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Pre-ResNet Caffe prototxt
name: "ResNet_50"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
force_color: true
}
data_param {
source: "examples/imagenet/ilsvrc12_train_lmdb"
batch_size: 32
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
force_color: true
}
data_param {
source: "examples/imagenet/ilsvrc12_val_lmdb"
batch_size: 25
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv1_bn"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv1_scale"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv1_relu"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
pad: 0
}
}
layer {
name: "conv2_res1_proj"
type: "Convolution"
bottom: "pool1"
top: "conv2_res1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res1_conv1"
type: "Convolution"
bottom: "pool1"
top: "conv2_res1_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res1_conv1_bn"
type: "BatchNorm"
bottom: "conv2_res1_conv1"
top: "conv2_res1_conv1"
}
layer {
name: "conv2_res1_conv1_scale"
type: "Scale"
bottom: "conv2_res1_conv1"
top: "conv2_res1_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res1_conv1_relu"
type: "ReLU"
bottom: "conv2_res1_conv1"
top: "conv2_res1_conv1"
}
layer {
name: "conv2_res1_conv2"
type: "Convolution"
bottom: "conv2_res1_conv1"
top: "conv2_res1_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res1_conv2_bn"
type: "BatchNorm"
bottom: "conv2_res1_conv2"
top: "conv2_res1_conv2"
}
layer {
name: "conv2_res1_conv2_scale"
type: "Scale"
bottom: "conv2_res1_conv2"
top: "conv2_res1_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res1_conv2_relu"
type: "ReLU"
bottom: "conv2_res1_conv2"
top: "conv2_res1_conv2"
}
layer {
name: "conv2_res1_conv3"
type: "Convolution"
bottom: "conv2_res1_conv2"
top: "conv2_res1_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res1"
type: "Eltwise"
bottom: "conv2_res1_proj"
bottom: "conv2_res1_conv3"
top: "conv2_res1"
}
layer {
name: "conv2_res2_pre_bn"
type: "BatchNorm"
bottom: "conv2_res1"
top: "conv2_res2_pre"
}
layer {
name: "conv2_res2_pre_scale"
type: "Scale"
bottom: "conv2_res2_pre"
top: "conv2_res2_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res2_pre_relu"
type: "ReLU"
bottom: "conv2_res2_pre"
top: "conv2_res2_pre"
}
layer {
name: "conv2_res2_conv1"
type: "Convolution"
bottom: "conv2_res2_pre"
top: "conv2_res2_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res2_conv1_bn"
type: "BatchNorm"
bottom: "conv2_res2_conv1"
top: "conv2_res2_conv1"
}
layer {
name: "conv2_res2_conv1_scale"
type: "Scale"
bottom: "conv2_res2_conv1"
top: "conv2_res2_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res2_conv1_relu"
type: "ReLU"
bottom: "conv2_res2_conv1"
top: "conv2_res2_conv1"
}
layer {
name: "conv2_res2_conv2"
type: "Convolution"
bottom: "conv2_res2_conv1"
top: "conv2_res2_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res2_conv2_bn"
type: "BatchNorm"
bottom: "conv2_res2_conv2"
top: "conv2_res2_conv2"
}
layer {
name: "conv2_res2_conv2_scale"
type: "Scale"
bottom: "conv2_res2_conv2"
top: "conv2_res2_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res2_conv2_relu"
type: "ReLU"
bottom: "conv2_res2_conv2"
top: "conv2_res2_conv2"
}
layer {
name: "conv2_res2_conv3"
type: "Convolution"
bottom: "conv2_res2_conv2"
top: "conv2_res2_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res2"
type: "Eltwise"
bottom: "conv2_res1"
bottom: "conv2_res2_conv3"
top: "conv2_res2"
}
layer {
name: "conv2_res3_pre_bn"
type: "BatchNorm"
bottom: "conv2_res2"
top: "conv2_res3_pre"
}
layer {
name: "conv2_res3_pre_scale"
type: "Scale"
bottom: "conv2_res3_pre"
top: "conv2_res3_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res3_pre_relu"
type: "ReLU"
bottom: "conv2_res3_pre"
top: "conv2_res3_pre"
}
layer {
name: "conv2_res3_conv1"
type: "Convolution"
bottom: "conv2_res3_pre"
top: "conv2_res3_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res3_conv1_bn"
type: "BatchNorm"
bottom: "conv2_res3_conv1"
top: "conv2_res3_conv1"
}
layer {
name: "conv2_res3_conv1_scale"
type: "Scale"
bottom: "conv2_res3_conv1"
top: "conv2_res3_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res3_conv1_relu"
type: "ReLU"
bottom: "conv2_res3_conv1"
top: "conv2_res3_conv1"
}
layer {
name: "conv2_res3_conv2"
type: "Convolution"
bottom: "conv2_res3_conv1"
top: "conv2_res3_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res3_conv2_bn"
type: "BatchNorm"
bottom: "conv2_res3_conv2"
top: "conv2_res3_conv2"
}
layer {
name: "conv2_res3_conv2_scale"
type: "Scale"
bottom: "conv2_res3_conv2"
top: "conv2_res3_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv2_res3_conv2_relu"
type: "ReLU"
bottom: "conv2_res3_conv2"
top: "conv2_res3_conv2"
}
layer {
name: "conv2_res3_conv3"
type: "Convolution"
bottom: "conv2_res3_conv2"
top: "conv2_res3_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_res3"
type: "Eltwise"
bottom: "conv2_res2"
bottom: "conv2_res3_conv3"
top: "conv2_res3"
}
layer {
name: "conv3_res1_pre_bn"
type: "BatchNorm"
bottom: "conv2_res3"
top: "conv3_res1_pre"
}
layer {
name: "conv3_res1_pre_scale"
type: "Scale"
bottom: "conv3_res1_pre"
top: "conv3_res1_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res1_pre_relu"
type: "ReLU"
bottom: "conv3_res1_pre"
top: "conv3_res1_pre"
}
layer {
name: "conv3_res1_proj"
type: "Convolution"
bottom: "conv3_res1_pre"
top: "conv3_res1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res1_conv1"
type: "Convolution"
bottom: "conv3_res1_pre"
top: "conv3_res1_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res1_conv1_bn"
type: "BatchNorm"
bottom: "conv3_res1_conv1"
top: "conv3_res1_conv1"
}
layer {
name: "conv3_res1_conv1_scale"
type: "Scale"
bottom: "conv3_res1_conv1"
top: "conv3_res1_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res1_conv1_relu"
type: "ReLU"
bottom: "conv3_res1_conv1"
top: "conv3_res1_conv1"
}
layer {
name: "conv3_res1_conv2"
type: "Convolution"
bottom: "conv3_res1_conv1"
top: "conv3_res1_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res1_conv2_bn"
type: "BatchNorm"
bottom: "conv3_res1_conv2"
top: "conv3_res1_conv2"
}
layer {
name: "conv3_res1_conv2_scale"
type: "Scale"
bottom: "conv3_res1_conv2"
top: "conv3_res1_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res1_conv2_relu"
type: "ReLU"
bottom: "conv3_res1_conv2"
top: "conv3_res1_conv2"
}
layer {
name: "conv3_res1_conv3"
type: "Convolution"
bottom: "conv3_res1_conv2"
top: "conv3_res1_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res1"
type: "Eltwise"
bottom: "conv3_res1_proj"
bottom: "conv3_res1_conv3"
top: "conv3_res1"
}
layer {
name: "conv3_res2_pre_bn"
type: "BatchNorm"
bottom: "conv3_res1"
top: "conv3_res2_pre"
}
layer {
name: "conv3_res2_pre_scale"
type: "Scale"
bottom: "conv3_res2_pre"
top: "conv3_res2_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res2_pre_relu"
type: "ReLU"
bottom: "conv3_res2_pre"
top: "conv3_res2_pre"
}
layer {
name: "conv3_res2_conv1"
type: "Convolution"
bottom: "conv3_res2_pre"
top: "conv3_res2_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res2_conv1_bn"
type: "BatchNorm"
bottom: "conv3_res2_conv1"
top: "conv3_res2_conv1"
}
layer {
name: "conv3_res2_conv1_scale"
type: "Scale"
bottom: "conv3_res2_conv1"
top: "conv3_res2_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res2_conv1_relu"
type: "ReLU"
bottom: "conv3_res2_conv1"
top: "conv3_res2_conv1"
}
layer {
name: "conv3_res2_conv2"
type: "Convolution"
bottom: "conv3_res2_conv1"
top: "conv3_res2_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res2_conv2_bn"
type: "BatchNorm"
bottom: "conv3_res2_conv2"
top: "conv3_res2_conv2"
}
layer {
name: "conv3_res2_conv2_scale"
type: "Scale"
bottom: "conv3_res2_conv2"
top: "conv3_res2_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res2_conv2_relu"
type: "ReLU"
bottom: "conv3_res2_conv2"
top: "conv3_res2_conv2"
}
layer {
name: "conv3_res2_conv3"
type: "Convolution"
bottom: "conv3_res2_conv2"
top: "conv3_res2_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res2"
type: "Eltwise"
bottom: "conv3_res1"
bottom: "conv3_res2_conv3"
top: "conv3_res2"
}
layer {
name: "conv3_res3_pre_bn"
type: "BatchNorm"
bottom: "conv3_res2"
top: "conv3_res3_pre"
}
layer {
name: "conv3_res3_pre_scale"
type: "Scale"
bottom: "conv3_res3_pre"
top: "conv3_res3_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res3_pre_relu"
type: "ReLU"
bottom: "conv3_res3_pre"
top: "conv3_res3_pre"
}
layer {
name: "conv3_res3_conv1"
type: "Convolution"
bottom: "conv3_res3_pre"
top: "conv3_res3_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res3_conv1_bn"
type: "BatchNorm"
bottom: "conv3_res3_conv1"
top: "conv3_res3_conv1"
}
layer {
name: "conv3_res3_conv1_scale"
type: "Scale"
bottom: "conv3_res3_conv1"
top: "conv3_res3_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res3_conv1_relu"
type: "ReLU"
bottom: "conv3_res3_conv1"
top: "conv3_res3_conv1"
}
layer {
name: "conv3_res3_conv2"
type: "Convolution"
bottom: "conv3_res3_conv1"
top: "conv3_res3_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res3_conv2_bn"
type: "BatchNorm"
bottom: "conv3_res3_conv2"
top: "conv3_res3_conv2"
}
layer {
name: "conv3_res3_conv2_scale"
type: "Scale"
bottom: "conv3_res3_conv2"
top: "conv3_res3_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res3_conv2_relu"
type: "ReLU"
bottom: "conv3_res3_conv2"
top: "conv3_res3_conv2"
}
layer {
name: "conv3_res3_conv3"
type: "Convolution"
bottom: "conv3_res3_conv2"
top: "conv3_res3_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res3"
type: "Eltwise"
bottom: "conv3_res2"
bottom: "conv3_res3_conv3"
top: "conv3_res3"
}
layer {
name: "conv3_res4_pre_bn"
type: "BatchNorm"
bottom: "conv3_res3"
top: "conv3_res4_pre"
}
layer {
name: "conv3_res4_pre_scale"
type: "Scale"
bottom: "conv3_res4_pre"
top: "conv3_res4_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res4_pre_relu"
type: "ReLU"
bottom: "conv3_res4_pre"
top: "conv3_res4_pre"
}
layer {
name: "conv3_res4_conv1"
type: "Convolution"
bottom: "conv3_res4_pre"
top: "conv3_res4_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res4_conv1_bn"
type: "BatchNorm"
bottom: "conv3_res4_conv1"
top: "conv3_res4_conv1"
}
layer {
name: "conv3_res4_conv1_scale"
type: "Scale"
bottom: "conv3_res4_conv1"
top: "conv3_res4_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res4_conv1_relu"
type: "ReLU"
bottom: "conv3_res4_conv1"
top: "conv3_res4_conv1"
}
layer {
name: "conv3_res4_conv2"
type: "Convolution"
bottom: "conv3_res4_conv1"
top: "conv3_res4_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res4_conv2_bn"
type: "BatchNorm"
bottom: "conv3_res4_conv2"
top: "conv3_res4_conv2"
}
layer {
name: "conv3_res4_conv2_scale"
type: "Scale"
bottom: "conv3_res4_conv2"
top: "conv3_res4_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv3_res4_conv2_relu"
type: "ReLU"
bottom: "conv3_res4_conv2"
top: "conv3_res4_conv2"
}
layer {
name: "conv3_res4_conv3"
type: "Convolution"
bottom: "conv3_res4_conv2"
top: "conv3_res4_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_res4"
type: "Eltwise"
bottom: "conv3_res3"
bottom: "conv3_res4_conv3"
top: "conv3_res4"
}
layer {
name: "conv4_res1_pre_bn"
type: "BatchNorm"
bottom: "conv3_res4"
top: "conv4_res1_pre"
}
layer {
name: "conv4_res1_pre_scale"
type: "Scale"
bottom: "conv4_res1_pre"
top: "conv4_res1_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res1_pre_relu"
type: "ReLU"
bottom: "conv4_res1_pre"
top: "conv4_res1_pre"
}
layer {
name: "conv4_res1_proj"
type: "Convolution"
bottom: "conv4_res1_pre"
top: "conv4_res1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res1_conv1"
type: "Convolution"
bottom: "conv4_res1_pre"
top: "conv4_res1_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res1_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res1_conv1"
top: "conv4_res1_conv1"
}
layer {
name: "conv4_res1_conv1_scale"
type: "Scale"
bottom: "conv4_res1_conv1"
top: "conv4_res1_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res1_conv1_relu"
type: "ReLU"
bottom: "conv4_res1_conv1"
top: "conv4_res1_conv1"
}
layer {
name: "conv4_res1_conv2"
type: "Convolution"
bottom: "conv4_res1_conv1"
top: "conv4_res1_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res1_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res1_conv2"
top: "conv4_res1_conv2"
}
layer {
name: "conv4_res1_conv2_scale"
type: "Scale"
bottom: "conv4_res1_conv2"
top: "conv4_res1_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res1_conv2_relu"
type: "ReLU"
bottom: "conv4_res1_conv2"
top: "conv4_res1_conv2"
}
layer {
name: "conv4_res1_conv3"
type: "Convolution"
bottom: "conv4_res1_conv2"
top: "conv4_res1_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res1"
type: "Eltwise"
bottom: "conv4_res1_proj"
bottom: "conv4_res1_conv3"
top: "conv4_res1"
}
layer {
name: "conv4_res2_pre_bn"
type: "BatchNorm"
bottom: "conv4_res1"
top: "conv4_res2_pre"
}
layer {
name: "conv4_res2_pre_scale"
type: "Scale"
bottom: "conv4_res2_pre"
top: "conv4_res2_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res2_pre_relu"
type: "ReLU"
bottom: "conv4_res2_pre"
top: "conv4_res2_pre"
}
layer {
name: "conv4_res2_conv1"
type: "Convolution"
bottom: "conv4_res2_pre"
top: "conv4_res2_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res2_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res2_conv1"
top: "conv4_res2_conv1"
}
layer {
name: "conv4_res2_conv1_scale"
type: "Scale"
bottom: "conv4_res2_conv1"
top: "conv4_res2_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res2_conv1_relu"
type: "ReLU"
bottom: "conv4_res2_conv1"
top: "conv4_res2_conv1"
}
layer {
name: "conv4_res2_conv2"
type: "Convolution"
bottom: "conv4_res2_conv1"
top: "conv4_res2_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res2_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res2_conv2"
top: "conv4_res2_conv2"
}
layer {
name: "conv4_res2_conv2_scale"
type: "Scale"
bottom: "conv4_res2_conv2"
top: "conv4_res2_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res2_conv2_relu"
type: "ReLU"
bottom: "conv4_res2_conv2"
top: "conv4_res2_conv2"
}
layer {
name: "conv4_res2_conv3"
type: "Convolution"
bottom: "conv4_res2_conv2"
top: "conv4_res2_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res2"
type: "Eltwise"
bottom: "conv4_res1"
bottom: "conv4_res2_conv3"
top: "conv4_res2"
}
layer {
name: "conv4_res3_pre_bn"
type: "BatchNorm"
bottom: "conv4_res2"
top: "conv4_res3_pre"
}
layer {
name: "conv4_res3_pre_scale"
type: "Scale"
bottom: "conv4_res3_pre"
top: "conv4_res3_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res3_pre_relu"
type: "ReLU"
bottom: "conv4_res3_pre"
top: "conv4_res3_pre"
}
layer {
name: "conv4_res3_conv1"
type: "Convolution"
bottom: "conv4_res3_pre"
top: "conv4_res3_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res3_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res3_conv1"
top: "conv4_res3_conv1"
}
layer {
name: "conv4_res3_conv1_scale"
type: "Scale"
bottom: "conv4_res3_conv1"
top: "conv4_res3_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res3_conv1_relu"
type: "ReLU"
bottom: "conv4_res3_conv1"
top: "conv4_res3_conv1"
}
layer {
name: "conv4_res3_conv2"
type: "Convolution"
bottom: "conv4_res3_conv1"
top: "conv4_res3_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res3_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res3_conv2"
top: "conv4_res3_conv2"
}
layer {
name: "conv4_res3_conv2_scale"
type: "Scale"
bottom: "conv4_res3_conv2"
top: "conv4_res3_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res3_conv2_relu"
type: "ReLU"
bottom: "conv4_res3_conv2"
top: "conv4_res3_conv2"
}
layer {
name: "conv4_res3_conv3"
type: "Convolution"
bottom: "conv4_res3_conv2"
top: "conv4_res3_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res3"
type: "Eltwise"
bottom: "conv4_res2"
bottom: "conv4_res3_conv3"
top: "conv4_res3"
}
layer {
name: "conv4_res4_pre_bn"
type: "BatchNorm"
bottom: "conv4_res3"
top: "conv4_res4_pre"
}
layer {
name: "conv4_res4_pre_scale"
type: "Scale"
bottom: "conv4_res4_pre"
top: "conv4_res4_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res4_pre_relu"
type: "ReLU"
bottom: "conv4_res4_pre"
top: "conv4_res4_pre"
}
layer {
name: "conv4_res4_conv1"
type: "Convolution"
bottom: "conv4_res4_pre"
top: "conv4_res4_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res4_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res4_conv1"
top: "conv4_res4_conv1"
}
layer {
name: "conv4_res4_conv1_scale"
type: "Scale"
bottom: "conv4_res4_conv1"
top: "conv4_res4_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res4_conv1_relu"
type: "ReLU"
bottom: "conv4_res4_conv1"
top: "conv4_res4_conv1"
}
layer {
name: "conv4_res4_conv2"
type: "Convolution"
bottom: "conv4_res4_conv1"
top: "conv4_res4_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res4_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res4_conv2"
top: "conv4_res4_conv2"
}
layer {
name: "conv4_res4_conv2_scale"
type: "Scale"
bottom: "conv4_res4_conv2"
top: "conv4_res4_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res4_conv2_relu"
type: "ReLU"
bottom: "conv4_res4_conv2"
top: "conv4_res4_conv2"
}
layer {
name: "conv4_res4_conv3"
type: "Convolution"
bottom: "conv4_res4_conv2"
top: "conv4_res4_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res4"
type: "Eltwise"
bottom: "conv4_res3"
bottom: "conv4_res4_conv3"
top: "conv4_res4"
}
layer {
name: "conv4_res5_pre_bn"
type: "BatchNorm"
bottom: "conv4_res4"
top: "conv4_res5_pre"
}
layer {
name: "conv4_res5_pre_scale"
type: "Scale"
bottom: "conv4_res5_pre"
top: "conv4_res5_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res5_pre_relu"
type: "ReLU"
bottom: "conv4_res5_pre"
top: "conv4_res5_pre"
}
layer {
name: "conv4_res5_conv1"
type: "Convolution"
bottom: "conv4_res5_pre"
top: "conv4_res5_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res5_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res5_conv1"
top: "conv4_res5_conv1"
}
layer {
name: "conv4_res5_conv1_scale"
type: "Scale"
bottom: "conv4_res5_conv1"
top: "conv4_res5_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res5_conv1_relu"
type: "ReLU"
bottom: "conv4_res5_conv1"
top: "conv4_res5_conv1"
}
layer {
name: "conv4_res5_conv2"
type: "Convolution"
bottom: "conv4_res5_conv1"
top: "conv4_res5_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res5_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res5_conv2"
top: "conv4_res5_conv2"
}
layer {
name: "conv4_res5_conv2_scale"
type: "Scale"
bottom: "conv4_res5_conv2"
top: "conv4_res5_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res5_conv2_relu"
type: "ReLU"
bottom: "conv4_res5_conv2"
top: "conv4_res5_conv2"
}
layer {
name: "conv4_res5_conv3"
type: "Convolution"
bottom: "conv4_res5_conv2"
top: "conv4_res5_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res5"
type: "Eltwise"
bottom: "conv4_res4"
bottom: "conv4_res5_conv3"
top: "conv4_res5"
}
layer {
name: "conv4_res6_pre_bn"
type: "BatchNorm"
bottom: "conv4_res5"
top: "conv4_res6_pre"
}
layer {
name: "conv4_res6_pre_scale"
type: "Scale"
bottom: "conv4_res6_pre"
top: "conv4_res6_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res6_pre_relu"
type: "ReLU"
bottom: "conv4_res6_pre"
top: "conv4_res6_pre"
}
layer {
name: "conv4_res6_conv1"
type: "Convolution"
bottom: "conv4_res6_pre"
top: "conv4_res6_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res6_conv1_bn"
type: "BatchNorm"
bottom: "conv4_res6_conv1"
top: "conv4_res6_conv1"
}
layer {
name: "conv4_res6_conv1_scale"
type: "Scale"
bottom: "conv4_res6_conv1"
top: "conv4_res6_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res6_conv1_relu"
type: "ReLU"
bottom: "conv4_res6_conv1"
top: "conv4_res6_conv1"
}
layer {
name: "conv4_res6_conv2"
type: "Convolution"
bottom: "conv4_res6_conv1"
top: "conv4_res6_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res6_conv2_bn"
type: "BatchNorm"
bottom: "conv4_res6_conv2"
top: "conv4_res6_conv2"
}
layer {
name: "conv4_res6_conv2_scale"
type: "Scale"
bottom: "conv4_res6_conv2"
top: "conv4_res6_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv4_res6_conv2_relu"
type: "ReLU"
bottom: "conv4_res6_conv2"
top: "conv4_res6_conv2"
}
layer {
name: "conv4_res6_conv3"
type: "Convolution"
bottom: "conv4_res6_conv2"
top: "conv4_res6_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_res6"
type: "Eltwise"
bottom: "conv4_res5"
bottom: "conv4_res6_conv3"
top: "conv4_res6"
}
layer {
name: "conv5_res1_pre_bn"
type: "BatchNorm"
bottom: "conv4_res6"
top: "conv5_res1_pre"
}
layer {
name: "conv5_res1_pre_scale"
type: "Scale"
bottom: "conv5_res1_pre"
top: "conv5_res1_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res1_pre_relu"
type: "ReLU"
bottom: "conv5_res1_pre"
top: "conv5_res1_pre"
}
layer {
name: "conv5_res1_proj"
type: "Convolution"
bottom: "conv5_res1_pre"
top: "conv5_res1_proj"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 2048
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res1_conv1"
type: "Convolution"
bottom: "conv5_res1_pre"
top: "conv5_res1_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res1_conv1_bn"
type: "BatchNorm"
bottom: "conv5_res1_conv1"
top: "conv5_res1_conv1"
}
layer {
name: "conv5_res1_conv1_scale"
type: "Scale"
bottom: "conv5_res1_conv1"
top: "conv5_res1_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res1_conv1_relu"
type: "ReLU"
bottom: "conv5_res1_conv1"
top: "conv5_res1_conv1"
}
layer {
name: "conv5_res1_conv2"
type: "Convolution"
bottom: "conv5_res1_conv1"
top: "conv5_res1_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res1_conv2_bn"
type: "BatchNorm"
bottom: "conv5_res1_conv2"
top: "conv5_res1_conv2"
}
layer {
name: "conv5_res1_conv2_scale"
type: "Scale"
bottom: "conv5_res1_conv2"
top: "conv5_res1_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res1_conv2_relu"
type: "ReLU"
bottom: "conv5_res1_conv2"
top: "conv5_res1_conv2"
}
layer {
name: "conv5_res1_conv3"
type: "Convolution"
bottom: "conv5_res1_conv2"
top: "conv5_res1_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 2048
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res1"
type: "Eltwise"
bottom: "conv5_res1_proj"
bottom: "conv5_res1_conv3"
top: "conv5_res1"
}
layer {
name: "conv5_res2_pre_bn"
type: "BatchNorm"
bottom: "conv5_res1"
top: "conv5_res2_pre"
}
layer {
name: "conv5_res2_pre_scale"
type: "Scale"
bottom: "conv5_res2_pre"
top: "conv5_res2_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res2_pre_relu"
type: "ReLU"
bottom: "conv5_res2_pre"
top: "conv5_res2_pre"
}
layer {
name: "conv5_res2_conv1"
type: "Convolution"
bottom: "conv5_res2_pre"
top: "conv5_res2_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res2_conv1_bn"
type: "BatchNorm"
bottom: "conv5_res2_conv1"
top: "conv5_res2_conv1"
}
layer {
name: "conv5_res2_conv1_scale"
type: "Scale"
bottom: "conv5_res2_conv1"
top: "conv5_res2_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res2_conv1_relu"
type: "ReLU"
bottom: "conv5_res2_conv1"
top: "conv5_res2_conv1"
}
layer {
name: "conv5_res2_conv2"
type: "Convolution"
bottom: "conv5_res2_conv1"
top: "conv5_res2_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res2_conv2_bn"
type: "BatchNorm"
bottom: "conv5_res2_conv2"
top: "conv5_res2_conv2"
}
layer {
name: "conv5_res2_conv2_scale"
type: "Scale"
bottom: "conv5_res2_conv2"
top: "conv5_res2_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res2_conv2_relu"
type: "ReLU"
bottom: "conv5_res2_conv2"
top: "conv5_res2_conv2"
}
layer {
name: "conv5_res2_conv3"
type: "Convolution"
bottom: "conv5_res2_conv2"
top: "conv5_res2_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 2048
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res2"
type: "Eltwise"
bottom: "conv5_res1"
bottom: "conv5_res2_conv3"
top: "conv5_res2"
}
layer {
name: "conv5_res3_pre_bn"
type: "BatchNorm"
bottom: "conv5_res2"
top: "conv5_res3_pre"
}
layer {
name: "conv5_res3_pre_scale"
type: "Scale"
bottom: "conv5_res3_pre"
top: "conv5_res3_pre"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res3_pre_relu"
type: "ReLU"
bottom: "conv5_res3_pre"
top: "conv5_res3_pre"
}
layer {
name: "conv5_res3_conv1"
type: "Convolution"
bottom: "conv5_res3_pre"
top: "conv5_res3_conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res3_conv1_bn"
type: "BatchNorm"
bottom: "conv5_res3_conv1"
top: "conv5_res3_conv1"
}
layer {
name: "conv5_res3_conv1_scale"
type: "Scale"
bottom: "conv5_res3_conv1"
top: "conv5_res3_conv1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res3_conv1_relu"
type: "ReLU"
bottom: "conv5_res3_conv1"
top: "conv5_res3_conv1"
}
layer {
name: "conv5_res3_conv2"
type: "Convolution"
bottom: "conv5_res3_conv1"
top: "conv5_res3_conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res3_conv2_bn"
type: "BatchNorm"
bottom: "conv5_res3_conv2"
top: "conv5_res3_conv2"
}
layer {
name: "conv5_res3_conv2_scale"
type: "Scale"
bottom: "conv5_res3_conv2"
top: "conv5_res3_conv2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_res3_conv2_relu"
type: "ReLU"
bottom: "conv5_res3_conv2"
top: "conv5_res3_conv2"
}
layer {
name: "conv5_res3_conv3"
type: "Convolution"
bottom: "conv5_res3_conv2"
top: "conv5_res3_conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 2048
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_res3"
type: "Eltwise"
bottom: "conv5_res2"
bottom: "conv5_res3_conv3"
top: "conv5_res3"
}
layer {
name: "conv5_bn"
type: "BatchNorm"
bottom: "conv5_res3"
top: "conv5"
}
layer {
name: "conv5_scale"
type: "Scale"
bottom: "conv5"
top: "conv5"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 1
}
}
}
layer {
name: "conv5_relu"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
pad: 0
}
}
layer {
name: "fc"
type: "InnerProduct"
bottom: "pool5"
top: "fc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 1000
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc"
bottom: "label"
top: "loss"
}
layer {
name: "accuracy_top1"
type: "Accuracy"
bottom: "fc"
bottom: "label"
top: "accuracy_top1"
include {
phase: TEST
}
accuracy_param {
top_k: 1
}
}
layer {
name: "accuracy_top5"
type: "Accuracy"
bottom: "fc"
bottom: "label"
top: "accuracy_top5"
include {
phase: TEST
}
accuracy_param {
top_k: 5
}
}
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