how to train or finetune #19
Comments
|
@gjtjx hello,have you solve the problem?Can you tell me where can get the model prototxt and share your experience about train with me?Thank you. |
|
@gjtjx You can set the batchsize=1 |
|
@Soulempty Hi, I ues it to train but the loss always oscillating , have you encountered this situation? |
|
I also doubt the model have some faulty,I remember there is oscillation at begin,do you use the model to infer the efficient? |
|
I don't use the model given by author , but I use the keras version to infer it, 20fps |
|
do you train it successfully? |
|
I train it,but the batchsize =1,dou you have caffe train model? |
|
yes ,I am training it with caffe and the bathchsize 1, but the loss is oscillating , I cannot find the solution. 能加微信聊下吗，哈哈 |
|
I noticed this issue a while back ago. If you want to train you either need to initialize with either ICNet/PSPNet weights or from ResNet weights. The prototxt files you have use a modified ResNet so you would have to modify the layers to match the original ResNet prototxt released by Kaiming He. If you prefer Tensorflow, I have a training implementation here: https://github.com/oandrienko/fast-semantic-segmentation |
any help?
name: "ICNet"
layer {
name: "data"
type: "ImageSegData"
top: "data"
top: "label"
#top: "data_dim"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_width: 2049
crop_height: 1025
mean_value: 104.008
mean_value: 116.669
mean_value: 122.675
scale_factors: 0.5
scale_factors: 0.75
scale_factors: 1
scale_factors: 1.25
scale_factors: 1.5
scale_factors: 1.75
scale_factors: 2.0
seg_class_num: 7
}
image_data_param {
#root_folder: "/home/rcvlab/workspace/caffe-seg/pspnet/"
source: "/home/train_list.txt"
batch_size: 2
is_color: true
new_height: 1160
new_width: 2312
shuffle: true
label_type: PIXEL
}
}
layer {
name: "data_sub1"
type: "Scale"
bottom: "data"
top: "data_sub1"
}
layer {
name: "data_sub2"
type: "Interp"
bottom: "data_sub1"
top: "data_sub2"
interp_param {
shrink_factor: 2
}
}
NETWORK
layer {
name: "conv1_1_3x3_s2"
type: "Convolution"
bottom: "data_sub2"
top: "conv1_1_3x3_s2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv1_1_3x3_s2/bn"
type: "BN"
bottom: "conv1_1_3x3_s2"
top: "conv1_1_3x3_s2"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv1_1_3x3_s2/relu"
type: "ReLU"
bottom: "conv1_1_3x3_s2"
top: "conv1_1_3x3_s2"
}
layer {
name: "conv1_2_3x3"
type: "Convolution"
bottom: "conv1_1_3x3_s2"
top: "conv1_2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv1_2_3x3/bn"
type: "BN"
bottom: "conv1_2_3x3"
top: "conv1_2_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv1_2_3x3/relu"
type: "ReLU"
bottom: "conv1_2_3x3"
top: "conv1_2_3x3"
}
layer {
name: "conv1_3_3x3"
type: "Convolution"
bottom: "conv1_2_3x3"
top: "conv1_3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv1_3_3x3/bn"
type: "BN"
bottom: "conv1_3_3x3"
top: "conv1_3_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv1_3_3x3/relu"
type: "ReLU"
bottom: "conv1_3_3x3"
top: "conv1_3_3x3"
}
layer {
name: "pool1_3x3_s2"
type: "Pooling"
bottom: "conv1_3_3x3"
top: "pool1_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
pad: 1
}
}
layer {
name: "conv2_1_1x1_reduce"
type: "Convolution"
bottom: "pool1_3x3_s2"
top: "conv2_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_1_1x1_reduce/bn"
type: "BN"
bottom: "conv2_1_1x1_reduce"
top: "conv2_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_1_1x1_reduce/relu"
type: "ReLU"
bottom: "conv2_1_1x1_reduce"
top: "conv2_1_1x1_reduce"
}
layer {
name: "conv2_1_3x3"
type: "Convolution"
bottom: "conv2_1_1x1_reduce"
top: "conv2_1_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_1_3x3/bn"
type: "BN"
bottom: "conv2_1_3x3"
top: "conv2_1_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_1_3x3/relu"
type: "ReLU"
bottom: "conv2_1_3x3"
top: "conv2_1_3x3"
}
layer {
name: "conv2_1_1x1_increase"
type: "Convolution"
bottom: "conv2_1_3x3"
top: "conv2_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_1_1x1_increase/bn"
type: "BN"
bottom: "conv2_1_1x1_increase"
top: "conv2_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_1_1x1_proj"
type: "Convolution"
bottom: "pool1_3x3_s2"
top: "conv2_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_1_1x1_proj/bn"
type: "BN"
bottom: "conv2_1_1x1_proj"
top: "conv2_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_1"
type: "Eltwise"
bottom: "conv2_1_1x1_proj"
bottom: "conv2_1_1x1_increase"
top: "conv2_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_1/relu"
type: "ReLU"
bottom: "conv2_1"
top: "conv2_1"
}
layer {
name: "conv2_2_1x1_reduce"
type: "Convolution"
bottom: "conv2_1"
top: "conv2_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_2_1x1_reduce/bn"
type: "BN"
bottom: "conv2_2_1x1_reduce"
top: "conv2_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_2_1x1_reduce/relu"
type: "ReLU"
bottom: "conv2_2_1x1_reduce"
top: "conv2_2_1x1_reduce"
}
layer {
name: "conv2_2_3x3"
type: "Convolution"
bottom: "conv2_2_1x1_reduce"
top: "conv2_2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_2_3x3/bn"
type: "BN"
bottom: "conv2_2_3x3"
top: "conv2_2_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_2_3x3/relu"
type: "ReLU"
bottom: "conv2_2_3x3"
top: "conv2_2_3x3"
}
layer {
name: "conv2_2_1x1_increase"
type: "Convolution"
bottom: "conv2_2_3x3"
top: "conv2_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_2_1x1_increase/bn"
type: "BN"
bottom: "conv2_2_1x1_increase"
top: "conv2_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_2"
type: "Eltwise"
bottom: "conv2_1"
bottom: "conv2_2_1x1_increase"
top: "conv2_2"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_2/relu"
type: "ReLU"
bottom: "conv2_2"
top: "conv2_2"
}
layer {
name: "conv2_3_1x1_reduce"
type: "Convolution"
bottom: "conv2_2"
top: "conv2_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_3_1x1_reduce/bn"
type: "BN"
bottom: "conv2_3_1x1_reduce"
top: "conv2_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_3_1x1_reduce/relu"
type: "ReLU"
bottom: "conv2_3_1x1_reduce"
top: "conv2_3_1x1_reduce"
}
layer {
name: "conv2_3_3x3"
type: "Convolution"
bottom: "conv2_3_1x1_reduce"
top: "conv2_3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_3_3x3/bn"
type: "BN"
bottom: "conv2_3_3x3"
top: "conv2_3_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_3_3x3/relu"
type: "ReLU"
bottom: "conv2_3_3x3"
top: "conv2_3_3x3"
}
layer {
name: "conv2_3_1x1_increase"
type: "Convolution"
bottom: "conv2_3_3x3"
top: "conv2_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_3_1x1_increase/bn"
type: "BN"
bottom: "conv2_3_1x1_increase"
top: "conv2_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_3"
type: "Eltwise"
bottom: "conv2_2"
bottom: "conv2_3_1x1_increase"
top: "conv2_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_3/relu"
type: "ReLU"
bottom: "conv2_3"
top: "conv2_3"
}
layer {
name: "conv3_1_1x1_reduce"
type: "Convolution"
bottom: "conv2_3"
top: "conv3_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_1_1x1_reduce/bn"
type: "BN"
bottom: "conv3_1_1x1_reduce"
top: "conv3_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_1_1x1_reduce/relu"
type: "ReLU"
bottom: "conv3_1_1x1_reduce"
top: "conv3_1_1x1_reduce"
}
layer {
name: "conv3_1_3x3"
type: "Convolution"
bottom: "conv3_1_1x1_reduce"
top: "conv3_1_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_1_3x3/bn"
type: "BN"
bottom: "conv3_1_3x3"
top: "conv3_1_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_1_3x3/relu"
type: "ReLU"
bottom: "conv3_1_3x3"
top: "conv3_1_3x3"
}
layer {
name: "conv3_1_1x1_increase"
type: "Convolution"
bottom: "conv3_1_3x3"
top: "conv3_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_1_1x1_increase/bn"
type: "BN"
bottom: "conv3_1_1x1_increase"
top: "conv3_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_1_1x1_proj"
type: "Convolution"
bottom: "conv2_3"
top: "conv3_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_1_1x1_proj/bn"
type: "BN"
bottom: "conv3_1_1x1_proj"
top: "conv3_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_1"
type: "Eltwise"
bottom: "conv3_1_1x1_proj"
bottom: "conv3_1_1x1_increase"
top: "conv3_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_1/relu"
type: "ReLU"
bottom: "conv3_1"
top: "conv3_1"
}
layer {
name: "conv3_1_sub4"
type: "Interp"
bottom: "conv3_1"
top: "conv3_1_sub4"
interp_param {
shrink_factor: 2
}
}
layer {
name: "conv3_2_1x1_reduce"
type: "Convolution"
bottom: "conv3_1_sub4"
top: "conv3_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_2_1x1_reduce/bn"
type: "BN"
bottom: "conv3_2_1x1_reduce"
top: "conv3_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_2_1x1_reduce/relu"
type: "ReLU"
bottom: "conv3_2_1x1_reduce"
top: "conv3_2_1x1_reduce"
}
layer {
name: "conv3_2_3x3"
type: "Convolution"
bottom: "conv3_2_1x1_reduce"
top: "conv3_2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_2_3x3/bn"
type: "BN"
bottom: "conv3_2_3x3"
top: "conv3_2_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_2_3x3/relu"
type: "ReLU"
bottom: "conv3_2_3x3"
top: "conv3_2_3x3"
}
layer {
name: "conv3_2_1x1_increase"
type: "Convolution"
bottom: "conv3_2_3x3"
top: "conv3_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_2_1x1_increase/bn"
type: "BN"
bottom: "conv3_2_1x1_increase"
top: "conv3_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_2"
type: "Eltwise"
bottom: "conv3_1_sub4"
bottom: "conv3_2_1x1_increase"
top: "conv3_2"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_2/relu"
type: "ReLU"
bottom: "conv3_2"
top: "conv3_2"
}
layer {
name: "conv3_3_1x1_reduce"
type: "Convolution"
bottom: "conv3_2"
top: "conv3_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_3_1x1_reduce/bn"
type: "BN"
bottom: "conv3_3_1x1_reduce"
top: "conv3_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_3_1x1_reduce/relu"
type: "ReLU"
bottom: "conv3_3_1x1_reduce"
top: "conv3_3_1x1_reduce"
}
layer {
name: "conv3_3_3x3"
type: "Convolution"
bottom: "conv3_3_1x1_reduce"
top: "conv3_3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_3_3x3/bn"
type: "BN"
bottom: "conv3_3_3x3"
top: "conv3_3_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_3_3x3/relu"
type: "ReLU"
bottom: "conv3_3_3x3"
top: "conv3_3_3x3"
}
layer {
name: "conv3_3_1x1_increase"
type: "Convolution"
bottom: "conv3_3_3x3"
top: "conv3_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_3_1x1_increase/bn"
type: "BN"
bottom: "conv3_3_1x1_increase"
top: "conv3_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_3"
type: "Eltwise"
bottom: "conv3_2"
bottom: "conv3_3_1x1_increase"
top: "conv3_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_3/relu"
type: "ReLU"
bottom: "conv3_3"
top: "conv3_3"
}
layer {
name: "conv3_4_1x1_reduce"
type: "Convolution"
bottom: "conv3_3"
top: "conv3_4_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_4_1x1_reduce/bn"
type: "BN"
bottom: "conv3_4_1x1_reduce"
top: "conv3_4_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_4_1x1_reduce/relu"
type: "ReLU"
bottom: "conv3_4_1x1_reduce"
top: "conv3_4_1x1_reduce"
}
layer {
name: "conv3_4_3x3"
type: "Convolution"
bottom: "conv3_4_1x1_reduce"
top: "conv3_4_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_4_3x3/bn"
type: "BN"
bottom: "conv3_4_3x3"
top: "conv3_4_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_4_3x3/relu"
type: "ReLU"
bottom: "conv3_4_3x3"
top: "conv3_4_3x3"
}
layer {
name: "conv3_4_1x1_increase"
type: "Convolution"
bottom: "conv3_4_3x3"
top: "conv3_4_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_4_1x1_increase/bn"
type: "BN"
bottom: "conv3_4_1x1_increase"
top: "conv3_4_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_4"
type: "Eltwise"
bottom: "conv3_3"
bottom: "conv3_4_1x1_increase"
top: "conv3_4"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_4/relu"
type: "ReLU"
bottom: "conv3_4"
top: "conv3_4"
}
layer {
name: "conv4_1_1x1_reduce"
type: "Convolution"
bottom: "conv3_4"
top: "conv4_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_1_1x1_reduce/bn"
type: "BN"
bottom: "conv4_1_1x1_reduce"
top: "conv4_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_1_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_1_1x1_reduce"
top: "conv4_1_1x1_reduce"
}
layer {
name: "conv4_1_3x3"
type: "Convolution"
bottom: "conv4_1_1x1_reduce"
top: "conv4_1_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_1_3x3/bn"
type: "BN"
bottom: "conv4_1_3x3"
top: "conv4_1_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_1_3x3/relu"
type: "ReLU"
bottom: "conv4_1_3x3"
top: "conv4_1_3x3"
}
layer {
name: "conv4_1_1x1_increase"
type: "Convolution"
bottom: "conv4_1_3x3"
top: "conv4_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_1_1x1_increase/bn"
type: "BN"
bottom: "conv4_1_1x1_increase"
top: "conv4_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_1_1x1_proj"
type: "Convolution"
bottom: "conv3_4"
top: "conv4_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_1_1x1_proj/bn"
type: "BN"
bottom: "conv4_1_1x1_proj"
top: "conv4_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_1"
type: "Eltwise"
bottom: "conv4_1_1x1_proj"
bottom: "conv4_1_1x1_increase"
top: "conv4_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_1/relu"
type: "ReLU"
bottom: "conv4_1"
top: "conv4_1"
}
layer {
name: "conv4_2_1x1_reduce"
type: "Convolution"
bottom: "conv4_1"
top: "conv4_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_2_1x1_reduce/bn"
type: "BN"
bottom: "conv4_2_1x1_reduce"
top: "conv4_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_2_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_2_1x1_reduce"
top: "conv4_2_1x1_reduce"
}
layer {
name: "conv4_2_3x3"
type: "Convolution"
bottom: "conv4_2_1x1_reduce"
top: "conv4_2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_2_3x3/bn"
type: "BN"
bottom: "conv4_2_3x3"
top: "conv4_2_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_2_3x3/relu"
type: "ReLU"
bottom: "conv4_2_3x3"
top: "conv4_2_3x3"
}
layer {
name: "conv4_2_1x1_increase"
type: "Convolution"
bottom: "conv4_2_3x3"
top: "conv4_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_2_1x1_increase/bn"
type: "BN"
bottom: "conv4_2_1x1_increase"
top: "conv4_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_2"
type: "Eltwise"
bottom: "conv4_1"
bottom: "conv4_2_1x1_increase"
top: "conv4_2"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_2/relu"
type: "ReLU"
bottom: "conv4_2"
top: "conv4_2"
}
layer {
name: "conv4_3_1x1_reduce"
type: "Convolution"
bottom: "conv4_2"
top: "conv4_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_3_1x1_reduce/bn"
type: "BN"
bottom: "conv4_3_1x1_reduce"
top: "conv4_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_3_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_3_1x1_reduce"
top: "conv4_3_1x1_reduce"
}
layer {
name: "conv4_3_3x3"
type: "Convolution"
bottom: "conv4_3_1x1_reduce"
top: "conv4_3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_3_3x3/bn"
type: "BN"
bottom: "conv4_3_3x3"
top: "conv4_3_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_3_3x3/relu"
type: "ReLU"
bottom: "conv4_3_3x3"
top: "conv4_3_3x3"
}
layer {
name: "conv4_3_1x1_increase"
type: "Convolution"
bottom: "conv4_3_3x3"
top: "conv4_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_3_1x1_increase/bn"
type: "BN"
bottom: "conv4_3_1x1_increase"
top: "conv4_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_3"
type: "Eltwise"
bottom: "conv4_2"
bottom: "conv4_3_1x1_increase"
top: "conv4_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_3/relu"
type: "ReLU"
bottom: "conv4_3"
top: "conv4_3"
}
layer {
name: "conv4_4_1x1_reduce"
type: "Convolution"
bottom: "conv4_3"
top: "conv4_4_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_4_1x1_reduce/bn"
type: "BN"
bottom: "conv4_4_1x1_reduce"
top: "conv4_4_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_4_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_4_1x1_reduce"
top: "conv4_4_1x1_reduce"
}
layer {
name: "conv4_4_3x3"
type: "Convolution"
bottom: "conv4_4_1x1_reduce"
top: "conv4_4_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_4_3x3/bn"
type: "BN"
bottom: "conv4_4_3x3"
top: "conv4_4_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_4_3x3/relu"
type: "ReLU"
bottom: "conv4_4_3x3"
top: "conv4_4_3x3"
}
layer {
name: "conv4_4_1x1_increase"
type: "Convolution"
bottom: "conv4_4_3x3"
top: "conv4_4_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_4_1x1_increase/bn"
type: "BN"
bottom: "conv4_4_1x1_increase"
top: "conv4_4_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_4"
type: "Eltwise"
bottom: "conv4_3"
bottom: "conv4_4_1x1_increase"
top: "conv4_4"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_4/relu"
type: "ReLU"
bottom: "conv4_4"
top: "conv4_4"
}
layer {
name: "conv4_5_1x1_reduce"
type: "Convolution"
bottom: "conv4_4"
top: "conv4_5_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_5_1x1_reduce/bn"
type: "BN"
bottom: "conv4_5_1x1_reduce"
top: "conv4_5_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_5_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_5_1x1_reduce"
top: "conv4_5_1x1_reduce"
}
layer {
name: "conv4_5_3x3"
type: "Convolution"
bottom: "conv4_5_1x1_reduce"
top: "conv4_5_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_5_3x3/bn"
type: "BN"
bottom: "conv4_5_3x3"
top: "conv4_5_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_5_3x3/relu"
type: "ReLU"
bottom: "conv4_5_3x3"
top: "conv4_5_3x3"
}
layer {
name: "conv4_5_1x1_increase"
type: "Convolution"
bottom: "conv4_5_3x3"
top: "conv4_5_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_5_1x1_increase/bn"
type: "BN"
bottom: "conv4_5_1x1_increase"
top: "conv4_5_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_5"
type: "Eltwise"
bottom: "conv4_4"
bottom: "conv4_5_1x1_increase"
top: "conv4_5"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_5/relu"
type: "ReLU"
bottom: "conv4_5"
top: "conv4_5"
}
layer {
name: "conv4_6_1x1_reduce"
type: "Convolution"
bottom: "conv4_5"
top: "conv4_6_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_6_1x1_reduce/bn"
type: "BN"
bottom: "conv4_6_1x1_reduce"
top: "conv4_6_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_6_1x1_reduce/relu"
type: "ReLU"
bottom: "conv4_6_1x1_reduce"
top: "conv4_6_1x1_reduce"
}
layer {
name: "conv4_6_3x3"
type: "Convolution"
bottom: "conv4_6_1x1_reduce"
top: "conv4_6_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
pad: 2
dilation: 2
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_6_3x3/bn"
type: "BN"
bottom: "conv4_6_3x3"
top: "conv4_6_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_6_3x3/relu"
type: "ReLU"
bottom: "conv4_6_3x3"
top: "conv4_6_3x3"
}
layer {
name: "conv4_6_1x1_increase"
type: "Convolution"
bottom: "conv4_6_3x3"
top: "conv4_6_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv4_6_1x1_increase/bn"
type: "BN"
bottom: "conv4_6_1x1_increase"
top: "conv4_6_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv4_6"
type: "Eltwise"
bottom: "conv4_5"
bottom: "conv4_6_1x1_increase"
top: "conv4_6"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_6/relu"
type: "ReLU"
bottom: "conv4_6"
top: "conv4_6"
}
layer {
name: "conv5_1_1x1_reduce"
type: "Convolution"
bottom: "conv4_6"
top: "conv5_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_1_1x1_reduce/bn"
type: "BN"
bottom: "conv5_1_1x1_reduce"
top: "conv5_1_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_1_1x1_reduce/relu"
type: "ReLU"
bottom: "conv5_1_1x1_reduce"
top: "conv5_1_1x1_reduce"
}
layer {
name: "conv5_1_3x3"
type: "Convolution"
bottom: "conv5_1_1x1_reduce"
top: "conv5_1_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 4
dilation: 4
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_1_3x3/bn"
type: "BN"
bottom: "conv5_1_3x3"
top: "conv5_1_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_1_3x3/relu"
type: "ReLU"
bottom: "conv5_1_3x3"
top: "conv5_1_3x3"
}
layer {
name: "conv5_1_1x1_increase"
type: "Convolution"
bottom: "conv5_1_3x3"
top: "conv5_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_1_1x1_increase/bn"
type: "BN"
bottom: "conv5_1_1x1_increase"
top: "conv5_1_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_1_1x1_proj"
type: "Convolution"
bottom: "conv4_6"
top: "conv5_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_1_1x1_proj/bn"
type: "BN"
bottom: "conv5_1_1x1_proj"
top: "conv5_1_1x1_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_1"
type: "Eltwise"
bottom: "conv5_1_1x1_proj"
bottom: "conv5_1_1x1_increase"
top: "conv5_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv5_1/relu"
type: "ReLU"
bottom: "conv5_1"
top: "conv5_1"
}
layer {
name: "conv5_2_1x1_reduce"
type: "Convolution"
bottom: "conv5_1"
top: "conv5_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_2_1x1_reduce/bn"
type: "BN"
bottom: "conv5_2_1x1_reduce"
top: "conv5_2_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_2_1x1_reduce/relu"
type: "ReLU"
bottom: "conv5_2_1x1_reduce"
top: "conv5_2_1x1_reduce"
}
layer {
name: "conv5_2_3x3"
type: "Convolution"
bottom: "conv5_2_1x1_reduce"
top: "conv5_2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 4
dilation: 4
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_2_3x3/bn"
type: "BN"
bottom: "conv5_2_3x3"
top: "conv5_2_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_2_3x3/relu"
type: "ReLU"
bottom: "conv5_2_3x3"
top: "conv5_2_3x3"
}
layer {
name: "conv5_2_1x1_increase"
type: "Convolution"
bottom: "conv5_2_3x3"
top: "conv5_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_2_1x1_increase/bn"
type: "BN"
bottom: "conv5_2_1x1_increase"
top: "conv5_2_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_2"
type: "Eltwise"
bottom: "conv5_1"
bottom: "conv5_2_1x1_increase"
top: "conv5_2"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv5_2/relu"
type: "ReLU"
bottom: "conv5_2"
top: "conv5_2"
}
layer {
name: "conv5_3_1x1_reduce"
type: "Convolution"
bottom: "conv5_2"
top: "conv5_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_3_1x1_reduce/bn"
type: "BN"
bottom: "conv5_3_1x1_reduce"
top: "conv5_3_1x1_reduce"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_3_1x1_reduce/relu"
type: "ReLU"
bottom: "conv5_3_1x1_reduce"
top: "conv5_3_1x1_reduce"
}
layer {
name: "conv5_3_3x3"
type: "Convolution"
bottom: "conv5_3_1x1_reduce"
top: "conv5_3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
pad: 4
dilation: 4
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_3_3x3/bn"
type: "BN"
bottom: "conv5_3_3x3"
top: "conv5_3_3x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_3_3x3/relu"
type: "ReLU"
bottom: "conv5_3_3x3"
top: "conv5_3_3x3"
}
layer {
name: "conv5_3_1x1_increase"
type: "Convolution"
bottom: "conv5_3_3x3"
top: "conv5_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_3_1x1_increase/bn"
type: "BN"
bottom: "conv5_3_1x1_increase"
top: "conv5_3_1x1_increase"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_3"
type: "Eltwise"
bottom: "conv5_2"
bottom: "conv5_3_1x1_increase"
top: "conv5_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv5_3/relu"
type: "ReLU"
bottom: "conv5_3"
top: "conv5_3"
}
layer {
name: "conv5_3_pool1"
type: "Pooling"
bottom: "conv5_3"
top: "conv5_3_pool1"
pooling_param {
pool: AVE
kernel_h: 33
kernel_w: 65
stride_h: 33
stride_w: 65
}
}
layer {
name: "conv5_3_pool1_interp"
type: "Interp"
bottom: "conv5_3_pool1"
top: "conv5_3_pool1_interp"
interp_param {
height: 33
width: 65
}
}
layer {
name: "conv5_3_pool2"
type: "Pooling"
bottom: "conv5_3"
top: "conv5_3_pool2"
pooling_param {
pool: AVE
kernel_h: 17
kernel_w: 33
stride_h: 16
stride_w: 32
}
}
layer {
name: "conv5_3_pool2_interp"
type: "Interp"
bottom: "conv5_3_pool2"
top: "conv5_3_pool2_interp"
interp_param {
height: 33
width: 65
}
}
layer {
name: "conv5_3_pool3"
type: "Pooling"
bottom: "conv5_3"
top: "conv5_3_pool3"
pooling_param {
pool: AVE
kernel_h: 13
kernel_w: 25
stride_h: 10
stride_w: 20
}
}
layer {
name: "conv5_3_pool3_interp"
type: "Interp"
bottom: "conv5_3_pool3"
top: "conv5_3_pool3_interp"
interp_param {
height: 33
width: 65
}
}
layer {
name: "conv5_3_pool6"
type: "Pooling"
bottom: "conv5_3"
top: "conv5_3_pool6"
pooling_param {
pool: AVE
kernel_h: 8
kernel_w: 15
stride_h: 5
stride_w: 10
}
}
layer {
name: "conv5_3_pool6_interp"
type: "Interp"
bottom: "conv5_3_pool6"
top: "conv5_3_pool6_interp"
interp_param {
height: 33
width: 65
}
}
layer {
name: "conv5_3_sum"
type: "Eltwise"
bottom: "conv5_3"
bottom: "conv5_3_pool6_interp"
bottom: "conv5_3_pool3_interp"
bottom: "conv5_3_pool2_interp"
bottom: "conv5_3_pool1_interp"
top: "conv5_3_sum"
}
layer {
name: "conv5_4_k1"
type: "Convolution"
bottom: "conv5_3_sum"
top: "conv5_4_k1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv5_4_k1/bn"
type: "BN"
bottom: "conv5_4_k1"
top: "conv5_4_k1"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv5_4_k1/relu"
type: "ReLU"
bottom: "conv5_4_k1"
top: "conv5_4_k1"
}
layer {
name: "conv5_4_interp"
type: "Interp"
bottom: "conv5_4_k1"
top: "conv5_4_interp"
interp_param {
zoom_factor: 2
}
}
layer {
name: "conv_sub4"
type: "Convolution"
bottom: "conv5_4_interp"
top: "conv_sub4"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
pad: 2
dilation: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv_sub4/bn"
type: "BN"
bottom: "conv_sub4"
top: "conv_sub4"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
####################sub2####################
layer {
name: "conv3_1_sub2_proj"
type: "Convolution"
bottom: "conv3_1"
top: "conv3_1_sub2_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_1_sub2_proj/bn"
type: "BN"
bottom: "conv3_1_sub2_proj"
top: "conv3_1_sub2_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "sub24_sum"
type: "Eltwise"
bottom: "conv3_1_sub2_proj"
bottom: "conv_sub4"
top: "sub24_sum"
}
layer {
name: "sub24_sum/relu"
type: "ReLU"
bottom: "sub24_sum"
top: "sub24_sum"
}
layer {
name: "sub24_sum_interp"
type: "Interp"
bottom: "sub24_sum"
top: "sub24_sum_interp"
interp_param {
zoom_factor: 2
}
}
layer {
name: "conv_sub2"
type: "Convolution"
bottom: "sub24_sum_interp"
top: "conv_sub2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
pad: 2
dilation: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv_sub2/bn"
type: "BN"
bottom: "conv_sub2"
top: "conv_sub2"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
####################sub1####################
layer {
name: "conv1_sub1"
type: "Convolution"
bottom: "data_sub1"
top: "conv1_sub1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv1_sub1/bn"
type: "BN"
bottom: "conv1_sub1"
top: "conv1_sub1"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv1_sub1/relu"
type: "ReLU"
bottom: "conv1_sub1"
top: "conv1_sub1"
}
layer {
name: "conv2_sub1"
type: "Convolution"
bottom: "conv1_sub1"
top: "conv2_sub1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv2_sub1/bn"
type: "BN"
bottom: "conv2_sub1"
top: "conv2_sub1"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv2_sub1/relu"
type: "ReLU"
bottom: "conv2_sub1"
top: "conv2_sub1"
}
layer {
name: "conv3_sub1"
type: "Convolution"
bottom: "conv2_sub1"
top: "conv3_sub1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_sub1/bn"
type: "BN"
bottom: "conv3_sub1"
top: "conv3_sub1"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "conv3_sub1/relu"
type: "ReLU"
bottom: "conv3_sub1"
top: "conv3_sub1"
}
layer {
name: "conv3_sub1_proj"
type: "Convolution"
bottom: "conv3_sub1"
top: "conv3_sub1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "conv3_sub1_proj/bn"
type: "BN"
bottom: "conv3_sub1_proj"
top: "conv3_sub1_proj"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
frozen: false
momentum: 0.95
}
}
layer {
name: "sub12_sum"
type: "Eltwise"
bottom: "conv3_sub1_proj"
bottom: "conv_sub2"
top: "sub12_sum"
}
layer {
name: "sub12_sum/relu"
type: "ReLU"
bottom: "sub12_sum"
top: "sub12_sum"
}
layer {
name: "sub12_sum_interp"
type: "Interp"
bottom: "sub12_sum"
top: "sub12_sum_interp"
interp_param {
zoom_factor: 2
}
}
layer {
name: "conv6_cls_a"
type: "Convolution"
bottom: "sub12_sum_interp"
top: "conv6_cls"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 7
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_interp"
type: "Interp"
bottom: "conv6_cls"
top: "conv6_interp"
interp_param {
zoom_factor: 4
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "conv6_interp"
bottom: "label"
top: "loss"
include {
phase: TRAIN
}
loss_param {
ignore_label: 255
}
}
but error 74
F1214 20:46:44.748036 22556 math_functions.cu:79] Check failed: error == cudaSuccess (74 vs. 0) misaligned address
*** Check failure stack trace: ***
@ 0x7f9cf2a81daa (unknown)
@ 0x7f9cf2a81ce4 (unknown)
@ 0x7f9cf2a816e6 (unknown)
@ 0x7f9cf2a84687 (unknown)
@ 0x7f9cf3285218 caffe::caffe_gpu_memcpy()
@ 0x7f9cf323a82b caffe::SyncedMemory::gpu_data()
@ 0x7f9cf31dbb02 caffe::Blob<>::gpu_data()
@ 0x7f9cf32777b5 caffe::ScaleLayer<>::Backward_gpu()
@ 0x7f9cf31c8125 caffe::Net<>::BackwardFromTo()
@ 0x7f9cf31c8271 caffe::Net<>::Backward()
@ 0x7f9cf3247b73 caffe::Solver<>::Step()
@ 0x7f9cf324851a caffe::Solver<>::Solve()
@ 0x408085 train()
@ 0x4059ac main
@ 0x7f9cf1a8df45 (unknown)
@ 0x40620b (unknown)
@ (nil) (unknown)
The text was updated successfully, but these errors were encountered: