shicai
8/30/2017 - 8:52 AM
Caffe implementation of Squeeze-and-Excitation Networks (SENet)
Caffe implementation of Squeeze-and-Excitation Networks (SENet)
name: "SE_RESNET_50_V1"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 225
dim: 225
}
# transform_param {
# scale: 0.017
# mirror: false
# crop_size: 225
# mean_value: [103.94,116.78,123.68]
# }
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
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"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv1/scale"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
bias_term: true
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2_1/prj"
type: "Convolution"
bottom: "pool1"
top: "conv2_1/prj"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/prj/bn"
type: "BatchNorm"
bottom: "conv2_1/prj"
top: "conv2_1/prj"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_1/prj/scale"
type: "Scale"
bottom: "conv2_1/prj"
top: "conv2_1/prj"
scale_param {
bias_term: true
}
}
layer {
name: "conv2_1/x1"
type: "Convolution"
bottom: "pool1"
top: "conv2_1/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/x1/bn"
type: "BatchNorm"
bottom: "conv2_1/x1"
top: "conv2_1/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_1/x1/scale"
type: "Scale"
bottom: "conv2_1/x1"
top: "conv2_1/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_1/x1"
type: "ReLU"
bottom: "conv2_1/x1"
top: "conv2_1/x1"
}
layer {
name: "conv2_1/x2"
type: "Convolution"
bottom: "conv2_1/x1"
top: "conv2_1/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/x2/bn"
type: "BatchNorm"
bottom: "conv2_1/x2"
top: "conv2_1/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_1/x2/scale"
type: "Scale"
bottom: "conv2_1/x2"
top: "conv2_1/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_1/x2"
type: "ReLU"
bottom: "conv2_1/x2"
top: "conv2_1/x2"
}
layer {
name: "conv2_1/x3"
type: "Convolution"
bottom: "conv2_1/x2"
top: "conv2_1/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/x3/bn"
type: "BatchNorm"
bottom: "conv2_1/x3"
top: "conv2_1/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_1/x3/scale"
type: "Scale"
bottom: "conv2_1/x3"
top: "conv2_1/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool2_1/gap"
type: "Pooling"
bottom: "conv2_1/x3"
top: "pool2_1/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc2_1/sqz"
type: "InnerProduct"
bottom: "pool2_1/gap"
top: "fc2_1/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 16
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu2_1/sqz"
type: "ReLU"
bottom: "fc2_1/sqz"
top: "fc2_1/sqz"
}
layer {
name: "fc2_1/exc"
type: "InnerProduct"
bottom: "fc2_1/sqz"
top: "fc2_1/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 256
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm2_1/gate"
type: "Sigmoid"
bottom: "fc2_1/exc"
top: "fc2_1/exc"
}
layer {
name: "scale2_1"
type: "Scale"
bottom: "conv2_1/x3"
bottom: "fc2_1/exc"
top: "scale2_1"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_2_1"
type: "Eltwise"
bottom: "conv2_1/prj"
bottom: "scale2_1"
top: "block_2_1"
}
layer {
name: "relu2_1"
type: "ReLU"
bottom: "block_2_1"
top: "block_2_1"
}
layer {
name: "conv2_2/x1"
type: "Convolution"
bottom: "block_2_1"
top: "conv2_2/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_2/x1/bn"
type: "BatchNorm"
bottom: "conv2_2/x1"
top: "conv2_2/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_2/x1/scale"
type: "Scale"
bottom: "conv2_2/x1"
top: "conv2_2/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_2/x1"
type: "ReLU"
bottom: "conv2_2/x1"
top: "conv2_2/x1"
}
layer {
name: "conv2_2/x2"
type: "Convolution"
bottom: "conv2_2/x1"
top: "conv2_2/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_2/x2/bn"
type: "BatchNorm"
bottom: "conv2_2/x2"
top: "conv2_2/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_2/x2/scale"
type: "Scale"
bottom: "conv2_2/x2"
top: "conv2_2/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_2/x2"
type: "ReLU"
bottom: "conv2_2/x2"
top: "conv2_2/x2"
}
layer {
name: "conv2_2/x3"
type: "Convolution"
bottom: "conv2_2/x2"
top: "conv2_2/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_2/x3/bn"
type: "BatchNorm"
bottom: "conv2_2/x3"
top: "conv2_2/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_2/x3/scale"
type: "Scale"
bottom: "conv2_2/x3"
top: "conv2_2/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool2_2/gap"
type: "Pooling"
bottom: "conv2_2/x3"
top: "pool2_2/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc2_2/sqz"
type: "InnerProduct"
bottom: "pool2_2/gap"
top: "fc2_2/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 16
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu2_2/sqz"
type: "ReLU"
bottom: "fc2_2/sqz"
top: "fc2_2/sqz"
}
layer {
name: "fc2_2/exc"
type: "InnerProduct"
bottom: "fc2_2/sqz"
top: "fc2_2/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 256
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm2_2/gate"
type: "Sigmoid"
bottom: "fc2_2/exc"
top: "fc2_2/exc"
}
layer {
name: "scale2_2"
type: "Scale"
bottom: "conv2_2/x3"
bottom: "fc2_2/exc"
top: "scale2_2"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_2_2"
type: "Eltwise"
bottom: "block_2_1"
bottom: "scale2_2"
top: "block_2_2"
}
layer {
name: "relu2_2"
type: "ReLU"
bottom: "block_2_2"
top: "block_2_2"
}
layer {
name: "conv2_3/x1"
type: "Convolution"
bottom: "block_2_2"
top: "conv2_3/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_3/x1/bn"
type: "BatchNorm"
bottom: "conv2_3/x1"
top: "conv2_3/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_3/x1/scale"
type: "Scale"
bottom: "conv2_3/x1"
top: "conv2_3/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_3/x1"
type: "ReLU"
bottom: "conv2_3/x1"
top: "conv2_3/x1"
}
layer {
name: "conv2_3/x2"
type: "Convolution"
bottom: "conv2_3/x1"
top: "conv2_3/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_3/x2/bn"
type: "BatchNorm"
bottom: "conv2_3/x2"
top: "conv2_3/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_3/x2/scale"
type: "Scale"
bottom: "conv2_3/x2"
top: "conv2_3/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu2_3/x2"
type: "ReLU"
bottom: "conv2_3/x2"
top: "conv2_3/x2"
}
layer {
name: "conv2_3/x3"
type: "Convolution"
bottom: "conv2_3/x2"
top: "conv2_3/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_3/x3/bn"
type: "BatchNorm"
bottom: "conv2_3/x3"
top: "conv2_3/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv2_3/x3/scale"
type: "Scale"
bottom: "conv2_3/x3"
top: "conv2_3/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool2_3/gap"
type: "Pooling"
bottom: "conv2_3/x3"
top: "pool2_3/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc2_3/sqz"
type: "InnerProduct"
bottom: "pool2_3/gap"
top: "fc2_3/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 16
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu2_3/sqz"
type: "ReLU"
bottom: "fc2_3/sqz"
top: "fc2_3/sqz"
}
layer {
name: "fc2_3/exc"
type: "InnerProduct"
bottom: "fc2_3/sqz"
top: "fc2_3/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 256
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm2_3/gate"
type: "Sigmoid"
bottom: "fc2_3/exc"
top: "fc2_3/exc"
}
layer {
name: "scale2_3"
type: "Scale"
bottom: "conv2_3/x3"
bottom: "fc2_3/exc"
top: "scale2_3"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_2_3"
type: "Eltwise"
bottom: "block_2_2"
bottom: "scale2_3"
top: "block_2_3"
}
layer {
name: "relu2_3"
type: "ReLU"
bottom: "block_2_3"
top: "block_2_3"
}
layer {
name: "conv3_1/prj"
type: "Convolution"
bottom: "block_2_3"
top: "conv3_1/prj"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/prj/bn"
type: "BatchNorm"
bottom: "conv3_1/prj"
top: "conv3_1/prj"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_1/prj/scale"
type: "Scale"
bottom: "conv3_1/prj"
top: "conv3_1/prj"
scale_param {
bias_term: true
}
}
layer {
name: "conv3_1/x1"
type: "Convolution"
bottom: "block_2_3"
top: "conv3_1/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/x1/bn"
type: "BatchNorm"
bottom: "conv3_1/x1"
top: "conv3_1/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_1/x1/scale"
type: "Scale"
bottom: "conv3_1/x1"
top: "conv3_1/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_1/x1"
type: "ReLU"
bottom: "conv3_1/x1"
top: "conv3_1/x1"
}
layer {
name: "conv3_1/x2"
type: "Convolution"
bottom: "conv3_1/x1"
top: "conv3_1/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/x2/bn"
type: "BatchNorm"
bottom: "conv3_1/x2"
top: "conv3_1/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_1/x2/scale"
type: "Scale"
bottom: "conv3_1/x2"
top: "conv3_1/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_1/x2"
type: "ReLU"
bottom: "conv3_1/x2"
top: "conv3_1/x2"
}
layer {
name: "conv3_1/x3"
type: "Convolution"
bottom: "conv3_1/x2"
top: "conv3_1/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/x3/bn"
type: "BatchNorm"
bottom: "conv3_1/x3"
top: "conv3_1/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_1/x3/scale"
type: "Scale"
bottom: "conv3_1/x3"
top: "conv3_1/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool3_1/gap"
type: "Pooling"
bottom: "conv3_1/x3"
top: "pool3_1/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc3_1/sqz"
type: "InnerProduct"
bottom: "pool3_1/gap"
top: "fc3_1/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu3_1/sqz"
type: "ReLU"
bottom: "fc3_1/sqz"
top: "fc3_1/sqz"
}
layer {
name: "fc3_1/exc"
type: "InnerProduct"
bottom: "fc3_1/sqz"
top: "fc3_1/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm3_1/gate"
type: "Sigmoid"
bottom: "fc3_1/exc"
top: "fc3_1/exc"
}
layer {
name: "scale3_1"
type: "Scale"
bottom: "conv3_1/x3"
bottom: "fc3_1/exc"
top: "scale3_1"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_3_1"
type: "Eltwise"
bottom: "conv3_1/prj"
bottom: "scale3_1"
top: "block_3_1"
}
layer {
name: "relu3_1"
type: "ReLU"
bottom: "block_3_1"
top: "block_3_1"
}
layer {
name: "conv3_2/x1"
type: "Convolution"
bottom: "block_3_1"
top: "conv3_2/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_2/x1/bn"
type: "BatchNorm"
bottom: "conv3_2/x1"
top: "conv3_2/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_2/x1/scale"
type: "Scale"
bottom: "conv3_2/x1"
top: "conv3_2/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_2/x1"
type: "ReLU"
bottom: "conv3_2/x1"
top: "conv3_2/x1"
}
layer {
name: "conv3_2/x2"
type: "Convolution"
bottom: "conv3_2/x1"
top: "conv3_2/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_2/x2/bn"
type: "BatchNorm"
bottom: "conv3_2/x2"
top: "conv3_2/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_2/x2/scale"
type: "Scale"
bottom: "conv3_2/x2"
top: "conv3_2/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_2/x2"
type: "ReLU"
bottom: "conv3_2/x2"
top: "conv3_2/x2"
}
layer {
name: "conv3_2/x3"
type: "Convolution"
bottom: "conv3_2/x2"
top: "conv3_2/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_2/x3/bn"
type: "BatchNorm"
bottom: "conv3_2/x3"
top: "conv3_2/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_2/x3/scale"
type: "Scale"
bottom: "conv3_2/x3"
top: "conv3_2/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool3_2/gap"
type: "Pooling"
bottom: "conv3_2/x3"
top: "pool3_2/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc3_2/sqz"
type: "InnerProduct"
bottom: "pool3_2/gap"
top: "fc3_2/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu3_2/sqz"
type: "ReLU"
bottom: "fc3_2/sqz"
top: "fc3_2/sqz"
}
layer {
name: "fc3_2/exc"
type: "InnerProduct"
bottom: "fc3_2/sqz"
top: "fc3_2/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm3_2/gate"
type: "Sigmoid"
bottom: "fc3_2/exc"
top: "fc3_2/exc"
}
layer {
name: "scale3_2"
type: "Scale"
bottom: "conv3_2/x3"
bottom: "fc3_2/exc"
top: "scale3_2"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_3_2"
type: "Eltwise"
bottom: "block_3_1"
bottom: "scale3_2"
top: "block_3_2"
}
layer {
name: "relu3_2"
type: "ReLU"
bottom: "block_3_2"
top: "block_3_2"
}
layer {
name: "conv3_3/x1"
type: "Convolution"
bottom: "block_3_2"
top: "conv3_3/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_3/x1/bn"
type: "BatchNorm"
bottom: "conv3_3/x1"
top: "conv3_3/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_3/x1/scale"
type: "Scale"
bottom: "conv3_3/x1"
top: "conv3_3/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_3/x1"
type: "ReLU"
bottom: "conv3_3/x1"
top: "conv3_3/x1"
}
layer {
name: "conv3_3/x2"
type: "Convolution"
bottom: "conv3_3/x1"
top: "conv3_3/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_3/x2/bn"
type: "BatchNorm"
bottom: "conv3_3/x2"
top: "conv3_3/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_3/x2/scale"
type: "Scale"
bottom: "conv3_3/x2"
top: "conv3_3/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_3/x2"
type: "ReLU"
bottom: "conv3_3/x2"
top: "conv3_3/x2"
}
layer {
name: "conv3_3/x3"
type: "Convolution"
bottom: "conv3_3/x2"
top: "conv3_3/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_3/x3/bn"
type: "BatchNorm"
bottom: "conv3_3/x3"
top: "conv3_3/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_3/x3/scale"
type: "Scale"
bottom: "conv3_3/x3"
top: "conv3_3/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool3_3/gap"
type: "Pooling"
bottom: "conv3_3/x3"
top: "pool3_3/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc3_3/sqz"
type: "InnerProduct"
bottom: "pool3_3/gap"
top: "fc3_3/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu3_3/sqz"
type: "ReLU"
bottom: "fc3_3/sqz"
top: "fc3_3/sqz"
}
layer {
name: "fc3_3/exc"
type: "InnerProduct"
bottom: "fc3_3/sqz"
top: "fc3_3/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm3_3/gate"
type: "Sigmoid"
bottom: "fc3_3/exc"
top: "fc3_3/exc"
}
layer {
name: "scale3_3"
type: "Scale"
bottom: "conv3_3/x3"
bottom: "fc3_3/exc"
top: "scale3_3"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_3_3"
type: "Eltwise"
bottom: "block_3_2"
bottom: "scale3_3"
top: "block_3_3"
}
layer {
name: "relu3_3"
type: "ReLU"
bottom: "block_3_3"
top: "block_3_3"
}
layer {
name: "conv3_4/x1"
type: "Convolution"
bottom: "block_3_3"
top: "conv3_4/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_4/x1/bn"
type: "BatchNorm"
bottom: "conv3_4/x1"
top: "conv3_4/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_4/x1/scale"
type: "Scale"
bottom: "conv3_4/x1"
top: "conv3_4/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_4/x1"
type: "ReLU"
bottom: "conv3_4/x1"
top: "conv3_4/x1"
}
layer {
name: "conv3_4/x2"
type: "Convolution"
bottom: "conv3_4/x1"
top: "conv3_4/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_4/x2/bn"
type: "BatchNorm"
bottom: "conv3_4/x2"
top: "conv3_4/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_4/x2/scale"
type: "Scale"
bottom: "conv3_4/x2"
top: "conv3_4/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu3_4/x2"
type: "ReLU"
bottom: "conv3_4/x2"
top: "conv3_4/x2"
}
layer {
name: "conv3_4/x3"
type: "Convolution"
bottom: "conv3_4/x2"
top: "conv3_4/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_4/x3/bn"
type: "BatchNorm"
bottom: "conv3_4/x3"
top: "conv3_4/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv3_4/x3/scale"
type: "Scale"
bottom: "conv3_4/x3"
top: "conv3_4/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool3_4/gap"
type: "Pooling"
bottom: "conv3_4/x3"
top: "pool3_4/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc3_4/sqz"
type: "InnerProduct"
bottom: "pool3_4/gap"
top: "fc3_4/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu3_4/sqz"
type: "ReLU"
bottom: "fc3_4/sqz"
top: "fc3_4/sqz"
}
layer {
name: "fc3_4/exc"
type: "InnerProduct"
bottom: "fc3_4/sqz"
top: "fc3_4/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm3_4/gate"
type: "Sigmoid"
bottom: "fc3_4/exc"
top: "fc3_4/exc"
}
layer {
name: "scale3_4"
type: "Scale"
bottom: "conv3_4/x3"
bottom: "fc3_4/exc"
top: "scale3_4"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_3_4"
type: "Eltwise"
bottom: "block_3_3"
bottom: "scale3_4"
top: "block_3_4"
}
layer {
name: "relu3_4"
type: "ReLU"
bottom: "block_3_4"
top: "block_3_4"
}
layer {
name: "conv4_1/prj"
type: "Convolution"
bottom: "block_3_4"
top: "conv4_1/prj"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/prj/bn"
type: "BatchNorm"
bottom: "conv4_1/prj"
top: "conv4_1/prj"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_1/prj/scale"
type: "Scale"
bottom: "conv4_1/prj"
top: "conv4_1/prj"
scale_param {
bias_term: true
}
}
layer {
name: "conv4_1/x1"
type: "Convolution"
bottom: "block_3_4"
top: "conv4_1/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/x1/bn"
type: "BatchNorm"
bottom: "conv4_1/x1"
top: "conv4_1/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_1/x1/scale"
type: "Scale"
bottom: "conv4_1/x1"
top: "conv4_1/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_1/x1"
type: "ReLU"
bottom: "conv4_1/x1"
top: "conv4_1/x1"
}
layer {
name: "conv4_1/x2"
type: "Convolution"
bottom: "conv4_1/x1"
top: "conv4_1/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/x2/bn"
type: "BatchNorm"
bottom: "conv4_1/x2"
top: "conv4_1/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_1/x2/scale"
type: "Scale"
bottom: "conv4_1/x2"
top: "conv4_1/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_1/x2"
type: "ReLU"
bottom: "conv4_1/x2"
top: "conv4_1/x2"
}
layer {
name: "conv4_1/x3"
type: "Convolution"
bottom: "conv4_1/x2"
top: "conv4_1/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/x3/bn"
type: "BatchNorm"
bottom: "conv4_1/x3"
top: "conv4_1/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_1/x3/scale"
type: "Scale"
bottom: "conv4_1/x3"
top: "conv4_1/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_1/gap"
type: "Pooling"
bottom: "conv4_1/x3"
top: "pool4_1/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_1/sqz"
type: "InnerProduct"
bottom: "pool4_1/gap"
top: "fc4_1/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_1/sqz"
type: "ReLU"
bottom: "fc4_1/sqz"
top: "fc4_1/sqz"
}
layer {
name: "fc4_1/exc"
type: "InnerProduct"
bottom: "fc4_1/sqz"
top: "fc4_1/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_1/gate"
type: "Sigmoid"
bottom: "fc4_1/exc"
top: "fc4_1/exc"
}
layer {
name: "scale4_1"
type: "Scale"
bottom: "conv4_1/x3"
bottom: "fc4_1/exc"
top: "scale4_1"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_1"
type: "Eltwise"
bottom: "conv4_1/prj"
bottom: "scale4_1"
top: "block_4_1"
}
layer {
name: "relu4_1"
type: "ReLU"
bottom: "block_4_1"
top: "block_4_1"
}
layer {
name: "conv4_2/x1"
type: "Convolution"
bottom: "block_4_1"
top: "conv4_2/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_2/x1/bn"
type: "BatchNorm"
bottom: "conv4_2/x1"
top: "conv4_2/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_2/x1/scale"
type: "Scale"
bottom: "conv4_2/x1"
top: "conv4_2/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_2/x1"
type: "ReLU"
bottom: "conv4_2/x1"
top: "conv4_2/x1"
}
layer {
name: "conv4_2/x2"
type: "Convolution"
bottom: "conv4_2/x1"
top: "conv4_2/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_2/x2/bn"
type: "BatchNorm"
bottom: "conv4_2/x2"
top: "conv4_2/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_2/x2/scale"
type: "Scale"
bottom: "conv4_2/x2"
top: "conv4_2/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_2/x2"
type: "ReLU"
bottom: "conv4_2/x2"
top: "conv4_2/x2"
}
layer {
name: "conv4_2/x3"
type: "Convolution"
bottom: "conv4_2/x2"
top: "conv4_2/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_2/x3/bn"
type: "BatchNorm"
bottom: "conv4_2/x3"
top: "conv4_2/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_2/x3/scale"
type: "Scale"
bottom: "conv4_2/x3"
top: "conv4_2/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_2/gap"
type: "Pooling"
bottom: "conv4_2/x3"
top: "pool4_2/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_2/sqz"
type: "InnerProduct"
bottom: "pool4_2/gap"
top: "fc4_2/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_2/sqz"
type: "ReLU"
bottom: "fc4_2/sqz"
top: "fc4_2/sqz"
}
layer {
name: "fc4_2/exc"
type: "InnerProduct"
bottom: "fc4_2/sqz"
top: "fc4_2/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_2/gate"
type: "Sigmoid"
bottom: "fc4_2/exc"
top: "fc4_2/exc"
}
layer {
name: "scale4_2"
type: "Scale"
bottom: "conv4_2/x3"
bottom: "fc4_2/exc"
top: "scale4_2"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_2"
type: "Eltwise"
bottom: "block_4_1"
bottom: "scale4_2"
top: "block_4_2"
}
layer {
name: "relu4_2"
type: "ReLU"
bottom: "block_4_2"
top: "block_4_2"
}
layer {
name: "conv4_3/x1"
type: "Convolution"
bottom: "block_4_2"
top: "conv4_3/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_3/x1/bn"
type: "BatchNorm"
bottom: "conv4_3/x1"
top: "conv4_3/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_3/x1/scale"
type: "Scale"
bottom: "conv4_3/x1"
top: "conv4_3/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_3/x1"
type: "ReLU"
bottom: "conv4_3/x1"
top: "conv4_3/x1"
}
layer {
name: "conv4_3/x2"
type: "Convolution"
bottom: "conv4_3/x1"
top: "conv4_3/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_3/x2/bn"
type: "BatchNorm"
bottom: "conv4_3/x2"
top: "conv4_3/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_3/x2/scale"
type: "Scale"
bottom: "conv4_3/x2"
top: "conv4_3/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_3/x2"
type: "ReLU"
bottom: "conv4_3/x2"
top: "conv4_3/x2"
}
layer {
name: "conv4_3/x3"
type: "Convolution"
bottom: "conv4_3/x2"
top: "conv4_3/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_3/x3/bn"
type: "BatchNorm"
bottom: "conv4_3/x3"
top: "conv4_3/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_3/x3/scale"
type: "Scale"
bottom: "conv4_3/x3"
top: "conv4_3/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_3/gap"
type: "Pooling"
bottom: "conv4_3/x3"
top: "pool4_3/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_3/sqz"
type: "InnerProduct"
bottom: "pool4_3/gap"
top: "fc4_3/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_3/sqz"
type: "ReLU"
bottom: "fc4_3/sqz"
top: "fc4_3/sqz"
}
layer {
name: "fc4_3/exc"
type: "InnerProduct"
bottom: "fc4_3/sqz"
top: "fc4_3/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_3/gate"
type: "Sigmoid"
bottom: "fc4_3/exc"
top: "fc4_3/exc"
}
layer {
name: "scale4_3"
type: "Scale"
bottom: "conv4_3/x3"
bottom: "fc4_3/exc"
top: "scale4_3"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_3"
type: "Eltwise"
bottom: "block_4_2"
bottom: "scale4_3"
top: "block_4_3"
}
layer {
name: "relu4_3"
type: "ReLU"
bottom: "block_4_3"
top: "block_4_3"
}
layer {
name: "conv4_4/x1"
type: "Convolution"
bottom: "block_4_3"
top: "conv4_4/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_4/x1/bn"
type: "BatchNorm"
bottom: "conv4_4/x1"
top: "conv4_4/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_4/x1/scale"
type: "Scale"
bottom: "conv4_4/x1"
top: "conv4_4/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_4/x1"
type: "ReLU"
bottom: "conv4_4/x1"
top: "conv4_4/x1"
}
layer {
name: "conv4_4/x2"
type: "Convolution"
bottom: "conv4_4/x1"
top: "conv4_4/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_4/x2/bn"
type: "BatchNorm"
bottom: "conv4_4/x2"
top: "conv4_4/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_4/x2/scale"
type: "Scale"
bottom: "conv4_4/x2"
top: "conv4_4/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_4/x2"
type: "ReLU"
bottom: "conv4_4/x2"
top: "conv4_4/x2"
}
layer {
name: "conv4_4/x3"
type: "Convolution"
bottom: "conv4_4/x2"
top: "conv4_4/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_4/x3/bn"
type: "BatchNorm"
bottom: "conv4_4/x3"
top: "conv4_4/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_4/x3/scale"
type: "Scale"
bottom: "conv4_4/x3"
top: "conv4_4/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_4/gap"
type: "Pooling"
bottom: "conv4_4/x3"
top: "pool4_4/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_4/sqz"
type: "InnerProduct"
bottom: "pool4_4/gap"
top: "fc4_4/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_4/sqz"
type: "ReLU"
bottom: "fc4_4/sqz"
top: "fc4_4/sqz"
}
layer {
name: "fc4_4/exc"
type: "InnerProduct"
bottom: "fc4_4/sqz"
top: "fc4_4/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_4/gate"
type: "Sigmoid"
bottom: "fc4_4/exc"
top: "fc4_4/exc"
}
layer {
name: "scale4_4"
type: "Scale"
bottom: "conv4_4/x3"
bottom: "fc4_4/exc"
top: "scale4_4"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_4"
type: "Eltwise"
bottom: "block_4_3"
bottom: "scale4_4"
top: "block_4_4"
}
layer {
name: "relu4_4"
type: "ReLU"
bottom: "block_4_4"
top: "block_4_4"
}
layer {
name: "conv4_5/x1"
type: "Convolution"
bottom: "block_4_4"
top: "conv4_5/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_5/x1/bn"
type: "BatchNorm"
bottom: "conv4_5/x1"
top: "conv4_5/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_5/x1/scale"
type: "Scale"
bottom: "conv4_5/x1"
top: "conv4_5/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_5/x1"
type: "ReLU"
bottom: "conv4_5/x1"
top: "conv4_5/x1"
}
layer {
name: "conv4_5/x2"
type: "Convolution"
bottom: "conv4_5/x1"
top: "conv4_5/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_5/x2/bn"
type: "BatchNorm"
bottom: "conv4_5/x2"
top: "conv4_5/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_5/x2/scale"
type: "Scale"
bottom: "conv4_5/x2"
top: "conv4_5/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_5/x2"
type: "ReLU"
bottom: "conv4_5/x2"
top: "conv4_5/x2"
}
layer {
name: "conv4_5/x3"
type: "Convolution"
bottom: "conv4_5/x2"
top: "conv4_5/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_5/x3/bn"
type: "BatchNorm"
bottom: "conv4_5/x3"
top: "conv4_5/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_5/x3/scale"
type: "Scale"
bottom: "conv4_5/x3"
top: "conv4_5/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_5/gap"
type: "Pooling"
bottom: "conv4_5/x3"
top: "pool4_5/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_5/sqz"
type: "InnerProduct"
bottom: "pool4_5/gap"
top: "fc4_5/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_5/sqz"
type: "ReLU"
bottom: "fc4_5/sqz"
top: "fc4_5/sqz"
}
layer {
name: "fc4_5/exc"
type: "InnerProduct"
bottom: "fc4_5/sqz"
top: "fc4_5/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_5/gate"
type: "Sigmoid"
bottom: "fc4_5/exc"
top: "fc4_5/exc"
}
layer {
name: "scale4_5"
type: "Scale"
bottom: "conv4_5/x3"
bottom: "fc4_5/exc"
top: "scale4_5"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_5"
type: "Eltwise"
bottom: "block_4_4"
bottom: "scale4_5"
top: "block_4_5"
}
layer {
name: "relu4_5"
type: "ReLU"
bottom: "block_4_5"
top: "block_4_5"
}
layer {
name: "conv4_6/x1"
type: "Convolution"
bottom: "block_4_5"
top: "conv4_6/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_6/x1/bn"
type: "BatchNorm"
bottom: "conv4_6/x1"
top: "conv4_6/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_6/x1/scale"
type: "Scale"
bottom: "conv4_6/x1"
top: "conv4_6/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_6/x1"
type: "ReLU"
bottom: "conv4_6/x1"
top: "conv4_6/x1"
}
layer {
name: "conv4_6/x2"
type: "Convolution"
bottom: "conv4_6/x1"
top: "conv4_6/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_6/x2/bn"
type: "BatchNorm"
bottom: "conv4_6/x2"
top: "conv4_6/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_6/x2/scale"
type: "Scale"
bottom: "conv4_6/x2"
top: "conv4_6/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu4_6/x2"
type: "ReLU"
bottom: "conv4_6/x2"
top: "conv4_6/x2"
}
layer {
name: "conv4_6/x3"
type: "Convolution"
bottom: "conv4_6/x2"
top: "conv4_6/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_6/x3/bn"
type: "BatchNorm"
bottom: "conv4_6/x3"
top: "conv4_6/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv4_6/x3/scale"
type: "Scale"
bottom: "conv4_6/x3"
top: "conv4_6/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool4_6/gap"
type: "Pooling"
bottom: "conv4_6/x3"
top: "pool4_6/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc4_6/sqz"
type: "InnerProduct"
bottom: "pool4_6/gap"
top: "fc4_6/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 64
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu4_6/sqz"
type: "ReLU"
bottom: "fc4_6/sqz"
top: "fc4_6/sqz"
}
layer {
name: "fc4_6/exc"
type: "InnerProduct"
bottom: "fc4_6/sqz"
top: "fc4_6/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm4_6/gate"
type: "Sigmoid"
bottom: "fc4_6/exc"
top: "fc4_6/exc"
}
layer {
name: "scale4_6"
type: "Scale"
bottom: "conv4_6/x3"
bottom: "fc4_6/exc"
top: "scale4_6"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_4_6"
type: "Eltwise"
bottom: "block_4_5"
bottom: "scale4_6"
top: "block_4_6"
}
layer {
name: "relu4_6"
type: "ReLU"
bottom: "block_4_6"
top: "block_4_6"
}
layer {
name: "conv5_1/prj"
type: "Convolution"
bottom: "block_4_6"
top: "conv5_1/prj"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 2048
bias_term: false
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/prj/bn"
type: "BatchNorm"
bottom: "conv5_1/prj"
top: "conv5_1/prj"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_1/prj/scale"
type: "Scale"
bottom: "conv5_1/prj"
top: "conv5_1/prj"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_1/x1"
type: "Convolution"
bottom: "block_4_6"
top: "conv5_1/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/x1/bn"
type: "BatchNorm"
bottom: "conv5_1/x1"
top: "conv5_1/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_1/x1/scale"
type: "Scale"
bottom: "conv5_1/x1"
top: "conv5_1/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_1/x1"
type: "ReLU"
bottom: "conv5_1/x1"
top: "conv5_1/x1"
}
layer {
name: "conv5_1/x2"
type: "Convolution"
bottom: "conv5_1/x1"
top: "conv5_1/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/x2/bn"
type: "BatchNorm"
bottom: "conv5_1/x2"
top: "conv5_1/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_1/x2/scale"
type: "Scale"
bottom: "conv5_1/x2"
top: "conv5_1/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_1/x2"
type: "ReLU"
bottom: "conv5_1/x2"
top: "conv5_1/x2"
}
layer {
name: "conv5_1/x3"
type: "Convolution"
bottom: "conv5_1/x2"
top: "conv5_1/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 2048
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/x3/bn"
type: "BatchNorm"
bottom: "conv5_1/x3"
top: "conv5_1/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_1/x3/scale"
type: "Scale"
bottom: "conv5_1/x3"
top: "conv5_1/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool5_1/gap"
type: "Pooling"
bottom: "conv5_1/x3"
top: "pool5_1/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc5_1/sqz"
type: "InnerProduct"
bottom: "pool5_1/gap"
top: "fc5_1/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu5_1/sqz"
type: "ReLU"
bottom: "fc5_1/sqz"
top: "fc5_1/sqz"
}
layer {
name: "fc5_1/exc"
type: "InnerProduct"
bottom: "fc5_1/sqz"
top: "fc5_1/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 2048
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm5_1/gate"
type: "Sigmoid"
bottom: "fc5_1/exc"
top: "fc5_1/exc"
}
layer {
name: "scale5_1"
type: "Scale"
bottom: "conv5_1/x3"
bottom: "fc5_1/exc"
top: "scale5_1"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_5_1"
type: "Eltwise"
bottom: "conv5_1/prj"
bottom: "scale5_1"
top: "block_5_1"
}
layer {
name: "relu5_1"
type: "ReLU"
bottom: "block_5_1"
top: "block_5_1"
}
layer {
name: "conv5_2/x1"
type: "Convolution"
bottom: "block_5_1"
top: "conv5_2/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_2/x1/bn"
type: "BatchNorm"
bottom: "conv5_2/x1"
top: "conv5_2/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_2/x1/scale"
type: "Scale"
bottom: "conv5_2/x1"
top: "conv5_2/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_2/x1"
type: "ReLU"
bottom: "conv5_2/x1"
top: "conv5_2/x1"
}
layer {
name: "conv5_2/x2"
type: "Convolution"
bottom: "conv5_2/x1"
top: "conv5_2/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_2/x2/bn"
type: "BatchNorm"
bottom: "conv5_2/x2"
top: "conv5_2/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_2/x2/scale"
type: "Scale"
bottom: "conv5_2/x2"
top: "conv5_2/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_2/x2"
type: "ReLU"
bottom: "conv5_2/x2"
top: "conv5_2/x2"
}
layer {
name: "conv5_2/x3"
type: "Convolution"
bottom: "conv5_2/x2"
top: "conv5_2/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 2048
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_2/x3/bn"
type: "BatchNorm"
bottom: "conv5_2/x3"
top: "conv5_2/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_2/x3/scale"
type: "Scale"
bottom: "conv5_2/x3"
top: "conv5_2/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool5_2/gap"
type: "Pooling"
bottom: "conv5_2/x3"
top: "pool5_2/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc5_2/sqz"
type: "InnerProduct"
bottom: "pool5_2/gap"
top: "fc5_2/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu5_2/sqz"
type: "ReLU"
bottom: "fc5_2/sqz"
top: "fc5_2/sqz"
}
layer {
name: "fc5_2/exc"
type: "InnerProduct"
bottom: "fc5_2/sqz"
top: "fc5_2/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 2048
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm5_2/gate"
type: "Sigmoid"
bottom: "fc5_2/exc"
top: "fc5_2/exc"
}
layer {
name: "scale5_2"
type: "Scale"
bottom: "conv5_2/x3"
bottom: "fc5_2/exc"
top: "scale5_2"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_5_2"
type: "Eltwise"
bottom: "block_5_1"
bottom: "scale5_2"
top: "block_5_2"
}
layer {
name: "relu5_2"
type: "ReLU"
bottom: "block_5_2"
top: "block_5_2"
}
layer {
name: "conv5_3/x1"
type: "Convolution"
bottom: "block_5_2"
top: "conv5_3/x1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_3/x1/bn"
type: "BatchNorm"
bottom: "conv5_3/x1"
top: "conv5_3/x1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_3/x1/scale"
type: "Scale"
bottom: "conv5_3/x1"
top: "conv5_3/x1"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_3/x1"
type: "ReLU"
bottom: "conv5_3/x1"
top: "conv5_3/x1"
}
layer {
name: "conv5_3/x2"
type: "Convolution"
bottom: "conv5_3/x1"
top: "conv5_3/x2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_3/x2/bn"
type: "BatchNorm"
bottom: "conv5_3/x2"
top: "conv5_3/x2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_3/x2/scale"
type: "Scale"
bottom: "conv5_3/x2"
top: "conv5_3/x2"
scale_param {
bias_term: true
}
}
layer {
name: "relu5_3/x2"
type: "ReLU"
bottom: "conv5_3/x2"
top: "conv5_3/x2"
}
layer {
name: "conv5_3/x3"
type: "Convolution"
bottom: "conv5_3/x2"
top: "conv5_3/x3"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 2048
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_3/x3/bn"
type: "BatchNorm"
bottom: "conv5_3/x3"
top: "conv5_3/x3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-4
}
}
layer {
name: "conv5_3/x3/scale"
type: "Scale"
bottom: "conv5_3/x3"
top: "conv5_3/x3"
scale_param {
bias_term: true
}
}
layer {
name: "pool5_3/gap"
type: "Pooling"
bottom: "conv5_3/x3"
top: "pool5_3/gap"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc5_3/sqz"
type: "InnerProduct"
bottom: "pool5_3/gap"
top: "fc5_3/sqz"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu5_3/sqz"
type: "ReLU"
bottom: "fc5_3/sqz"
top: "fc5_3/sqz"
}
layer {
name: "fc5_3/exc"
type: "InnerProduct"
bottom: "fc5_3/sqz"
top: "fc5_3/exc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
inner_product_param {
num_output: 2048
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sigm5_3/gate"
type: "Sigmoid"
bottom: "fc5_3/exc"
top: "fc5_3/exc"
}
layer {
name: "scale5_3"
type: "Scale"
bottom: "conv5_3/x3"
bottom: "fc5_3/exc"
top: "scale5_3"
scale_param {
axis: 0
bias_term: false
}
}
layer {
name: "block_5_3"
type: "Eltwise"
bottom: "block_5_2"
bottom: "scale5_3"
top: "block_5_3"
}
layer {
name: "relu5_3"
type: "ReLU"
bottom: "block_5_3"
top: "block_5_3"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "block_5_3"
top: "pool5"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "fc6"
type: "Convolution"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 1000
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "prob"
top: "prob"
type: "Softmax"
bottom: "fc6"
}
#layer {
# name: "loss"
# type: "SoftmaxWithLoss"
# bottom: "fc6"
# bottom: "label"
# top: "loss"
#}
#layer {
# name: "top1/acc"
# type: "Accuracy"
# bottom: "fc6"
# bottom: "label"
# top: "top1/acc"
# include {
# phase: TEST
# }
#}
#layer {
# name: "top5/acc"
# type: "Accuracy"
# bottom: "fc6"
# bottom: "label"
# top: "top5/acc"
# include {
# phase: TEST
# }
# accuracy_param {
# top_k: 5
# }
#}