4/dw"
type: "Convolution"
bottom: "conv3"
top: "conv4/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4/dw/bn"
type: "BatchNorm"
bottom: "conv4/dw"
top: "conv4/dw"
}
layer {
name: "conv4/dw/scale"
type: "Scale"
bottom: "conv4/dw"
top: "conv4/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv4/dw/relu"
type: "ReLU"
bottom: "conv4/dw"
top: "conv4/dw"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv4/dw"
top: "conv4"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4/bn"
type: "BatchNorm"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv4/scale"
type: "Scale"
bottom: "conv4"
top: "conv4"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv4/relu"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5/dw"
type: "Convolution"
bottom: "conv4"
top: "conv5/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv5/dw/bn"
type: "BatchNorm"
bottom: "conv5/dw"
top: "conv5/dw"
}
layer {
name: "conv5/dw/scale"
type: "Scale"
bottom: "conv5/dw"
top: "conv5/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv5/dw/relu"
type: "ReLU"
bottom: "conv5/dw"
top: "conv5/dw"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv5/dw"
top: "conv5"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5/bn"
type: "BatchNorm"
bottom: "conv5"
top: "conv5"
}
layer {
name: "conv5/scale"
type: "Scale"
bottom: "conv5"
top: "conv5"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv5/relu"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "conv6/dw"
type: "Convolution"
bottom: "conv5"
top: "conv6/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv6/dw/bn"
type: "BatchNorm"
bottom: "conv6/dw"
top: "conv6/dw"
}
layer {
name: "conv6/dw/scale"
type: "Scale"
bottom: "conv6/dw"
top: "conv6/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv6/dw/relu"
type: "ReLU"
bottom: "conv6/dw"
top: "conv6/dw"
}
layer {
name: "conv6"
type: "Convolution"
bottom: "conv6/dw"
top: "conv6"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6/bn"
type: "BatchNorm"
bottom: "conv6"
top: "conv6"
}
layer {
name: "conv6/scale"
type: "Scale"
bottom: "conv6"
top: "conv6"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv6/relu"
type: "ReLU"
bottom: "conv6"
top: "conv6"
}
layer {
name: "conv7/dw"
type: "Convolution"
bottom: "conv6"
top: "conv7/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv7/dw/bn"
type: "BatchNorm"
bottom: "conv7/dw"
top: "conv7/dw"
}
layer {
name: "conv7/dw/scale"
type: "Scale"
bottom: "conv7/dw"
top: "conv7/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv7/dw/relu"
type: "ReLU"
bottom: "conv7/dw"
top: "conv7/dw"
}
layer {
name: "conv7"
type: "Convolution"
bottom: "conv7/dw"
top: "conv7"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv7/bn"
type: "BatchNorm"
bottom: "conv7"
top: "conv7"
}
layer {
name: "conv7/scale"
type: "Scale"
bottom: "conv7"
top: "conv7"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv7/relu"
type: "ReLU"
bottom: "conv7"
top: "conv7"
}
layer {
name: "conv8/dw"
type: "Convolution"
bottom: "conv7"
top: "conv8/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv8/dw/bn"
type: "BatchNorm"
bottom: "conv8/dw"
top: "conv8/dw"
}
layer {
name: "conv8/dw/scale"
type: "Scale"
bottom: "conv8/dw"
top: "conv8/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv8/dw/relu"
type: "ReLU"
bottom: "conv8/dw"
top: "conv8/dw"
}
layer {
name: "conv8"
type: "Convolution"
bottom: "conv8/dw"
top: "conv8"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv8/bn"
type: "BatchNorm"
bottom: "conv8"
top: "conv8"
}
layer {
name: "conv8/scale"
type: "Scale"
bottom: "conv8"
top: "conv8"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv8/relu"
type: "ReLU"
bottom: "conv8"
top: "conv8"
}
layer {
name: "conv9/dw"
type: "Convolution"
bottom: "conv8"
top: "conv9/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv9/dw/bn"
type: "BatchNorm"
bottom: "conv9/dw"
top: "conv9/dw"
}
layer {
name: "conv9/dw/scale"
type: "Scale"
bottom: "conv9/dw"
top: "conv9/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv9/dw/relu"
type: "ReLU"
bottom: "conv9/dw"
top: "conv9/dw"
}
layer {
name: "conv9"
type: "Convolution"
bottom: "conv9/dw"
top: "conv9"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv9/bn"
type: "BatchNorm"
bottom: "conv9"
top: "conv9"
}
layer {
name: "conv9/scale"
type: "Scale"
bottom: "conv9"
top: "conv9"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv9/relu"
type: "ReLU"
bottom: "conv9"
top: "conv9"
}
layer {
name: "conv10/dw"
type: "Convolution"
bottom: "conv9"
top: "conv10/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv10/dw/bn"
type: "BatchNorm"
bottom: "conv10/dw"
top: "conv10/dw"
}
layer {
name: "conv10/dw/scale"
type: "Scale"
bottom: "conv10/dw"
top: "conv10/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv10/dw/relu"
type: "ReLU"
bottom: "conv10/dw"
top: "conv10/dw"
}
layer {
name: "conv10"
type: "Convolution"
bottom: "conv10/dw"
top: "conv10"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv10/bn"
type: "BatchNorm"
bottom: "conv10"
top: "conv10"
}
layer {
name: "conv10/scale"
type: "Scale"
bottom: "conv10"
top: "conv10"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv10/relu"
type: "ReLU"
bottom: "conv10"
top: "conv10"
}
layer {
name: "conv11/dw"
type: "Convolution"
bottom: "conv10"
top: "conv11/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv11/dw/bn"
type: "BatchNorm"
bottom: "conv11/dw"
top: "conv11/dw"
}
layer {
name: "conv11/dw/scale"
type: "Scale"
bottom: "conv11/dw"
top: "conv11/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv11/dw/relu"
type: "ReLU"
bottom: "conv11/dw"
top: "conv11/dw"
}
layer {
name: "conv11"
type: "Convolution"
bottom: "conv11/dw"
top: "conv11"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv11/bn"
type: "BatchNorm"
bottom: "conv11"
top: "conv11"
}
layer {
name: "conv11/scale"
type: "Scale"
bottom: "conv11"
top: "conv11"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv11/relu"
type: "ReLU"
bottom: "conv11"
top: "conv11"
}
layer {
name: "conv12/dw"
type: "Convolution"
bottom: "conv11"
top: "conv12/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv12/dw/bn"
type: "BatchNorm"
bottom: "conv12/dw"
top: "conv12/dw"
}
layer {
name: "conv12/dw/scale"
type: "Scale"
bottom: "conv12/dw"
top: "conv12/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv12/dw/relu"
type: "ReLU"
bottom: "conv12/dw"
top: "conv12/dw"
}
layer {
name: "conv12"
type: "Convolution"
bottom: "conv12/dw"
top: "conv12"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv12/bn"
type: "BatchNorm"
bottom: "conv12"
top: "conv12"
}
layer {
name: "conv12/scale"
type: "Scale"
bottom: "conv12"
top: "conv12"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv12/relu"
type: "ReLU"
bottom: "conv12"
top: "conv12"
}
layer {
name: "conv13/dw"
type: "Convolution"
bottom: "conv12"
top: "conv13/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 1
kernel_size: 3
group: 1024
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv13/dw/bn"
type: "BatchNorm"
bottom: "conv13/dw"
top: "conv13/dw"
}
layer {
name: "conv13/dw/scale"
type: "Scale"
bottom: "conv13/dw"
top: "conv13/dw"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv13/dw/relu"
type: "ReLU"
bottom: "conv13/dw"
top: "conv13/dw"
}
layer {
name: "conv13"
type: "Convolution"
bottom: "conv13/dw"
top: "conv13"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv13/bn"
type: "BatchNorm"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv13/scale"
type: "Scale"
bottom: "conv13"
top: "conv13"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv13/relu"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv14_1"
type: "Convolution"
bottom: "conv13"
top: "conv14_1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv14_1/bn"
type: "BatchNorm"
bottom: "conv14_1"
top: "conv14_1"
}
layer {
name: "conv14_1/scale"
type: "Scale"
bottom: "conv14_1"
top: "conv14_1"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv14_1/relu"
type: "ReLU"
bottom: "conv14_1"
top: "conv14_1"
}
layer {
name: "conv14_2"
type: "Convolution"
bottom: "conv14_1"
top: "conv14_2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv14_2/bn"
type: "BatchNorm"
bottom: "conv14_2"
top: "conv14_2"
}
layer {
name: "conv14_2/scale"
type: "Scale"
bottom: "conv14_2"
top: "conv14_2"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv14_2/relu"
type: "ReLU"
bottom: "conv14_2"
top: "conv14_2"
}
layer {
name: "conv15_1"
type: "Convolution"
bottom: "conv14_2"
top: "conv15_1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15_1/bn"
type: "BatchNorm"
bottom: "conv15_1"
top: "conv15_1"
}
layer {
name: "conv15_1/scale"
type: "Scale"
bottom: "conv15_1"
top: "conv15_1"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15_1/relu"
type: "ReLU"
bottom: "conv15_1"
top: "conv15_1"
}
layer {
name: "conv15_2"
type: "Convolution"
bottom: "conv15_1"
top: "conv15_2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15_2/bn"
type: "BatchNorm"
bottom: "conv15_2"
top: "conv15_2"
}
layer {
name: "conv15_2/scale"
type: "Scale"
bottom: "conv15_2"
top: "conv15_2"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15_2/relu"
type: "ReLU"
bottom: "conv15_2"
top: "conv15_2"
}
layer {
name: "conv16_1"
type: "Convolution"
bottom: "conv15_2"
top: "conv16_1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16_1/bn"
type: "BatchNorm"
bottom: "conv16_1"
top: "conv16_1"
}
layer {
name: "conv16_1/scale"
type: "Scale"
bottom: "conv16_1"
top: "conv16_1"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16_1/relu"
type: "ReLU"
bottom: "conv16_1"
top: "conv16_1"
}
layer {
name: "conv16_2"
type: "Convolution"
bottom: "conv16_1"
top: "conv16_2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16_2/bn"
type: "BatchNorm"
bottom: "conv16_2"
top: "conv16_2"
}
layer {
name: "conv16_2/scale"
type: "Scale"
bottom: "conv16_2"
top: "conv16_2"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16_2/relu"
type: "ReLU"
bottom: "conv16_2"
top: "conv16_2"
}
layer {
name: "conv17_1"
type: "Convolution"
bottom: "conv16_2"
top: "conv17_1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17_1/bn"
type: "BatchNorm"
bottom: "conv17_1"
top: "conv17_1"
}
layer {
name: "conv17_1/scale"
type: "Scale"
bottom: "conv17_1"
top: "conv17_1"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17_1/relu"
type: "ReLU"
bottom: "conv17_1"
top: "conv17_1"
}
layer {
name: "conv17_2"
type: "Convolution"
bottom: "conv17_1"
top: "conv17_2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17_2/bn"
type: "BatchNorm"
bottom: "conv17_2"
top: "conv17_2"
}
layer {
name: "conv17_2/scale"
type: "Scale"
bottom: "conv17_2"
top: "conv17_2"
param {
lr_mult: 0.1
decay_mult: 0
}
param {
lr_mult: 0.2
decay_mult: 0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17_2/relu"
type: "ReLU"
bottom: "conv17_2"
top: "conv17_2"
}
layer {
name: "conv11_mbox_loc"
type: "Convolution"
bottom: "conv11"
top: "conv11_mbox_loc"
param {
lr_mult: 0.1
decay_mult: 0.1
}
param {
lr_mult: 0.2
decay_mult: 0
}
convolution_param {
num_output: 12
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv11_mbox_loc_perm"
type: "Permute"
bottom: "conv11_mbox_loc"
top: "conv11_mbox_loc_perm"
permute_param {
order: 0
or
I0407 01:31:07.624553 5755 layer_factory.hpp:77] Creating layer data
I0407 01:31:07.624944 5755 net.cpp:100] Creating Layer data
I0407 01:31:07.624984 5755 net.cpp:408] data -> data
I0407 01:31:07.625072 5755 net.cpp:408] data -> label
I0407 01:31:07.625355 5758 db_lmdb.cpp:35] Opened lmdb trainval_lmdb/
I0407 01:31:07.631899 5755 annotated_data_layer.cpp:62] output data size: 24,3,300,300
I0407 01:31:07.632081 5755 net.cpp:150] Setting up data
I0407 01:31:07.632103 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632130 5755 net.cpp:157] Top shape: 1 1 1 8 (8)
I0407 01:31:07.632141 5755 net.cpp:165] Memory required for data: 25920032
I0407 01:31:07.632176 5755 layer_factory.hpp:77] Creating layer data_data_0_split
I0407 01:31:07.632277 5755 net.cpp:100] Creating Layer data_data_0_split
I0407 01:31:07.632299 5755 net.cpp:434] data_data_0_split <- data
I0407 01:31:07.632333 5755 net.cpp:408] data_data_0_split -> data_data_0_split_0
I0407 01:31:07.632370 5755 net.cpp:408] data_data_0_split -> data_data_0_split_1
I0407 01:31:07.632392 5755 net.cpp:408] data_data_0_split -> data_data_0_split_2
I0407 01:31:07.632414 5755 net.cpp:408] data_data_0_split -> data_data_0_split_3
I0407 01:31:07.632437 5755 net.cpp:408] data_data_0_split -> data_data_0_split_4
I0407 01:31:07.632462 5755 net.cpp:408] data_data_0_split -> data_data_0_split_5
I0407 01:31:07.632474 5755 net.cpp:408] data_data_0_split -> data_data_0_split_6
I0407 01:31:07.632503 5755 net.cpp:150] Setting up data_data_0_split
I0407 01:31:07.632553 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632575 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632604 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632701 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632715 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632732 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632766 5755 net.cpp:157] Top shape: 24 3 300 300 (6480000)
I0407 01:31:07.632786 5755 net.cpp:165] Memory required for data: 207360032
I0407 01:31:07.632805 5755 layer_factory.hpp:77] Creating layer conv0
I0407 01:31:07.632861 5755 net.cpp:100] Creating Layer conv0
I0407 01:31:07.632880 5755 net.cpp:434] conv0 <- data_data_0_split_0
I0407 01:31:07.632901 5755 net.cpp:408] conv0 -> conv0
I0407 01:31:07.633342 5755 net.cpp:150] Setting up conv0
I0407 01:31:07.633366 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.633389 5755 net.cpp:165] Memory required for data: 276480032
I0407 01:31:07.633430 5755 layer_factory.hpp:77] Creating layer conv0/bn
I0407 01:31:07.633461 5755 net.cpp:100] Creating Layer conv0/bn
I0407 01:31:07.633479 5755 net.cpp:434] conv0/bn <- conv0
I0407 01:31:07.633499 5755 net.cpp:395] conv0/bn -> conv0 (in-place)
I0407 01:31:07.633626 5755 net.cpp:150] Setting up conv0/bn
I0407 01:31:07.633653 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.633674 5755 net.cpp:165] Memory required for data: 345600032
I0407 01:31:07.633699 5755 layer_factory.hpp:77] Creating layer conv0/scale
I0407 01:31:07.633725 5755 net.cpp:100] Creating Layer conv0/scale
I0407 01:31:07.633750 5755 net.cpp:434] conv0/scale <- conv0
I0407 01:31:07.633770 5755 net.cpp:395] conv0/scale -> conv0 (in-place)
I0407 01:31:07.633805 5755 layer_factory.hpp:77] Creating layer conv0/scale
I0407 01:31:07.634006 5755 net.cpp:150] Setting up conv0/scale
I0407 01:31:07.634032 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.634052 5755 net.cpp:165] Memory required for data: 414720032
I0407 01:31:07.634075 5755 layer_factory.hpp:77] Creating layer conv0/relu
I0407 01:31:07.634095 5755 net.cpp:100] Creating Layer conv0/relu
I0407 01:31:07.634112 5755 net.cpp:434] conv0/relu <- conv0
I0407 01:31:07.634177 5755 net.cpp:395] conv0/relu -> conv0 (in-place)
I0407 01:31:07.634208 5755 net.cpp:150] Setting up conv0/relu
I0407 01:31:07.634235 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.634255 5755 net.cpp:165] Memory required for data: 483840032
I0407 01:31:07.634274 5755 layer_factory.hpp:77] Creating layer conv1/dw
I0407 01:31:07.634295 5755 net.cpp:100] Creating Layer conv1/dw
I0407 01:31:07.634312 5755 net.cpp:434] conv1/dw <- conv0
I0407 01:31:07.634346 5755 net.cpp:408] conv1/dw -> conv1/dw
I0407 01:31:07.634388 5755 net.cpp:150] Setting up conv1/dw
I0407 01:31:07.634407 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.634435 5755 net.cpp:165] Memory required for data: 552960032
I0407 01:31:07.634454 5755 layer_factory.hpp:77] Creating layer conv1/dw/bn
I0407 01:31:07.634479 5755 net.cpp:100] Creating Layer conv1/dw/bn
I0407 01:31:07.634496 5755 net.cpp:434] conv1/dw/bn <- conv1/dw
I0407 01:31:07.634526 5755 net.cpp:395] conv1/dw/bn -> conv1/dw (in-place)
I0407 01:31:07.634642 5755 net.cpp:150] Setting up conv1/dw/bn
I0407 01:31:07.634660 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.634680 5755 net.cpp:165] Memory required for data: 622080032
I0407 01:31:07.634704 5755 layer_factory.hpp:77] Creating layer conv1/dw/scale
I0407 01:31:07.634733 5755 net.cpp:100] Creating Layer conv1/dw/scale
I0407 01:31:07.634752 5755 net.cpp:434] conv1/dw/scale <- conv1/dw
I0407 01:31:07.634771 5755 net.cpp:395] conv1/dw/scale -> conv1/dw (in-place)
I0407 01:31:07.634796 5755 layer_factory.hpp:77] Creating layer conv1/dw/scale
I0407 01:31:07.635004 5755 net.cpp:150] Setting up conv1/dw/scale
I0407 01:31:07.635033 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.635056 5755 net.cpp:165] Memory required for data: 691200032
I0407 01:31:07.635079 5755 layer_factory.hpp:77] Creating layer conv1/dw/relu
I0407 01:31:07.635362 5755 net.cpp:100] Creating Layer conv1/dw/relu
I0407 01:31:07.635430 5755 net.cpp:434] conv1/dw/relu <- conv1/dw
I0407 01:31:07.635452 5755 net.cpp:395] conv1/dw/relu -> conv1/dw (in-place)
I0407 01:31:07.635473 5755 net.cpp:150] Setting up conv1/dw/relu
I0407 01:31:07.635489 5755 net.cpp:157] Top shape: 24 32 150 150 (17280000)
I0407 01:31:07.635519 5755 net.cpp:165] Memory required for data: 760320032
I0407 01:31:07.635535 5755 layer_factory.hpp:77] Creating layer conv1
I0407 01:31:07.635557 5755 net.cpp:100] Creating Layer conv1
I0407 01:31:07.635576 5755 net.cpp:434] conv1 <- conv1/dw
I0407 01:31:07.635604 5755 net.cpp:408] conv1 -> conv1
I0407 01:31:07.635674 5755 net.cpp:150] Setting up conv1
I0407 01:31:07.635692 5755 net.cpp:157] Top shape: 24 64 150 150 (34560000)
I0407 01:31:07.635722 5755 net.cpp:165] Memory required for data: 898560032
I0407 01:31:07.635741 5755 layer_factory.hpp:77] Creating layer conv1/bn
I0407 01:31:07.635761 5755 net.cpp:100] Creating Layer conv1/bn
I0407 01:31:07.635778 5755 net.cpp:434] conv1/bn <- conv1
I0407 01:31:07.635809 5755 net.cpp:395] conv1/bn -> conv1 (in-place)
I0407 01:31:07.635932 5755 net.cpp:150] Setting up conv1/bn
I0407 01:31:07.635951 5755 net.cpp:157] Top shape: 24 64 150 150 (34560000)
I0407 01:31:07.635970 5755 net.cpp:165] Memory required for data: 1036800032
I0407 01:31:07.636008 5755 layer_factory.hpp:77] Creating layer conv1/scale
I0407 01:31:07.636029 5755 net.cpp:100] Creating Layer conv1/scale
I0407 01:31:07.636047 5755 net.cpp:434] conv1/scale <- conv1
I0407 01:31:07.636067 5755 net.cpp:395] conv1/scale -> conv1 (in-place)
I0407 01:31:07.636101 5755 layer_factory.hpp:77] Creating layer conv1/scale
I0407 01:31:07.636330 5755 net.cpp:150] Setting up conv1/scale
I0407 01:31:07.636350 5755 net.cpp:157] Top shape: 24 64 150 150 (34560000)
I0407 01:31:07.636369 5755 net.cpp:165] Memory required for data: 1175040032
I0407 01:31:07.636404 5755 layer_factory.hpp:77] Creating layer conv1/relu
I0407 01:31:07.636426 5755 net.cpp:100] Creating Layer conv1/relu
I0407 01:31:07.636443 5755 net.cpp:434] conv1/relu <- conv1
I0407 01:31:07.636464 5755 net.cpp:395] conv1/relu -> conv1 (in-place)
I0407 01:31:07.636492 5755 net.cpp:150] Setting up conv1/relu
I0407 01:31:07.636508 5755 net.cpp:157] Top shape: 24 64 150 150 (34560000)
I0407 01:31:07.636528 5755 net.cpp:165] Memory required for data: 1313280032
I0407 01:31:07.636544 5755 layer_factory.hpp:77] Creating layer conv2/dw
I0407 01:31:07.636566 5755 net.cpp:100] Creating Layer conv2/dw
I0407 01:31:07.636591 5755 net.cpp:434] conv2/dw <- conv1
I0407 01:31:07.636611 5755 net.cpp:408] conv2/dw -> conv2/dw
I0407 01:31:07.636660 5755 net.cpp:150] Setting up conv2/dw
I0407 01:31:07.636685 5755 net.cpp:157] Top shape: 24 64 75 75 (8640000)
I0407 01:31:07.636705 5755 net.cpp:165] Memory required for data: 1347840032
I0407 01:31:07.636724 5755 layer_factory.hpp:77] Creating layer conv2/dw/bn
I0407 01:31:07.636744 5755 net.cpp:100] Creating Layer conv2/dw/bn
I0407 01:31:07.636760 5755 net.cpp:434] conv2/dw/bn <- conv2/dw
I0407 01:31:07.636787 5755 net.cpp:395] conv2/dw/bn -> conv2/dw (in-place)
I0407 01:31:07.636843 5755 net.cpp:150] Setting up conv2/dw/bn
I0407 01:31:07.636862 5755 net.cpp:157] Top shape: 24 64 75 75 (8640000)
I0407 01:31:07.636888 5755 net.cpp:165] Memory required for data: 1382400032
I0407 01:31:07.636911 5755 layer_factory.hpp:77] Creating layer conv2/dw/scale
I0407 01:31:07.636934 5755 net.cpp:100] Creating Layer conv2/dw/scale
I0407 01:31:07.636952 5755 net.cpp:434] conv2/dw/scale <- conv2/dw
I0407 01:31:07.636983 5755 net.cpp:395] conv2/dw/scale -> conv2/dw (in-place)
I0407 01:31:07.637008 5755 layer_factory.hpp:77] Creating layer conv2/dw/scale
I0407 01:31:07.637078 5755 net.cpp:150] Setting up conv2/dw/scale
I0407 01:31:07.637095 5755 net.cpp:157] Top shape: 24 64 75 75 (8640000)
I0407 01:31:07.637115 5755 net.cpp:165] Memory required for data: 1416960032
I0407 01:31:07.637136 5755 layer_factory.hpp:77] Creating layer conv2/dw/relu
I0407 01:31:07.637158 5755 net.cpp:100] Creating Layer conv2/dw/relu
I0407 01:31:07.637199 5755 net.cpp:434] conv2/dw/relu <- conv2/dw
I0407 01:31:07.637219 5755 net.cpp:395] conv2/dw/relu -> conv2/dw (in-place)
I0407 01:31:07.637238 5755 net.cpp:150] Setting up conv2/dw/relu
I0407 01:31:07.637253 5755 net.cpp:157] Top shape: 24 64 75 75 (8640000)
I0407 01:31:07.637281 5755 net.cpp:165] Memory required for data: 1451520032
I0407 01:31:07.637298 5755 layer_factory.hpp:77] Creating layer conv2
I0407 01:31:07.637328 5755 net.cpp:100] Creating Layer conv2
I0407 01:31:07.637346 5755 net.cpp:434] conv2 <- conv2/dw
I0407 01:31:07.637374 5755 net.cpp:408] conv2 -> conv2
I0407 01:31:07.637590 5755 net.cpp:150] Setting up conv2
I0407 01:31:07.637609 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.637629 5755 net.cpp:165] Memory required for data: 1520640032
I0407 01:31:07.637648 5755 layer_factory.hpp:77] Creating layer conv2/bn
I0407 01:31:07.637676 5755 net.cpp:100] Creating Layer conv2/bn
I0407 01:31:07.637694 5755 net.cpp:434] conv2/bn <- conv2
I0407 01:31:07.637712 5755 net.cpp:395] conv2/bn -> conv2 (in-place)
I0407 01:31:07.637782 5755 net.cpp:150] Setting up conv2/bn
I0407 01:31:07.637799 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.637820 5755 net.cpp:165] Memory required for data: 1589760032
I0407 01:31:07.637841 5755 layer_factory.hpp:77] Creating layer conv2/scale
I0407 01:31:07.637869 5755 net.cpp:100] Creating Layer conv2/scale
I0407 01:31:07.637887 5755 net.cpp:434] conv2/scale <- conv2
I0407 01:31:07.637907 5755 net.cpp:395] conv2/scale -> conv2 (in-place)
I0407 01:31:07.637930 5755 layer_factory.hpp:77] Creating layer conv2/scale
I0407 01:31:07.638006 5755 net.cpp:150] Setting up conv2/scale
I0407 01:31:07.638025 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.638042 5755 net.cpp:165] Memory required for data: 1658880032
I0407 01:31:07.638072 5755 layer_factory.hpp:77] Creating layer conv2/relu
I0407 01:31:07.638098 5755 net.cpp:100] Creating Layer conv2/relu
I0407 01:31:07.638115 5755 net.cpp:434] conv2/relu <- conv2
I0407 01:31:07.638134 5755 net.cpp:395] conv2/relu -> conv2 (in-place)
I0407 01:31:07.638204 5755 net.cpp:150] Setting up conv2/relu
I0407 01:31:07.638226 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.638245 5755 net.cpp:165] Memory required for data: 1728000032
I0407 01:31:07.638270 5755 layer_factory.hpp:77] Creating layer conv3/dw
I0407 01:31:07.638293 5755 net.cpp:100] Creating Layer conv3/dw
I0407 01:31:07.638309 5755 net.cpp:434] conv3/dw <- conv2
I0407 01:31:07.638329 5755 net.cpp:408] conv3/dw -> conv3/dw
I0407 01:31:07.638392 5755 net.cpp:150] Setting up conv3/dw
I0407 01:31:07.638411 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.638432 5755 net.cpp:165] Memory required for data: 1797120032
I0407 01:31:07.638458 5755 layer_factory.hpp:77] Creating layer conv3/dw/bn
I0407 01:31:07.638480 5755 net.cpp:100] Creating Layer conv3/dw/bn
I0407 01:31:07.638499 5755 net.cpp:434] conv3/dw/bn <- conv3/dw
I0407 01:31:07.638516 5755 net.cpp:395] conv3/dw/bn -> conv3/dw (in-place)
I0407 01:31:07.638576 5755 net.cpp:150] Setting up conv3/dw/bn
I0407 01:31:07.638592 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.638610 5755 net.cpp:165] Memory required for data: 1866240032
I0407 01:31:07.638638 5755 layer_factory.hpp:77] Creating layer conv3/dw/scale
I0407 01:31:07.638667 5755 net.cpp:100] Creating Layer conv3/dw/scale
I0407 01:31:07.638684 5755 net.cpp:434] conv3/dw/scale <- conv3/dw
I0407 01:31:07.638705 5755 net.cpp:395] conv3/dw/scale -> conv3/dw (in-place)
I0407 01:31:07.638732 5755 layer_factory.hpp:77] Creating layer conv3/dw/scale
I0407 01:31:07.638808 5755 net.cpp:150] Setting up conv3/dw/scale
I0407 01:31:07.638825 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.638854 5755 net.cpp:165] Memory required for data: 1935360032
I0407 01:31:07.638877 5755 layer_factory.hpp:77] Creating layer conv3/dw/relu
I0407 01:31:07.639402 5755 net.cpp:100] Creating Layer conv3/dw/relu
I0407 01:31:07.639454 5755 net.cpp:434] conv3/dw/relu <- conv3/dw
I0407 01:31:07.639475 5755 net.cpp:395] conv3/dw/relu -> conv3/dw (in-place)
I0407 01:31:07.639497 5755 net.cpp:150] Setting up conv3/dw/relu
I0407 01:31:07.639513 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.639541 5755 net.cpp:165] Memory required for data: 2004480032
I0407 01:31:07.639559 5755 layer_factory.hpp:77] Creating layer conv3
I0407 01:31:07.639580 5755 net.cpp:100] Creating Layer conv3
I0407 01:31:07.639597 5755 net.cpp:434] conv3 <- conv3/dw
I0407 01:31:07.639616 5755 net.cpp:408] conv3 -> conv3
I0407 01:31:07.640012 5755 net.cpp:150] Setting up conv3
I0407 01:31:07.640041 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.640063 5755 net.cpp:165] Memory required for data: 2073600032
I0407 01:31:07.640082 5755 layer_factory.hpp:77] Creating layer conv3/bn
I0407 01:31:07.640101 5755 net.cpp:100] Creating Layer conv3/bn
I0407 01:31:07.640118 5755 net.cpp:434] conv3/bn <- conv3
I0407 01:31:07.640146 5755 net.cpp:395] conv3/bn -> conv3 (in-place)
I0407 01:31:07.640205 5755 net.cpp:150] Setting up conv3/bn
I0407 01:31:07.640229 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.640249 5755 net.cpp:165] Memory required for data: 2142720032
I0407 01:31:07.640271 5755 layer_factory.hpp:77] Creating layer conv3/scale
I0407 01:31:07.640292 5755 net.cpp:100] Creating Layer conv3/scale
I0407 01:31:07.640309 5755 net.cpp:434] conv3/scale <- conv3
I0407 01:31:07.640928 5755 net.cpp:395] conv3/scale -> conv3 (in-place)
I0407 01:31:07.640964 5755 layer_factory.hpp:77] Creating layer conv3/scale
I0407 01:31:07.641057 5755 net.cpp:150] Setting up conv3/scale
I0407 01:31:07.641077 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.641098 5755 net.cpp:165] Memory required for data: 2211840032
I0407 01:31:07.641126 5755 layer_factory.hpp:77] Creating layer conv3/relu
I0407 01:31:07.641151 5755 net.cpp:100] Creating Layer conv3/relu
I0407 01:31:07.641168 5755 net.cpp:434] conv3/relu <- conv3
I0407 01:31:07.641187 5755 net.cpp:395] conv3/relu -> conv3 (in-place)
I0407 01:31:07.641216 5755 net.cpp:150] Setting up conv3/relu
I0407 01:31:07.641232 5755 net.cpp:157] Top shape: 24 128 75 75 (17280000)
I0407 01:31:07.641252 5755 net.cpp:165] Memory required for data: 2280960032
I0407 01:31:07.641268 5755 layer_factory.hpp:77] Creating layer conv4/dw
I0407 01:31:07.641290 5755 net.cpp:100] Creating Layer conv4/dw
I0407 01:31:07.641315 5755 net.cpp:434] conv4/dw <- conv3
I0407 01:31:07.641335 5755 net.cpp:408] conv4/dw -> conv4/dw
I0407 01:31:07.641422 5755 net.cpp:150] Setting up conv4/dw
I0407 01:31:07.641443 5755 net.cpp:157] Top shape: 24 128 38 38 (4435968)
I0407 01:31:07.641465 5755 net.cpp:165] Memory required for data: 2298703904
I0407 01:31:07.641487 5755 layer_factory.hpp:77] Creating layer conv4/dw/bn
I0407 01:31:07.641516 5755 net.cpp:100] Creating Layer conv4/dw/bn
I0407 01:31:07.641533 5755 net.cpp:434] conv4/dw/bn <- conv4/dw
I0407 01:31:07.641552 5755 net.cpp:395] conv4/dw/bn -> conv4/dw (in-place)
I0407 01:31:07.641609 5755 net.cpp:150] Setting up conv4/dw/bn
I0407 01:31:07.641629 5755 net.cpp:157] Top shape: 24 128 38 38 (4435968)
I0407 01:31:07.641649 5755 net.cpp:165] Memory required for data: 2316447776
I0407 01:31:07.641670 5755 layer_factory.hpp:77] Creating layer conv4/dw/scale
I0407 01:31:07.641708 5755 net.cpp:100] Creating Layer conv4/dw/scale
I0407 01:31:07.641726 5755 net.cpp:434] conv4/dw/scale <- conv4/dw
I0407 01:31:07.641746 5755 net.cpp:395] conv4/dw/scale -> conv4/dw (in-place)
I0407 01:31:07.641774 5755 layer_factory.hpp:77] Creating layer conv4/dw/scale
I0407 01:31:07.641820 5755 net.cpp:150] Setting up conv4/dw/scale
I0407 01:31:07.641839 5755 net.cpp:157] Top shape: 24 128 38 38 (4435968)
I0407 01:31:07.641857 5755 net.cpp:165] Memory required for data: 2334191648
I0407 01:31:07.641877 5755 layer_factory.hpp:77] Creating layer conv4/dw/relu
I0407 01:31:07.641911 5755 net.cpp:100] Creating Layer conv4/dw/relu
I0407 01:31:07.641950 5755 net.cpp:434] conv4/dw/relu <- conv4/dw
I0407 01:31:07.641971 5755 net.cpp:395] conv4/dw/relu -> conv4/dw (in-place)
I0407 01:31:07.642050 5755 net.cpp:150] Setting up conv4/dw/relu
I0407 01:31:07.642069 5755 net.cpp:157] Top shape: 24 128 38 38 (4435968)
I0407 01:31:07.642120 5755 net.cpp:165] Memory required for data: 2351935520
I0407 01:31:07.642138 5755 layer_factory.hpp:77] Creating layer conv4
I0407 01:31:07.642164 5755 net.cpp:100] Creating Layer conv4
I0407 01:31:07.642182 5755 net.cpp:434] conv4 <- conv4/dw
I0407 01:31:07.642211 5755 net.cpp:408] conv4 -> conv4
I0407 01:31:07.643013 5755 net.cpp:150] Setting up conv4
I0407 01:31:07.643065 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.643107 5755 net.cpp:165] Memory required for data: 2387423264
I0407 01:31:07.643232 5755 layer_factory.hpp:77] Creating layer conv4/bn
I0407 01:31:07.643265 5755 net.cpp:100] Creating Layer conv4/bn
I0407 01:31:07.643294 5755 net.cpp:434] conv4/bn <- conv4
I0407 01:31:07.643316 5755 net.cpp:395] conv4/bn -> conv4 (in-place)
I0407 01:31:07.643359 5755 net.cpp:150] Setting up conv4/bn
I0407 01:31:07.643386 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.643409 5755 net.cpp:165] Memory required for data: 2422911008
I0407 01:31:07.643435 5755 layer_factory.hpp:77] Creating layer conv4/scale
I0407 01:31:07.643471 5755 net.cpp:100] Creating Layer conv4/scale
I0407 01:31:07.643491 5755 net.cpp:434] conv4/scale <- conv4
I0407 01:31:07.643510 5755 net.cpp:395] conv4/scale -> conv4 (in-place)
I0407 01:31:07.643538 5755 layer_factory.hpp:77] Creating layer conv4/scale
I0407 01:31:07.643596 5755 net.cpp:150] Setting up conv4/scale
I0407 01:31:07.643615 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.643633 5755 net.cpp:165] Memory required for data: 2458398752
I0407 01:31:07.643653 5755 layer_factory.hpp:77] Creating layer conv4/relu
I0407 01:31:07.643683 5755 net.cpp:100] Creating Layer conv4/relu
I0407 01:31:07.643702 5755 net.cpp:434] conv4/relu <- conv4
I0407 01:31:07.643720 5755 net.cpp:395] conv4/relu -> conv4 (in-place)
I0407 01:31:07.643741 5755 net.cpp:150] Setting up conv4/relu
I0407 01:31:07.643765 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.643785 5755 net.cpp:165] Memory required for data: 2493886496
I0407 01:31:07.643803 5755 layer_factory.hpp:77] Creating layer conv5/dw
I0407 01:31:07.643829 5755 net.cpp:100] Creating Layer conv5/dw
I0407 01:31:07.643847 5755 net.cpp:434] conv5/dw <- conv4
I0407 01:31:07.643877 5755 net.cpp:408] conv5/dw -> conv5/dw
I0407 01:31:07.643972 5755 net.cpp:150] Setting up conv5/dw
I0407 01:31:07.643991 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.644011 5755 net.cpp:165] Memory required for data: 2529374240
I0407 01:31:07.644029 5755 layer_factory.hpp:77] Creating layer conv5/dw/bn
I0407 01:31:07.644052 5755 net.cpp:100] Creating Layer conv5/dw/bn
I0407 01:31:07.644078 5755 net.cpp:434] conv5/dw/bn <- conv5/dw
I0407 01:31:07.644098 5755 net.cpp:395] conv5/dw/bn -> conv5/dw (in-place)
I0407 01:31:07.644132 5755 net.cpp:150] Setting up conv5/dw/bn
I0407 01:31:07.644150 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.644177 5755 net.cpp:165] Memory required for data: 2564861984
I0407 01:31:07.644199 5755 layer_factory.hpp:77] Creating layer conv5/dw/scale
I0407 01:31:07.644220 5755 net.cpp:100] Creating Layer conv5/dw/scale
I0407 01:31:07.644237 5755 net.cpp:434] conv5/dw/scale <- conv5/dw
I0407 01:31:07.644268 5755 net.cpp:395] conv5/dw/scale -> conv5/dw (in-place)
I0407 01:31:07.644294 5755 layer_factory.hpp:77] Creating layer conv5/dw/scale
I0407 01:31:07.644333 5755 net.cpp:150] Setting up conv5/dw/scale
I0407 01:31:07.644359 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.644378 5755 net.cpp:165] Memory required for data: 2600349728
I0407 01:31:07.644399 5755 layer_factory.hpp:77] Creating layer conv5/dw/relu
I0407 01:31:07.644421 5755 net.cpp:100] Creating Layer conv5/dw/relu
I0407 01:31:07.644486 5755 net.cpp:434] conv5/dw/relu <- conv5/dw
I0407 01:31:07.644505 5755 net.cpp:395] conv5/dw/relu -> conv5/dw (in-place)
I0407 01:31:07.644526 5755 net.cpp:150] Setting up conv5/dw/relu
I0407 01:31:07.644541 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.644569 5755 net.cpp:165] Memory required for data: 2635837472
I0407 01:31:07.644587 5755 layer_factory.hpp:77] Creating layer conv5
I0407 01:31:07.644610 5755 net.cpp:100] Creating Layer conv5
I0407 01:31:07.644627 5755 net.cpp:434] conv5 <- conv5/dw
I0407 01:31:07.644655 5755 net.cpp:408] conv5 -> conv5
I0407 01:31:07.645952 5755 net.cpp:150] Setting up conv5
I0407 01:31:07.645972 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.645993 5755 net.cpp:165] Memory required for data: 2671325216
I0407 01:31:07.646013 5755 layer_factory.hpp:77] Creating layer conv5/bn
I0407 01:31:07.646039 5755 net.cpp:100] Creating Layer conv5/bn
I0407 01:31:07.646057 5755 net.cpp:434] conv5/bn <- conv5
I0407 01:31:07.646076 5755 net.cpp:395] conv5/bn -> conv5 (in-place)
I0407 01:31:07.646109 5755 net.cpp:150] Setting up conv5/bn
I0407 01:31:07.646194 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.646214 5755 net.cpp:165] Memory required for data: 2706812960
I0407 01:31:07.646245 5755 layer_factory.hpp:77] Creating layer conv5/scale
I0407 01:31:07.646270 5755 net.cpp:100] Creating Layer conv5/scale
I0407 01:31:07.646287 5755 net.cpp:434] conv5/scale <- conv5
I0407 01:31:07.646307 5755 net.cpp:395] conv5/scale -> conv5 (in-place)
I0407 01:31:07.646342 5755 layer_factory.hpp:77] Creating layer conv5/scale
I0407 01:31:07.646390 5755 net.cpp:150] Setting up conv5/scale
I0407 01:31:07.646407 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.646435 5755 net.cpp:165] Memory required for data: 2742300704
I0407 01:31:07.646469 5755 layer_factory.hpp:77] Creating layer conv5/relu
I0407 01:31:07.646488 5755 net.cpp:100] Creating Layer conv5/relu
I0407 01:31:07.646505 5755 net.cpp:434] conv5/relu <- conv5
I0407 01:31:07.646533 5755 net.cpp:395] conv5/relu -> conv5 (in-place)
I0407 01:31:07.646551 5755 net.cpp:150] Setting up conv5/relu
I0407 01:31:07.646567 5755 net.cpp:157] Top shape: 24 256 38 38 (8871936)
I0407 01:31:07.646585 5755 net.cpp:165] Memory required for data: 2777788448
I0407 01:31:07.646602 5755 layer_factory.hpp:77] Creating layer conv6/dw
I0407 01:31:07.646636 5755 net.cpp:100] Creating Layer conv6/dw
I0407 01:31:07.646652 5755 net.cpp:434] conv6/dw <- conv5
I0407 01:31:07.646673 5755 net.cpp:408] conv6/dw -> conv6/dw
I0407 01:31:07.646760 5755 net.cpp:150] Setting up conv6/dw
I0407 01:31:07.646777 5755 net.cpp:157] Top shape: 24 256 19 19 (2217984)
I0407 01:31:07.646797 5755 net.cpp:165] Memory required for data: 2786660384
I0407 01:31:07.646826 5755 layer_factory.hpp:77] Creating layer conv6/dw/bn
I0407 01:31:07.646844 5755 net.cpp:100] Creating Layer conv6/dw/bn
I0407 01:31:07.646862 5755 net.cpp:434] conv6/dw/bn <- conv6/dw
I0407 01:31:07.646881 5755 net.cpp:395] conv6/dw/bn -> conv6/dw (in-place)
I0407 01:31:07.646924 5755 net.cpp:150] Setting up conv6/dw/bn
I0407 01:31:07.646941 5755 net.cpp:157] Top shape: 24 256 19 19 (2217984)
I0407 01:31:07.646960 5755 net.cpp:165] Memory required for data: 2795532320
I0407 01:31:07.646981 5755 layer_factory.hpp:77] Creating layer conv6/dw/scale
I0407 01:31:07.647012 5755 net.cpp:100] Creating Layer conv6/dw/scale
I0407 01:31:07.647029 5755 net.cpp:434] conv6/dw/scale <- conv6/dw
I0407 01:31:07.647049 5755 net.cpp:395] conv6/dw/scale -> conv6/dw (in-place)
I0407 01:31:07.647073 5755 layer_factory.hpp:77] Creating layer conv6/dw/scale
I0407 01:31:07.647115 5755 net.cpp:150] Setting up conv6/dw/scale
I0407 01:31:07.647133 5755 net.cpp:157] Top shape: 24 256 19 19 (2217984)
I0407 01:31:07.647152 5755 net.cpp:165] Memory required for data: 2804404256
I0407 01:31:07.647171 5755 layer_factory.hpp:77] Creating layer conv6/dw/relu
I0407 01:31:07.647189 5755 net.cpp:100] Creating Layer conv6/dw/relu
I0407 01:31:07.647233 5755 net.cpp:434] conv6/dw/relu <- conv6/dw
I0407 01:31:07.647251 5755 net.cpp:395] conv6/dw/relu -> conv6/dw (in-place)
I0407 01:31:07.647271 5755 net.cpp:150] Setting up conv6/dw/relu
I0407 01:31:07.647287 5755 net.cpp:157] Top shape: 24 256 19 19 (2217984)
I0407 01:31:07.647313 5755 net.cpp:165] Memory required for data: 2813276192
I0407 01:31:07.647330 5755 layer_factory.hpp:77] Creating layer conv6
I0407 01:31:07.647356 5755 net.cpp:100] Creating Layer conv6
I0407 01:31:07.647372 5755 net.cpp:434] conv6 <- conv6/dw
I0407 01:31:07.647394 5755 net.cpp:408] conv6 -> conv6
I0407 01:31:07.650038 5755 net.cpp:150] Setting up conv6
I0407 01:31:07.650087 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.650111 5755 net.cpp:165] Memory required for data: 2831020064
I0407 01:31:07.650135 5755 layer_factory.hpp:77] Creating layer conv6/bn
I0407 01:31:07.650205 5755 net.cpp:100] Creating Layer conv6/bn
I0407 01:31:07.650228 5755 net.cpp:434] conv6/bn <- conv6
I0407 01:31:07.650259 5755 net.cpp:395] conv6/bn -> conv6 (in-place)
I0407 01:31:07.650301 5755 net.cpp:150] Setting up conv6/bn
I0407 01:31:07.650318 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.650338 5755 net.cpp:165] Memory required for data: 2848763936
I0407 01:31:07.650369 5755 layer_factory.hpp:77] Creating layer conv6/scale
I0407 01:31:07.650391 5755 net.cpp:100] Creating Layer conv6/scale
I0407 01:31:07.650409 5755 net.cpp:434] conv6/scale <- conv6
I0407 01:31:07.650429 5755 net.cpp:395] conv6/scale -> conv6 (in-place)
I0407 01:31:07.650466 5755 layer_factory.hpp:77] Creating layer conv6/scale
I0407 01:31:07.650511 5755 net.cpp:150] Setting up conv6/scale
I0407 01:31:07.650528 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.650559 5755 net.cpp:165] Memory required for data: 2866507808
I0407 01:31:07.650585 5755 layer_factory.hpp:77] Creating layer conv6/relu
I0407 01:31:07.650612 5755 net.cpp:100] Creating Layer conv6/relu
I0407 01:31:07.650629 5755 net.cpp:434] conv6/relu <- conv6
I0407 01:31:07.650656 5755 net.cpp:395] conv6/relu -> conv6 (in-place)
I0407 01:31:07.650678 5755 net.cpp:150] Setting up conv6/relu
I0407 01:31:07.650694 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.650713 5755 net.cpp:165] Memory required for data: 2884251680
I0407 01:31:07.650729 5755 layer_factory.hpp:77] Creating layer conv7/dw
I0407 01:31:07.650774 5755 net.cpp:100] Creating Layer conv7/dw
I0407 01:31:07.650792 5755 net.cpp:434] conv7/dw <- conv6
I0407 01:31:07.650813 5755 net.cpp:408] conv7/dw -> conv7/dw
I0407 01:31:07.650982 5755 net.cpp:150] Setting up conv7/dw
I0407 01:31:07.651008 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.651034 5755 net.cpp:165] Memory required for data: 2901995552
I0407 01:31:07.651069 5755 layer_factory.hpp:77] Creating layer conv7/dw/bn
I0407 01:31:07.651099 5755 net.cpp:100] Creating Layer conv7/dw/bn
I0407 01:31:07.651121 5755 net.cpp:434] conv7/dw/bn <- conv7/dw
I0407 01:31:07.651155 5755 net.cpp:395] conv7/dw/bn -> conv7/dw (in-place)
I0407 01:31:07.651206 5755 net.cpp:150] Setting up conv7/dw/bn
I0407 01:31:07.651228 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.651263 5755 net.cpp:165] Memory required for data: 2919739424
I0407 01:31:07.651293 5755 layer_factory.hpp:77] Creating layer conv7/dw/scale
I0407 01:31:07.651324 5755 net.cpp:100] Creating Layer conv7/dw/scale
I0407 01:31:07.651355 5755 net.cpp:434] conv7/dw/scale <- conv7/dw
I0407 01:31:07.651454 5755 net.cpp:395] conv7/dw/scale -> conv7/dw (in-place)
I0407 01:31:07.651494 5755 layer_factory.hpp:77] Creating layer conv7/dw/scale
I0407 01:31:07.651552 5755 net.cpp:150] Setting up conv7/dw/scale
I0407 01:31:07.651576 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.651597 5755 net.cpp:165] Memory required for data: 2937483296
I0407 01:31:07.651620 5755 layer_factory.hpp:77] Creating layer conv7/dw/relu
I0407 01:31:07.651651 5755 net.cpp:100] Creating Layer conv7/dw/relu
I0407 01:31:07.651723 5755 net.cpp:434] conv7/dw/relu <- conv7/dw
I0407 01:31:07.651755 5755 net.cpp:395] conv7/dw/relu -> conv7/dw (in-place)
I0407 01:31:07.651779 5755 net.cpp:150] Setting up conv7/dw/relu
I0407 01:31:07.651800 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.651821 5755 net.cpp:165] Memory required for data: 2955227168
I0407 01:31:07.651849 5755 layer_factory.hpp:77] Creating layer conv7
I0407 01:31:07.651878 5755 net.cpp:100] Creating Layer conv7
I0407 01:31:07.651898 5755 net.cpp:434] conv7 <- conv7/dw
I0407 01:31:07.651935 5755 net.cpp:408] conv7 -> conv7
I0407 01:31:07.657287 5755 net.cpp:150] Setting up conv7
I0407 01:31:07.657351 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.657375 5755 net.cpp:165] Memory required for data: 2972971040
I0407 01:31:07.657402 5755 layer_factory.hpp:77] Creating layer conv7/bn
I0407 01:31:07.657428 5755 net.cpp:100] Creating Layer conv7/bn
I0407 01:31:07.657454 5755 net.cpp:434] conv7/bn <- conv7
I0407 01:31:07.657477 5755 net.cpp:395] conv7/bn -> conv7 (in-place)
I0407 01:31:07.657514 5755 net.cpp:150] Setting up conv7/bn
I0407 01:31:07.657539 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.657559 5755 net.cpp:165] Memory required for data: 2990714912
I0407 01:31:07.657582 5755 layer_factory.hpp:77] Creating layer conv7/scale
I0407 01:31:07.657606 5755 net.cpp:100] Creating Layer conv7/scale
I0407 01:31:07.657624 5755 net.cpp:434] conv7/scale <- conv7
I0407 01:31:07.657651 5755 net.cpp:395] conv7/scale -> conv7 (in-place)
I0407 01:31:07.657682 5755 layer_factory.hpp:77] Creating layer conv7/scale
I0407 01:31:07.657722 5755 net.cpp:150] Setting up conv7/scale
I0407 01:31:07.657748 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.657768 5755 net.cpp:165] Memory required for data: 3008458784
I0407 01:31:07.657788 5755 layer_factory.hpp:77] Creating layer conv7/relu
I0407 01:31:07.657811 5755 net.cpp:100] Creating Layer conv7/relu
I0407 01:31:07.657847 5755 net.cpp:434] conv7/relu <- conv7
I0407 01:31:07.657867 5755 net.cpp:395] conv7/relu -> conv7 (in-place)
I0407 01:31:07.657889 5755 net.cpp:150] Setting up conv7/relu
I0407 01:31:07.657905 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.657932 5755 net.cpp:165] Memory required for data: 3026202656
I0407 01:31:07.657950 5755 layer_factory.hpp:77] Creating layer conv8/dw
I0407 01:31:07.657984 5755 net.cpp:100] Creating Layer conv8/dw
I0407 01:31:07.658001 5755 net.cpp:434] conv8/dw <- conv7
I0407 01:31:07.658030 5755 net.cpp:408] conv8/dw -> conv8/dw
I0407 01:31:07.658185 5755 net.cpp:150] Setting up conv8/dw
I0407 01:31:07.658246 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.658264 5755 net.cpp:165] Memory required for data: 3043946528
I0407 01:31:07.658283 5755 layer_factory.hpp:77] Creating layer conv8/dw/bn
I0407 01:31:07.658308 5755 net.cpp:100] Creating Layer conv8/dw/bn
I0407 01:31:07.658332 5755 net.cpp:434] conv8/dw/bn <- conv8/dw
I0407 01:31:07.658351 5755 net.cpp:395] conv8/dw/bn -> conv8/dw (in-place)
I0407 01:31:07.658390 5755 net.cpp:150] Setting up conv8/dw/bn
I0407 01:31:07.658406 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.658433 5755 net.cpp:165] Memory required for data: 3061690400
I0407 01:31:07.658455 5755 layer_factory.hpp:77] Creating layer conv8/dw/scale
I0407 01:31:07.658491 5755 net.cpp:100] Creating Layer conv8/dw/scale
I0407 01:31:07.658509 5755 net.cpp:434] conv8/dw/scale <- conv8/dw
I0407 01:31:07.658537 5755 net.cpp:395] conv8/dw/scale -> conv8/dw (in-place)
I0407 01:31:07.658566 5755 layer_factory.hpp:77] Creating layer conv8/dw/scale
I0407 01:31:07.658608 5755 net.cpp:150] Setting up conv8/dw/scale
I0407 01:31:07.658634 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.658653 5755 net.cpp:165] Memory required for data: 3079434272
I0407 01:31:07.658674 5755 layer_factory.hpp:77] Creating layer conv8/dw/relu
I0407 01:31:07.658692 5755 net.cpp:100] Creating Layer conv8/dw/relu
I0407 01:31:07.658764 5755 net.cpp:434] conv8/dw/relu <- conv8/dw
I0407 01:31:07.658785 5755 net.cpp:395] conv8/dw/relu -> conv8/dw (in-place)
I0407 01:31:07.658805 5755 net.cpp:150] Setting up conv8/dw/relu
I0407 01:31:07.658829 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.658849 5755 net.cpp:165] Memory required for data: 3097178144
I0407 01:31:07.658865 5755 layer_factory.hpp:77] Creating layer conv8
I0407 01:31:07.658897 5755 net.cpp:100] Creating Layer conv8
I0407 01:31:07.658924 5755 net.cpp:434] conv8 <- conv8/dw
I0407 01:31:07.658944 5755 net.cpp:408] conv8 -> conv8
I0407 01:31:07.664489 5755 net.cpp:150] Setting up conv8
I0407 01:31:07.664548 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.664579 5755 net.cpp:165] Memory required for data: 3114922016
I0407 01:31:07.664628 5755 layer_factory.hpp:77] Creating layer conv8/bn
I0407 01:31:07.664666 5755 net.cpp:100] Creating Layer conv8/bn
I0407 01:31:07.664701 5755 net.cpp:434] conv8/bn <- conv8
I0407 01:31:07.664734 5755 net.cpp:395] conv8/bn -> conv8 (in-place)
I0407 01:31:07.664782 5755 net.cpp:150] Setting up conv8/bn
I0407 01:31:07.664816 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.664839 5755 net.cpp:165] Memory required for data: 3132665888
I0407 01:31:07.664875 5755 layer_factory.hpp:77] Creating layer conv8/scale
I0407 01:31:07.664901 5755 net.cpp:100] Creating Layer conv8/scale
I0407 01:31:07.664937 5755 net.cpp:434] conv8/scale <- conv8
I0407 01:31:07.664970 5755 net.cpp:395] conv8/scale -> conv8 (in-place)
I0407 01:31:07.665001 5755 layer_factory.hpp:77] Creating layer conv8/scale
I0407 01:31:07.665060 5755 net.cpp:150] Setting up conv8/scale
I0407 01:31:07.665091 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.665136 5755 net.cpp:165] Memory required for data: 3150409760
I0407 01:31:07.665159 5755 layer_factory.hpp:77] Creating layer conv8/relu
I0407 01:31:07.665194 5755 net.cpp:100] Creating Layer conv8/relu
I0407 01:31:07.665230 5755 net.cpp:434] conv8/relu <- conv8
I0407 01:31:07.665253 5755 net.cpp:395] conv8/relu -> conv8 (in-place)
I0407 01:31:07.665287 5755 net.cpp:150] Setting up conv8/relu
I0407 01:31:07.665323 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.665343 5755 net.cpp:165] Memory required for data: 3168153632
I0407 01:31:07.665364 5755 layer_factory.hpp:77] Creating layer conv9/dw
I0407 01:31:07.665410 5755 net.cpp:100] Creating Layer conv9/dw
I0407 01:31:07.665446 5755 net.cpp:434] conv9/dw <- conv8
I0407 01:31:07.665484 5755 net.cpp:408] conv9/dw -> conv9/dw
I0407 01:31:07.665632 5755 net.cpp:150] Setting up conv9/dw
I0407 01:31:07.665661 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.665699 5755 net.cpp:165] Memory required for data: 3185897504
I0407 01:31:07.665724 5755 layer_factory.hpp:77] Creating layer conv9/dw/bn
I0407 01:31:07.665760 5755 net.cpp:100] Creating Layer conv9/dw/bn
I0407 01:31:07.665797 5755 net.cpp:434] conv9/dw/bn <- conv9/dw
I0407 01:31:07.665834 5755 net.cpp:395] conv9/dw/bn -> conv9/dw (in-place)
I0407 01:31:07.665899 5755 net.cpp:150] Setting up conv9/dw/bn
I0407 01:31:07.665928 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.665961 5755 net.cpp:165] Memory required for data: 3203641376
I0407 01:31:07.665983 5755 layer_factory.hpp:77] Creating layer conv9/dw/scale
I0407 01:31:07.666024 5755 net.cpp:100] Creating Layer conv9/dw/scale
I0407 01:31:07.666047 5755 net.cpp:434] conv9/dw/scale <- conv9/dw
I0407 01:31:07.666121 5755 net.cpp:395] conv9/dw/scale -> conv9/dw (in-place)
I0407 01:31:07.666172 5755 layer_factory.hpp:77] Creating layer conv9/dw/scale
I0407 01:31:07.666236 5755 net.cpp:150] Setting up conv9/dw/scale
I0407 01:31:07.666265 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.666301 5755 net.cpp:165] Memory required for data: 3221385248
I0407 01:31:07.666324 5755 layer_factory.hpp:77] Creating layer conv9/dw/relu
I0407 01:31:07.666345 5755 net.cpp:100] Creating Layer conv9/dw/relu
I0407 01:31:07.666424 5755 net.cpp:434] conv9/dw/relu <- conv9/dw
I0407 01:31:07.666457 5755 net.cpp:395] conv9/dw/relu -> conv9/dw (in-place)
I0407 01:31:07.666497 5755 net.cpp:150] Setting up conv9/dw/relu
I0407 01:31:07.666532 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.666566 5755 net.cpp:165] Memory required for data: 3239129120
I0407 01:31:07.666610 5755 layer_factory.hpp:77] Creating layer conv9
I0407 01:31:07.666636 5755 net.cpp:100] Creating Layer conv9
I0407 01:31:07.666668 5755 net.cpp:434] conv9 <- conv9/dw
I0407 01:31:07.666710 5755 net.cpp:408] conv9 -> conv9
F0407 01:31:07.673615 5759 math_functions.cpp:250] Check failed: a <= b (0 vs. -1.19209e-07)
*** Check failure stack trace: ***
I0407 01:31:07.677111 5755 net.cpp:150] Setting up conv9
I0407 01:31:07.677577 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.677608 5755 net.cpp:165] Memory required for data: 3256872992
I0407 01:31:07.677647 5755 layer_factory.hpp:77] Creating layer conv9/bn
I0407 01:31:07.677682 5755 net.cpp:100] Creating Layer conv9/bn
I0407 01:31:07.677714 5755 net.cpp:434] conv9/bn <- conv9
I0407 01:31:07.677739 5755 net.cpp:395] conv9/bn -> conv9 (in-place)
I0407 01:31:07.677788 5755 net.cpp:150] Setting up conv9/bn
I0407 01:31:07.677808 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.677834 5755 net.cpp:165] Memory required for data: 3274616864
I0407 01:31:07.677857 5755 layer_factory.hpp:77] Creating layer conv9/scale
I0407 01:31:07.677883 5755 net.cpp:100] Creating Layer conv9/scale
I0407 01:31:07.679563 5755 net.cpp:434] conv9/scale <- conv9
I0407 01:31:07.679589 5755 net.cpp:395] conv9/scale -> conv9 (in-place)
I0407 01:31:07.679631 5755 layer_factory.hpp:77] Creating layer conv9/scale
I0407 01:31:07.679684 5755 net.cpp:150] Setting up conv9/scale
I0407 01:31:07.679702 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.679723 5755 net.cpp:165] Memory required for data: 3292360736
I0407 01:31:07.679752 5755 layer_factory.hpp:77] Creating layer conv9/relu
I0407 01:31:07.679780 5755 net.cpp:100] Creating Layer conv9/relu
I0407 01:31:07.679805 5755 net.cpp:434] conv9/relu <- conv9
I0407 01:31:07.679826 5755 net.cpp:395] conv9/relu -> conv9 (in-place)
I0407 01:31:07.679847 5755 net.cpp:150] Setting up conv9/relu
I0407 01:31:07.679864 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.679893 5755 net.cpp:165] Memory required for data: 3310104608
I0407 01:31:07.679908 5755 layer_factory.hpp:77] Creating layer conv10/dw
I0407 01:31:07.679944 5755 net.cpp:100] Creating Layer conv10/dw
I0407 01:31:07.679965 5755 net.cpp:434] conv10/dw <- conv9
I0407 01:31:07.679986 5755 net.cpp:408] conv10/dw -> conv10/dw
I0407 01:31:07.680155 5755 net.cpp:150] Setting up conv10/dw
I0407 01:31:07.680174 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.680193 5755 net.cpp:165] Memory required for data: 3327848480
I0407 01:31:07.680220 5755 layer_factory.hpp:77] Creating layer conv10/dw/bn
I0407 01:31:07.680240 5755 net.cpp:100] Creating Layer conv10/dw/bn
I0407 01:31:07.680259 5755 net.cpp:434] conv10/dw/bn <- conv10/dw
I0407 01:31:07.680285 5755 net.cpp:395] conv10/dw/bn -> conv10/dw (in-place)
I0407 01:31:07.680322 5755 net.cpp:150] Setting up conv10/dw/bn
I0407 01:31:07.680339 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.680367 5755 net.cpp:165] Memory required for data: 3345592352
I0407 01:31:07.680392 5755 layer_factory.hpp:77] Creating layer conv10/dw/scale
I0407 01:31:07.680421 5755 net.cpp:100] Creating Layer conv10/dw/scale
I0407 01:31:07.680439 5755 net.cpp:434] conv10/dw/scale <- conv10/dw
I0407 01:31:07.680461 5755 net.cpp:395] conv10/dw/scale -> conv10/dw (in-place)
I0407 01:31:07.680503 5755 layer_factory.hpp:77] Creating layer conv10/dw/scale
I0407 01:31:07.680542 5755 net.cpp:150] Setting up conv10/dw/scale
I0407 01:31:07.680577 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.680596 5755 net.cpp:165] Memory required for data: 3363336224
I0407 01:31:07.680625 5755 layer_factory.hpp:77] Creating layer conv10/dw/relu
I0407 01:31:07.680646 5755 net.cpp:100] Creating Layer conv10/dw/relu
I0407 01:31:07.680665 5755 net.cpp:434] conv10/dw/relu <- conv10/dw
I0407 01:31:07.680691 5755 net.cpp:395] conv10/dw/relu -> conv10/dw (in-place)
I0407 01:31:07.680711 5755 net.cpp:150] Setting up conv10/dw/relu
I0407 01:31:07.680727 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.680747 5755 net.cpp:165] Memory required for data: 3381080096
I0407 01:31:07.680771 5755 layer_factory.hpp:77] Creating layer conv10
I0407 01:31:07.680805 5755 net.cpp:100] Creating Layer conv10
I0407 01:31:07.680830 5755 net.cpp:434] conv10 <- conv10/dw
I0407 01:31:07.680856 5755 net.cpp:408] conv10 -> conv10
@ 0x7f85ed16c0cd google::LogMessage::Fail()
@ 0x7f85ed16df33 google::LogMessage::SendToLog()
@ 0x7f85ed16bc28 google::LogMessage::Flush()
@ 0x7f85ed16e999 google::LogMessageFatal::~LogMessageFatal()
@ 0x7f85ed7b3987 caffe::caffe_rng_uniform<>()
I0407 01:31:07.703788 5755 net.cpp:150] Setting up conv10
I0407 01:31:07.705435 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.705483 5755 net.cpp:165] Memory required for data: 3398823968
I0407 01:31:07.705534 5755 layer_factory.hpp:77] Creating layer conv10/bn
I0407 01:31:07.705581 5755 net.cpp:100] Creating Layer conv10/bn
I0407 01:31:07.705619 5755 net.cpp:434] conv10/bn <- conv10
I0407 01:31:07.705646 5755 net.cpp:395] conv10/bn -> conv10 (in-place)
I0407 01:31:07.705705 5755 net.cpp:150] Setting up conv10/bn
I0407 01:31:07.705739 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.705760 5755 net.cpp:165] Memory required for data: 3416567840
I0407 01:31:07.705802 5755 layer_factory.hpp:77] Creating layer conv10/scale
I0407 01:31:07.705840 5755 net.cpp:100] Creating Layer conv10/scale
I0407 01:31:07.705860 5755 net.cpp:434] conv10/scale <- conv10
I0407 01:31:07.705899 5755 net.cpp:395] conv10/scale -> conv10 (in-place)
I0407 01:31:07.705938 5755 layer_factory.hpp:77] Creating layer conv10/scale
I0407 01:31:07.705991 5755 net.cpp:150] Setting up conv10/scale
I0407 01:31:07.706027 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.706049 5755 net.cpp:165] Memory required for data: 3434311712
I0407 01:31:07.706079 5755 layer_factory.hpp:77] Creating layer conv10/relu
I0407 01:31:07.706116 5755 net.cpp:100] Creating Layer conv10/relu
I0407 01:31:07.706182 5755 net.cpp:434] conv10/relu <- conv10
I0407 01:31:07.706223 5755 net.cpp:395] conv10/relu -> conv10 (in-place)
I0407 01:31:07.706245 5755 net.cpp:150] Setting up conv10/relu
I0407 01:31:07.706262 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.706290 5755 net.cpp:165] Memory required for data: 3452055584
I0407 01:31:07.706307 5755 layer_factory.hpp:77] Creating layer conv11/dw
I0407 01:31:07.706351 5755 net.cpp:100] Creating Layer conv11/dw
I0407 01:31:07.706373 5755 net.cpp:434] conv11/dw <- conv10
@ 0x7f85ed78c9e8 caffe::SampleBBox()
I0407 01:31:07.709905 5755 net.cpp:408] conv11/dw -> conv11/dw
I0407 01:31:07.710197 5755 net.cpp:150] Setting up conv11/dw
I0407 01:31:07.710238 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.710264 5755 net.cpp:165] Memory required for data: 3469799456
I0407 01:31:07.710297 5755 layer_factory.hpp:77] Creating layer conv11/dw/bn
I0407 01:31:07.711845 5755 net.cpp:100] Creating Layer conv11/dw/bn
I0407 01:31:07.711881 5755 net.cpp:434] conv11/dw/bn <- conv11/dw
I0407 01:31:07.711905 5755 net.cpp:395] conv11/dw/bn -> conv11/dw (in-place)
I0407 01:31:07.711969 5755 net.cpp:150] Setting up conv11/dw/bn
I0407 01:31:07.712005 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.712039 5755 net.cpp:165] Memory required for data: 3487543328
I0407 01:31:07.712095 5755 layer_factory.hpp:77] Creating layer conv11/dw/scale
I0407 01:31:07.712139 5755 net.cpp:100] Creating Layer conv11/dw/scale
I0407 01:31:07.712167 5755 net.cpp:434] conv11/dw/scale <- conv11/dw
I0407 01:31:07.712188 5755 net.cpp:395] conv11/dw/scale -> conv11/dw (in-place)
I0407 01:31:07.712241 5755 layer_factory.hpp:77] Creating layer conv11/dw/scale
I0407 01:31:07.712299 5755 net.cpp:150] Setting up conv11/dw/scale
I0407 01:31:07.712337 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.712366 5755 net.cpp:165] Memory required for data: 3505287200
I0407 01:31:07.712419 5755 layer_factory.hpp:77] Creating layer conv11/dw/relu
I0407 01:31:07.712453 5755 net.cpp:100] Creating Layer conv11/dw/relu
I0407 01:31:07.712494 5755 net.cpp:434] conv11/dw/relu <- conv11/dw
I0407 01:31:07.712520 5755 net.cpp:395] conv11/dw/relu -> conv11/dw (in-place)
I0407 01:31:07.712572 5755 net.cpp:150] Setting up conv11/dw/relu
I0407 01:31:07.712594 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.713093 5755 net.cpp:165] Memory required for data: 3523031072
I0407 01:31:07.713119 5755 layer_factory.hpp:77] Creating layer conv11
I0407 01:31:07.713182 5755 net.cpp:100] Creating Layer conv11
I0407 01:31:07.713223 5755 net.cpp:434] conv11 <- conv11/dw
I0407 01:31:07.713310 5755 net.cpp:408] conv11 -> conv11
@ 0x7f85ed78cd40 caffe::GenerateSamples()
@ 0x7f85ed78cf90 caffe::GenerateBatchSamples()
@ 0x7f85ed5b2e52 caffe::AnnotatedDataLayer<>::load_batch()
@ 0x7f85ed6a98ea caffe::BasePrefetchingDataLayer<>::InternalThreadEntry()
I0407 01:31:07.724553 5755 net.cpp:150] Setting up conv11
I0407 01:31:07.726023 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.726052 5755 net.cpp:165] Memory required for data: 3540774944
I0407 01:31:07.726125 5755 layer_factory.hpp:77] Creating layer conv11/bn
I0407 01:31:07.726167 5755 net.cpp:100] Creating Layer conv11/bn
I0407 01:31:07.726191 5755 net.cpp:434] conv11/bn <- conv11
I0407 01:31:07.726227 5755 net.cpp:395] conv11/bn -> conv11 (in-place)
I0407 01:31:07.727397 5755 net.cpp:150] Setting up conv11/bn
I0407 01:31:07.727417 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.727445 5755 net.cpp:165] Memory required for data: 3558518816
I0407 01:31:07.727471 5755 layer_factory.hpp:77] Creating layer conv11/scale
I0407 01:31:07.727499 5755 net.cpp:100] Creating Layer conv11/scale
I0407 01:31:07.727524 5755 net.cpp:434] conv11/scale <- conv11
I0407 01:31:07.727545 5755 net.cpp:395] conv11/scale -> conv11 (in-place)
I0407 01:31:07.727586 5755 layer_factory.hpp:77] Creating layer conv11/scale
I0407 01:31:07.727629 5755 net.cpp:150] Setting up conv11/scale
I0407 01:31:07.727655 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.727675 5755 net.cpp:165] Memory required for data: 3576262688
I0407 01:31:07.727696 5755 layer_factory.hpp:77] Creating layer conv11/relu
I0407 01:31:07.727725 5755 net.cpp:100] Creating Layer conv11/relu
I0407 01:31:07.727743 5755 net.cpp:434] conv11/relu <- conv11
I0407 01:31:07.727767 5755 net.cpp:395] conv11/relu -> conv11 (in-place)
I0407 01:31:07.727797 5755 net.cpp:150] Setting up conv11/relu
I0407 01:31:07.727814 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.727833 5755 net.cpp:165] Memory required for data: 3594006560
I0407 01:31:07.727859 5755 layer_factory.hpp:77] Creating layer conv11_conv11/relu_0_split
I0407 01:31:07.727883 5755 net.cpp:100] Creating Layer conv11_conv11/relu_0_split
I0407 01:31:07.727901 5755 net.cpp:434] conv11_conv11/relu_0_split <- conv11
I0407 01:31:07.727931 5755 net.cpp:408] conv11_conv11/relu_0_split -> conv11_conv11/relu_0_split_0
I0407 01:31:07.727962 5755 net.cpp:408] conv11_conv11/relu_0_split -> conv11_conv11/relu_0_split_1
I0407 01:31:07.727994 5755 net.cpp:408] conv11_conv11/relu_0_split -> conv11_conv11/relu_0_split_2
I0407 01:31:07.728018 5755 net.cpp:408] conv11_conv11/relu_0_split -> conv11_conv11/relu_0_split_3
I0407 01:31:07.728041 5755 net.cpp:150] Setting up conv11_conv11/relu_0_split
I0407 01:31:07.728067 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.728087 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.728106 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.728132 5755 net.cpp:157] Top shape: 24 512 19 19 (4435968)
I0407 01:31:07.728152 5755 net.cpp:165] Memory required for data: 3664982048
I0407 01:31:07.728169 5755 layer_factory.hpp:77] Creating layer conv12/dw
I0407 01:31:07.728205 5755 net.cpp:100] Creating Layer conv12/dw
I0407 01:31:07.728224 5755 net.cpp:434] conv12/dw <- conv11_conv11/relu_0_split_0
I0407 01:31:07.728245 5755 net.cpp:408] conv12/dw -> conv12/dw
I0407 01:31:07.728404 5755 net.cpp:150] Setting up conv12/dw
I0407 01:31:07.728425 5755 net.cpp:157] Top shape: 24 512 10 10 (1228800)
I0407 01:31:07.728446 5755 net.cpp:165] Memory required for data: 3669897248
I0407 01:31:07.728472 5755 layer_factory.hpp:77] Creating layer conv12/dw/bn
I0407 01:31:07.728492 5755 net.cpp:100] Creating Layer conv12/dw/bn
I0407 01:31:07.728509 5755 net.cpp:434] conv12/dw/bn <- conv12/dw
I0407 01:31:07.728536 5755 net.cpp:395] conv12/dw/bn -> conv12/dw (in-place)
I0407 01:31:07.728574 5755 net.cpp:150] Setting up conv12/dw/bn
I0407 01:31:07.728591 5755 net.cpp:157] Top shape: 24 512 10 10 (1228800)
I0407 01:31:07.728621 5755 net.cpp:165] Memory required for data: 3674812448
I0407 01:31:07.728644 5755 layer_factory.hpp:77] Creating layer conv12/dw/scale
I0407 01:31:07.728677 5755 net.cpp:100] Creating Layer conv12/dw/scale
I0407 01:31:07.728772 5755 net.cpp:434] conv12/dw/scale <- conv12/dw
@ 0x7f85e92e9bcd (unknown)
I0407 01:31:07.728816 5755 net.cpp:395] conv12/dw/scale -> conv12/dw (in-place)
I0407 01:31:07.729979 5755 layer_factory.hpp:77] Creating layer conv12/dw/scale
I0407 01:31:07.730049 5755 net.cpp:150] Setting up conv12/dw/scale
I0407 01:31:07.730068 5755 net.cpp:157] Top shape: 24 512 10 10 (1228800)
I0407 01:31:07.730088 5755 net.cpp:165] Memory required for data: 3679727648
I0407 01:31:07.730149 5755 layer_factory.hpp:77] Creating layer conv12/dw/relu
I0407 01:31:07.730183 5755 net.cpp:100] Creating Layer conv12/dw/relu
I0407 01:31:07.730206 5755 net.cpp:434] conv12/dw/relu <- conv12/dw
I0407 01:31:07.730239 5755 net.cpp:395] conv12/dw/relu -> conv12/dw (in-place)
I0407 01:31:07.730268 5755 net.cpp:150] Setting up conv12/dw/relu
I0407 01:31:07.730289 5755 net.cpp:157] Top shape: 24 512 10 10 (1228800)
I0407 01:31:07.730322 5755 net.cpp:165] Memory required for data: 3684642848
I0407 01:31:07.730340 5755 layer_factory.hpp:77] Creating layer conv12
I0407 01:31:07.730376 5755 net.cpp:100] Creating Layer conv12
I0407 01:31:07.730398 5755 net.cpp:434] conv12 <- conv12/dw
I0407 01:31:07.730424 5755 net.cpp:408] conv12 -> conv12
@ 0x7f85e6a776db start_thread
@ 0x7f85eb76188f clone
Aborted (core dumped)
@Rheza001
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Rheza001 commented Apr 6, 2020

i only trained 80 data. should i create more?

@mhmdghazal
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i have a similar issue

@TNemes-3141
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After spending way too much time on this problem and trying endless solutions, I finally found what causes this issue. This error is particularly treacherous as in the most cases, it decides simply not to give an error message.

See the original thread here: weiliu89/caffe#669 (comment)

Before compiling, you must edit the source code a little bit. Go to caffe/src/caffe/util/math_functions.cpp and in line 247, you find this function, which you should edit to look like this:

void caffe_rng_uniform(const int n, Dtype a, Dtype b, Dtype* r) {
  CHECK_GE(n, 0);
  CHECK(r);
  
  if (a > b) {
    Dtype c = a;
    a = b;
    b = c;
  }
  CHECK_LE(a, b);
  boost::uniform_real<Dtype> random_distribution(a, caffe_nextafter<Dtype>(b));
  boost::variate_generator<caffe::rng_t*, boost::uniform_real<Dtype> >
      variate_generator(caffe_rng(), random_distribution);
  for (int i = 0; i < n; ++i) {
    r[i] = variate_generator();
  }
}

Note that I just added an if statement (that switches the variables a and b if a is larger than b) and removed the const flag in the parameter's line from Dtype a and Dtype b.
Then simply do:

make clean
make -j$(nproc)
make py -j$(nproc)
make test -j$(nproc)
make runtest -j$(nproc) # You should run the tests after compiling to make sure you don't run into any other unexpected error.

For me, this worked very well!

@tahriribraq tahriribraq mentioned this issue Jul 29, 2020
Closed
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@Rheza001 @mhmdghazal @TNemes-3141