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ashutoshsatapathy1990/DualPathNet68.prototxt (NVIDIA DIGITS)

Created July 16, 2019 10:18
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DualPathNet68.prototxt (NVIDIA DIGITS)
# DPN-68
name: "DPN-68"
layer {
name: "train-data"
type: "Data"
top: "data"
top: "label"
transform_param {
mirror: true
crop_size: 224
}
data_param {
batch_size: 32
}
include { stage: "train" }
}
layer {
name: "val-data"
type: "Data"
top: "data"
top: "label"
transform_param {
mirror: false
crop_size: 224
}
data_param {
batch_size: 16
}
include { stage: "val" }
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 10
kernel_size: 3
pad: 1
stride: 2
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv1_bn"
type: "BatchNorm"
bottom: "conv1"
top: "conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv1_relu"
type: "ReLU"
bottom: "conv1_bn"
top: "conv1_bn"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1_bn"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
pad: 1
}
}
#################### dpn1 ####################
layer {
name: "dpn1_match_bn"
type: "BatchNorm"
bottom: "pool1"
top: "dpn1_match_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_match_relu"
type: "ReLU"
bottom: "dpn1_match_bn"
top: "dpn1_match_bn"
}
layer {
name: "dpn1_match_conv"
type: "Convolution"
bottom: "dpn1_match_bn"
top: "dpn1_match_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_match_conv_Slice"
type: "Slice"
bottom: "dpn1_match_conv"
top: "dpn1_match_conv_split1"
top: "dpn1_match_conv_split2"
#0-63 64-95
slice_param {
axis: 1
slice_point: 64
}
}
layer {
name: "dpn1_bn"
type: "BatchNorm"
bottom: "pool1"
top: "dpn1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_relu"
type: "ReLU"
bottom: "dpn1_bn"
top: "dpn1_bn"
}
layer {
name: "dpn1_conv1"
type: "Convolution"
bottom: "dpn1_bn"
top: "dpn1_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_conv1_bn"
type: "BatchNorm"
bottom: "dpn1_conv1"
top: "dpn1_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_conv1_relu"
type: "ReLU"
bottom: "dpn1_conv1_bn"
top: "dpn1_conv1_bn"
}
layer {
name: "dpn1_conv2"
type: "Convolution"
bottom: "dpn1_conv1_bn"
top: "dpn1_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_conv2_bn"
type: "BatchNorm"
bottom: "dpn1_conv2"
top: "dpn1_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_conv2_relu"
type: "ReLU"
bottom: "dpn1_conv2_bn"
top: "dpn1_conv2_bn"
}
layer {
name: "dpn1_conv3_branch1"
type: "Convolution"
bottom: "dpn1_conv2_bn"
top: "dpn1_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_conv3_branch2"
type: "Convolution"
bottom: "dpn1_conv2_bn"
top: "dpn1_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn1_elewise"
type: "Eltwise"
bottom: "dpn1_match_conv_split1"
bottom: "dpn1_conv3_branch1"
top: "dpn1_elewise"
}
layer {
name: "dpn1_concat"
type: "Concat"
bottom: "dpn1_match_conv_split2"
bottom: "dpn1_conv3_branch2"
top: "dpn1_concat"
}
#################### dpn2 ####################
layer {
name: "dpn2_concat_input"
type: "Concat"
bottom: "dpn1_elewise"
bottom: "dpn1_concat"
top: "dpn2_concat_input"
}
layer {
name: "dpn2_bn"
type: "BatchNorm"
bottom: "dpn2_concat_input"
top: "dpn2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_relu"
type: "ReLU"
bottom: "dpn2_bn"
top: "dpn2_bn"
}
layer {
name: "dpn2_conv1"
type: "Convolution"
bottom: "dpn2_bn"
top: "dpn2_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_conv1_bn"
type: "BatchNorm"
bottom: "dpn2_conv1"
top: "dpn2_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_conv1_relu"
type: "ReLU"
bottom: "dpn2_conv1_bn"
top: "dpn2_conv1_bn"
}
layer {
name: "dpn2_conv2"
type: "Convolution"
bottom: "dpn2_conv1_bn"
top: "dpn2_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_conv2_bn"
type: "BatchNorm"
bottom: "dpn2_conv2"
top: "dpn2_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_conv2_relu"
type: "ReLU"
bottom: "dpn2_conv2_bn"
top: "dpn2_conv2_bn"
}
layer {
name: "dpn2_conv3_branch1"
type: "Convolution"
bottom: "dpn2_conv2_bn"
top: "dpn2_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_conv3_branch2"
type: "Convolution"
bottom: "dpn2_conv2_bn"
top: "dpn2_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn2_elewise"
type: "Eltwise"
bottom: "dpn1_elewise"
bottom: "dpn2_conv3_branch1"
top: "dpn2_elewise"
}
layer {
name: "dpn2_concat"
type: "Concat"
bottom: "dpn1_concat"
bottom: "dpn2_conv3_branch2"
top: "dpn2_concat"
}
#################### dpn3 ####################
layer {
name: "dpn3_concat_input"
type: "Concat"
bottom: "dpn2_elewise"
bottom: "dpn2_concat"
top: "dpn3_concat_input"
}
layer {
name: "dpn3_bn"
type: "BatchNorm"
bottom: "dpn3_concat_input"
top: "dpn3_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_relu"
type: "ReLU"
bottom: "dpn3_bn"
top: "dpn3_bn"
}
layer {
name: "dpn3_conv1"
type: "Convolution"
bottom: "dpn3_bn"
top: "dpn3_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_conv1_bn"
type: "BatchNorm"
bottom: "dpn3_conv1"
top: "dpn3_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_conv1_relu"
type: "ReLU"
bottom: "dpn3_conv1_bn"
top: "dpn3_conv1_bn"
}
layer {
name: "dpn3_conv2"
type: "Convolution"
bottom: "dpn3_conv1_bn"
top: "dpn3_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_conv2_bn"
type: "BatchNorm"
bottom: "dpn3_conv2"
top: "dpn3_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_conv2_relu"
type: "ReLU"
bottom: "dpn3_conv2_bn"
top: "dpn3_conv2_bn"
}
layer {
name: "dpn3_conv3_branch1"
type: "Convolution"
bottom: "dpn3_conv2_bn"
top: "dpn3_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_conv3_branch2"
type: "Convolution"
bottom: "dpn3_conv2_bn"
top: "dpn3_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn3_elewise"
type: "Eltwise"
bottom: "dpn2_elewise"
bottom: "dpn3_conv3_branch1"
top: "dpn3_elewise"
}
layer {
name: "dpn3_concat"
type: "Concat"
bottom: "dpn2_concat"
bottom: "dpn3_conv3_branch2"
top: "dpn3_concat"
}
#################### dpn4 ####################
layer {
name: "dpn4_concat_input"
type: "Concat"
bottom: "dpn3_elewise"
bottom: "dpn3_concat"
top: "dpn4_concat_input"
}
layer {
name: "dpn4_match_bn"
type: "BatchNorm"
bottom: "dpn4_concat_input"
top: "dpn4_match_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_match_relu"
type: "ReLU"
bottom: "dpn4_match_bn"
top: "dpn4_match_bn"
}
layer {
name: "dpn4_match_conv"
type: "Convolution"
bottom: "dpn4_match_bn"
top: "dpn4_match_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
pad: 0
stride: 2
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_match_conv_Slice"
type: "Slice"
bottom: "dpn4_match_conv"
top: "dpn4_match_conv_split1"
top: "dpn4_match_conv_split2"
#0-127, 128-191
slice_param {
axis: 1
slice_point: 128
}
}
layer {
name: "dpn4_bn"
type: "BatchNorm"
bottom: "dpn4_concat_input"
top: "dpn4_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_relu"
type: "ReLU"
bottom: "dpn4_bn"
top: "dpn4_bn"
}
layer {
name: "dpn4_conv1"
type: "Convolution"
bottom: "dpn4_bn"
top: "dpn4_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_conv1_bn"
type: "BatchNorm"
bottom: "dpn4_conv1"
top: "dpn4_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_conv1_relu"
type: "ReLU"
bottom: "dpn4_conv1_bn"
top: "dpn4_conv1_bn"
}
layer {
name: "dpn4_conv2"
type: "Convolution"
bottom: "dpn4_conv1_bn"
top: "dpn4_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 2
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_conv2_bn"
type: "BatchNorm"
bottom: "dpn4_conv2"
top: "dpn4_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_conv2_relu"
type: "ReLU"
bottom: "dpn4_conv2_bn"
top: "dpn4_conv2_bn"
}
layer {
name: "dpn4_conv3_branch1"
type: "Convolution"
bottom: "dpn4_conv2_bn"
top: "dpn4_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_conv3_branch2"
type: "Convolution"
bottom: "dpn4_conv2_bn"
top: "dpn4_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn4_elewise"
type: "Eltwise"
bottom: "dpn4_match_conv_split1"
bottom: "dpn4_conv3_branch1"
top: "dpn4_elewise"
}
layer {
name: "dpn4_concat"
type: "Concat"
bottom: "dpn4_match_conv_split2"
bottom: "dpn4_conv3_branch2"
top: "dpn4_concat"
}
#################### dpn5 ####################
layer {
name: "dpn5_concat_input"
type: "Concat"
bottom: "dpn4_elewise"
bottom: "dpn4_concat"
top: "dpn5_concat_input"
}
layer {
name: "dpn5_bn"
type: "BatchNorm"
bottom: "dpn5_concat_input"
top: "dpn5_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_relu"
type: "ReLU"
bottom: "dpn5_bn"
top: "dpn5_bn"
}
layer {
name: "dpn5_conv1"
type: "Convolution"
bottom: "dpn5_bn"
top: "dpn5_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_conv1_bn"
type: "BatchNorm"
bottom: "dpn5_conv1"
top: "dpn5_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_conv1_relu"
type: "ReLU"
bottom: "dpn5_conv1_bn"
top: "dpn5_conv1_bn"
}
layer {
name: "dpn5_conv2"
type: "Convolution"
bottom: "dpn5_conv1_bn"
top: "dpn5_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_conv2_bn"
type: "BatchNorm"
bottom: "dpn5_conv2"
top: "dpn5_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_conv2_relu"
type: "ReLU"
bottom: "dpn5_conv2_bn"
top: "dpn5_conv2_bn"
}
layer {
name: "dpn5_conv3_branch1"
type: "Convolution"
bottom: "dpn5_conv2_bn"
top: "dpn5_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_conv3_branch2"
type: "Convolution"
bottom: "dpn5_conv2_bn"
top: "dpn5_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn5_elewise"
type: "Eltwise"
bottom: "dpn4_elewise"
bottom: "dpn5_conv3_branch1"
top: "dpn5_elewise"
}
layer {
name: "dpn5_concat"
type: "Concat"
bottom: "dpn4_concat"
bottom: "dpn5_conv3_branch2"
top: "dpn5_concat"
}
#################### dpn6 ####################
layer {
name: "dpn6_concat_input"
type: "Concat"
bottom: "dpn5_elewise"
bottom: "dpn5_concat"
top: "dpn6_concat_input"
}
layer {
name: "dpn6_bn"
type: "BatchNorm"
bottom: "dpn6_concat_input"
top: "dpn6_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_relu"
type: "ReLU"
bottom: "dpn6_bn"
top: "dpn6_bn"
}
layer {
name: "dpn6_conv1"
type: "Convolution"
bottom: "dpn6_bn"
top: "dpn6_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_conv1_bn"
type: "BatchNorm"
bottom: "dpn6_conv1"
top: "dpn6_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_conv1_relu"
type: "ReLU"
bottom: "dpn6_conv1_bn"
top: "dpn6_conv1_bn"
}
layer {
name: "dpn6_conv2"
type: "Convolution"
bottom: "dpn6_conv1_bn"
top: "dpn6_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_conv2_bn"
type: "BatchNorm"
bottom: "dpn6_conv2"
top: "dpn6_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_conv2_relu"
type: "ReLU"
bottom: "dpn6_conv2_bn"
top: "dpn6_conv2_bn"
}
layer {
name: "dpn6_conv3_branch1"
type: "Convolution"
bottom: "dpn6_conv2_bn"
top: "dpn6_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_conv3_branch2"
type: "Convolution"
bottom: "dpn6_conv2_bn"
top: "dpn6_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn6_elewise"
type: "Eltwise"
bottom: "dpn5_elewise"
bottom: "dpn6_conv3_branch1"
top: "dpn6_elewise"
}
layer {
name: "dpn6_concat"
type: "Concat"
bottom: "dpn5_concat"
bottom: "dpn6_conv3_branch2"
top: "dpn6_concat"
}
#################### dpn7 ####################
layer {
name: "dpn7_concat_input"
type: "Concat"
bottom: "dpn6_elewise"
bottom: "dpn6_concat"
top: "dpn7_concat_input"
}
layer {
name: "dpn7_bn"
type: "BatchNorm"
bottom: "dpn7_concat_input"
top: "dpn7_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_relu"
type: "ReLU"
bottom: "dpn7_bn"
top: "dpn7_bn"
}
layer {
name: "dpn7_conv1"
type: "Convolution"
bottom: "dpn7_bn"
top: "dpn7_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_conv1_bn"
type: "BatchNorm"
bottom: "dpn7_conv1"
top: "dpn7_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_conv1_relu"
type: "ReLU"
bottom: "dpn7_conv1_bn"
top: "dpn7_conv1_bn"
}
layer {
name: "dpn7_conv2"
type: "Convolution"
bottom: "dpn7_conv1_bn"
top: "dpn7_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_conv2_bn"
type: "BatchNorm"
bottom: "dpn7_conv2"
top: "dpn7_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_conv2_relu"
type: "ReLU"
bottom: "dpn7_conv2_bn"
top: "dpn7_conv2_bn"
}
layer {
name: "dpn7_conv3_branch1"
type: "Convolution"
bottom: "dpn7_conv2_bn"
top: "dpn7_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_conv3_branch2"
type: "Convolution"
bottom: "dpn7_conv2_bn"
top: "dpn7_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn7_elewise"
type: "Eltwise"
bottom: "dpn6_elewise"
bottom: "dpn7_conv3_branch1"
top: "dpn7_elewise"
}
layer {
name: "dpn7_concat"
type: "Concat"
bottom: "dpn6_concat"
bottom: "dpn7_conv3_branch2"
top: "dpn7_concat"
}
#################### dpn8 ####################
layer {
name: "dpn8_concat_input"
type: "Concat"
bottom: "dpn7_elewise"
bottom: "dpn7_concat"
top: "dpn8_concat_input"
}
layer {
name: "dpn8_match_bn"
type: "BatchNorm"
bottom: "dpn8_concat_input"
top: "dpn8_match_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_match_relu"
type: "ReLU"
bottom: "dpn8_match_bn"
top: "dpn8_match_bn"
}
layer {
name: "dpn8_match_conv"
type: "Convolution"
bottom: "dpn8_match_bn"
top: "dpn8_match_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
kernel_size: 1
pad: 0
stride: 2
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_match_conv_Slice"
type: "Slice"
bottom: "dpn8_match_conv"
top: "dpn8_match_conv_split1"
top: "dpn8_match_conv_split2" #0-255, 256~319
slice_param {
axis: 1
slice_point: 256
}
}
layer {
name: "dpn8_bn"
type: "BatchNorm"
bottom: "dpn8_concat_input"
top: "dpn8_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_relu"
type: "ReLU"
bottom: "dpn8_bn"
top: "dpn8_bn"
}
layer {
name: "dpn8_conv1"
type: "Convolution"
bottom: "dpn8_bn"
top: "dpn8_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_conv1_bn"
type: "BatchNorm"
bottom: "dpn8_conv1"
top: "dpn8_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_conv1_relu"
type: "ReLU"
bottom: "dpn8_conv1_bn"
top: "dpn8_conv1_bn"
}
layer {
name: "dpn8_conv2"
type: "Convolution"
bottom: "dpn8_conv1_bn"
top: "dpn8_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 2
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_conv2_bn"
type: "BatchNorm"
bottom: "dpn8_conv2"
top: "dpn8_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_conv2_relu"
type: "ReLU"
bottom: "dpn8_conv2_bn"
top: "dpn8_conv2_bn"
}
layer {
name: "dpn8_conv3_branch1"
type: "Convolution"
bottom: "dpn8_conv2_bn"
top: "dpn8_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_conv3_branch2"
type: "Convolution"
bottom: "dpn8_conv2_bn"
top: "dpn8_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn8_elewise"
type: "Eltwise"
bottom: "dpn8_match_conv_split1"
bottom: "dpn8_conv3_branch1"
top: "dpn8_elewise"
}
layer {
name: "dpn8_concat"
type: "Concat"
bottom: "dpn8_match_conv_split2"
bottom: "dpn8_conv3_branch2"
top: "dpn8_concat"
}
#################### dpn9 ####################
layer {
name: "dpn9_concat_input"
type: "Concat"
bottom: "dpn8_elewise"
bottom: "dpn8_concat"
top: "dpn9_concat_input"
}
layer {
name: "dpn9_bn"
type: "BatchNorm"
bottom: "dpn9_concat_input"
top: "dpn9_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_relu"
type: "ReLU"
bottom: "dpn9_bn"
top: "dpn9_bn"
}
layer {
name: "dpn9_conv1"
type: "Convolution"
bottom: "dpn9_bn"
top: "dpn9_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_conv1_bn"
type: "BatchNorm"
bottom: "dpn9_conv1"
top: "dpn9_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_conv1_relu"
type: "ReLU"
bottom: "dpn9_conv1_bn"
top: "dpn9_conv1_bn"
}
layer {
name: "dpn9_conv2"
type: "Convolution"
bottom: "dpn9_conv1_bn"
top: "dpn9_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_conv2_bn"
type: "BatchNorm"
bottom: "dpn9_conv2"
top: "dpn9_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_conv2_relu"
type: "ReLU"
bottom: "dpn9_conv2_bn"
top: "dpn9_conv2_bn"
}
layer {
name: "dpn9_conv3_branch1"
type: "Convolution"
bottom: "dpn9_conv2_bn"
top: "dpn9_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_conv3_branch2"
type: "Convolution"
bottom: "dpn9_conv2_bn"
top: "dpn9_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn9_elewise"
type: "Eltwise"
bottom: "dpn8_elewise"
bottom: "dpn9_conv3_branch1"
top: "dpn9_elewise"
}
layer {
name: "dpn9_concat"
type: "Concat"
bottom: "dpn8_concat"
bottom: "dpn9_conv3_branch2"
top: "dpn9_concat"
}
#################### dpn10 ####################
layer {
name: "dpn10_concat_input"
type: "Concat"
bottom: "dpn9_elewise"
bottom: "dpn9_concat"
top: "dpn10_concat_input"
}
layer {
name: "dpn10_bn"
type: "BatchNorm"
bottom: "dpn10_concat_input"
top: "dpn10_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_relu"
type: "ReLU"
bottom: "dpn10_bn"
top: "dpn10_bn"
}
layer {
name: "dpn10_conv1"
type: "Convolution"
bottom: "dpn10_bn"
top: "dpn10_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_conv1_bn"
type: "BatchNorm"
bottom: "dpn10_conv1"
top: "dpn10_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_conv1_relu"
type: "ReLU"
bottom: "dpn10_conv1_bn"
top: "dpn10_conv1_bn"
}
layer {
name: "dpn10_conv2"
type: "Convolution"
bottom: "dpn10_conv1_bn"
top: "dpn10_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_conv2_bn"
type: "BatchNorm"
bottom: "dpn10_conv2"
top: "dpn10_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_conv2_relu"
top: "dpn10_conv2_bn"
bottom: "dpn10_conv2_bn"
type: "ReLU"
}
layer {
name: "dpn10_conv3_branch1"
type: "Convolution"
bottom: "dpn10_conv2_bn"
top: "dpn10_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_conv3_branch2"
type: "Convolution"
bottom: "dpn10_conv2_bn"
top: "dpn10_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn10_elewise"
type: "Eltwise"
bottom: "dpn9_elewise"
bottom: "dpn10_conv3_branch1"
top: "dpn10_elewise"
}
layer {
name: "dpn10_concat"
type: "Concat"
bottom: "dpn9_concat"
bottom: "dpn10_conv3_branch2"
top: "dpn10_concat"
}
#################### dpn11 ####################
layer {
name: "dpn11_concat_input"
type: "Concat"
bottom: "dpn10_elewise"
bottom: "dpn10_concat"
top: "dpn11_concat_input"
}
layer {
name: "dpn11_bn"
type: "BatchNorm"
bottom: "dpn11_concat_input"
top: "dpn11_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_relu"
type: "ReLU"
bottom: "dpn11_bn"
top: "dpn11_bn"
}
layer {
name: "dpn11_conv1"
bottom: "dpn11_bn"
top: "dpn11_conv1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_conv1_bn"
type: "BatchNorm"
bottom: "dpn11_conv1"
top: "dpn11_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_conv1_relu"
type: "ReLU"
bottom: "dpn11_conv1_bn"
top: "dpn11_conv1_bn"
}
layer {
name: "dpn11_conv2"
type: "Convolution"
bottom: "dpn11_conv1_bn"
top: "dpn11_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_conv2_bn"
type: "BatchNorm"
bottom: "dpn11_conv2"
top: "dpn11_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_conv2_relu"
type: "ReLU"
bottom: "dpn11_conv2_bn"
top: "dpn11_conv2_bn"
}
layer {
name: "dpn11_conv3_branch1"
type: "Convolution"
bottom: "dpn11_conv2_bn"
top: "dpn11_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_conv3_branch2"
type: "Convolution"
bottom: "dpn11_conv2_bn"
top: "dpn11_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn11_elewise"
type: "Eltwise"
bottom: "dpn10_elewise"
bottom: "dpn11_conv3_branch1"
top: "dpn11_elewise"
}
layer {
name: "dpn11_concat"
type: "Concat"
bottom: "dpn10_concat"
bottom: "dpn11_conv3_branch2"
top: "dpn11_concat"
}
#################### dpn12 ####################
layer {
name: "dpn12_concat_input"
type: "Concat"
bottom: "dpn11_elewise"
bottom: "dpn11_concat"
top: "dpn12_concat_input"
}
layer {
name: "dpn12_bn"
type: "BatchNorm"
bottom: "dpn12_concat_input"
top: "dpn12_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_relu"
type: "ReLU"
bottom: "dpn12_bn"
top: "dpn12_bn"
}
layer {
name: "dpn12_conv1"
type: "Convolution"
bottom: "dpn12_bn"
top: "dpn12_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_conv1_bn"
type: "BatchNorm"
bottom: "dpn12_conv1"
top: "dpn12_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_conv1_relu"
type: "ReLU"
bottom: "dpn12_conv1_bn"
top: "dpn12_conv1_bn"
}
layer {
name: "dpn12_conv2"
type: "Convolution"
bottom: "dpn12_conv1_bn"
top: "dpn12_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_conv2_bn"
type: "BatchNorm"
bottom: "dpn12_conv2"
top: "dpn12_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_conv2_relu"
type: "ReLU"
bottom: "dpn12_conv2_bn"
top: "dpn12_conv2_bn"
}
layer {
name: "dpn12_conv3_branch1"
type: "Convolution"
bottom: "dpn12_conv2_bn"
top: "dpn12_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_conv3_branch2"
type: "Convolution"
bottom: "dpn12_conv2_bn"
top: "dpn12_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn12_elewise"
type: "Eltwise"
bottom: "dpn11_elewise"
bottom: "dpn12_conv3_branch1"
top: "dpn12_elewise"
}
layer {
name: "dpn12_concat"
type: "Concat"
bottom: "dpn11_concat"
bottom: "dpn12_conv3_branch2"
top: "dpn12_concat"
}
#################### dpn13 ####################
layer {
name: "dpn13_concat_input"
type: "Concat"
bottom: "dpn12_elewise"
bottom: "dpn12_concat"
top: "dpn13_concat_input"
}
layer {
name: "dpn13_bn"
type: "BatchNorm"
bottom: "dpn13_concat_input"
top: "dpn13_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_relu"
type: "ReLU"
bottom: "dpn13_bn"
top: "dpn13_bn"
}
layer {
name: "dpn13_conv1"
type: "Convolution"
bottom: "dpn13_bn"
top: "dpn13_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_conv1_bn"
bottom: "dpn13_conv1"
top: "dpn13_conv1_bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_conv1_relu"
type: "ReLU"
bottom: "dpn13_conv1_bn"
top: "dpn13_conv1_bn"
}
layer {
name: "dpn13_conv2"
type: "Convolution"
bottom: "dpn13_conv1_bn"
top: "dpn13_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_conv2_bn"
type: "BatchNorm"
bottom: "dpn13_conv2"
top: "dpn13_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_conv2_relu"
type: "ReLU"
bottom: "dpn13_conv2_bn"
top: "dpn13_conv2_bn"
}
layer {
name: "dpn13_conv3_branch1"
type: "Convolution"
bottom: "dpn13_conv2_bn"
top: "dpn13_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_conv3_branch2"
type: "Convolution"
bottom: "dpn13_conv2_bn"
top: "dpn13_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn13_elewise"
type: "Eltwise"
bottom: "dpn12_elewise"
bottom: "dpn13_conv3_branch1"
top: "dpn13_elewise"
}
layer {
name: "dpn13_concat"
type: "Concat"
bottom: "dpn12_concat"
bottom: "dpn13_conv3_branch2"
top: "dpn13_concat"
}
#################### dpn14 ####################
layer {
name: "dpn14_concat_input"
type: "Concat"
bottom: "dpn13_elewise"
bottom: "dpn13_concat"
top: "dpn14_concat_input"
}
layer {
name: "dpn14_bn"
type: "BatchNorm"
bottom: "dpn14_concat_input"
top: "dpn14_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_relu"
type: "ReLU"
bottom: "dpn14_bn"
top: "dpn14_bn"
}
layer {
name: "dpn14_conv1"
type: "Convolution"
bottom: "dpn14_bn"
top: "dpn14_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_conv1_bn"
type: "BatchNorm"
bottom: "dpn14_conv1"
top: "dpn14_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_conv1_relu"
type: "ReLU"
bottom: "dpn14_conv1_bn"
top: "dpn14_conv1_bn"
}
layer {
name: "dpn14_conv2"
type: "Convolution"
bottom: "dpn14_conv1_bn"
top: "dpn14_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_conv2_bn"
type: "BatchNorm"
bottom: "dpn14_conv2"
top: "dpn14_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_conv2_relu"
type: "ReLU"
bottom: "dpn14_conv2_bn"
top: "dpn14_conv2_bn"
}
layer {
name: "dpn14_conv3_branch1"
type: "Convolution"
bottom: "dpn14_conv2_bn"
top: "dpn14_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_conv3_branch2"
type: "Convolution"
bottom: "dpn14_conv2_bn"
top: "dpn14_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn14_elewise"
type: "Eltwise"
bottom: "dpn13_elewise"
bottom: "dpn14_conv3_branch1"
top: "dpn14_elewise"
}
layer {
name: "dpn14_concat"
type: "Concat"
bottom: "dpn13_concat"
bottom: "dpn14_conv3_branch2"
top: "dpn14_concat"
}
#################### dpn15 ####################
layer {
name: "dpn15_concat_input"
type: "Concat"
bottom: "dpn14_elewise"
bottom: "dpn14_concat"
top: "dpn15_concat_input"
}
layer {
name: "dpn15_bn"
type: "BatchNorm"
bottom: "dpn15_concat_input"
top: "dpn15_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_relu"
type: "ReLU"
bottom: "dpn15_bn"
top: "dpn15_bn"
}
layer {
name: "dpn15_conv1"
type: "Convolution"
bottom: "dpn15_bn"
top: "dpn15_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_conv1_bn"
type: "BatchNorm"
bottom: "dpn15_conv1"
top: "dpn15_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_conv1_relu"
type: "ReLU"
bottom: "dpn15_conv1_bn"
top: "dpn15_conv1_bn"
}
layer {
name: "dpn15_conv2"
bottom: "dpn15_conv1_bn"
top: "dpn15_conv2"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_conv2_bn"
type: "BatchNorm"
bottom: "dpn15_conv2"
top: "dpn15_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_conv2_relu"
type: "ReLU"
bottom: "dpn15_conv2_bn"
top: "dpn15_conv2_bn"
}
layer {
name: "dpn15_conv3_branch1"
type: "Convolution"
bottom: "dpn15_conv2_bn"
top: "dpn15_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_conv3_branch2"
type: "Convolution"
bottom: "dpn15_conv2_bn"
top: "dpn15_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn15_elewise"
type: "Eltwise"
bottom: "dpn14_elewise"
bottom: "dpn15_conv3_branch1"
top: "dpn15_elewise"
}
layer {
name: "dpn15_concat"
type: "Concat"
bottom: "dpn14_concat"
bottom: "dpn15_conv3_branch2"
top: "dpn15_concat"
}
#################### dpn16 ####################
layer {
name: "dpn16_concat_input"
type: "Concat"
bottom: "dpn15_elewise"
bottom: "dpn15_concat"
top: "dpn16_concat_input"
}
layer {
name: "dpn16_bn"
type: "BatchNorm"
bottom: "dpn16_concat_input"
top: "dpn16_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_relu"
type: "ReLU"
bottom: "dpn16_bn"
top: "dpn16_bn"
}
layer {
name: "dpn16_conv1"
type: "Convolution"
bottom: "dpn16_bn"
top: "dpn16_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_conv1_bn"
type: "BatchNorm"
bottom: "dpn16_conv1"
top: "dpn16_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_conv1_relu"
type: "ReLU"
bottom: "dpn16_conv1_bn"
top: "dpn16_conv1_bn"
}
layer {
name: "dpn16_conv2"
type: "Convolution"
bottom: "dpn16_conv1_bn"
top: "dpn16_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_conv2_bn"
type: "BatchNorm"
bottom: "dpn16_conv2"
top: "dpn16_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_conv2_relu"
type: "ReLU"
bottom: "dpn16_conv2_bn"
top: "dpn16_conv2_bn"
}
layer {
name: "dpn16_conv3_branch1"
type: "Convolution"
bottom: "dpn16_conv2_bn"
top: "dpn16_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_conv3_branch2"
type: "Convolution"
bottom: "dpn16_conv2_bn"
top: "dpn16_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn16_elewise"
type: "Eltwise"
bottom: "dpn15_elewise"
bottom: "dpn16_conv3_branch1"
top: "dpn16_elewise"
}
layer {
name: "dpn16_concat"
type: "Concat"
bottom: "dpn15_concat"
bottom: "dpn16_conv3_branch2"
top: "dpn16_concat"
}
#################### dpn17 ####################
layer {
name: "dpn17_concat_input"
type: "Concat"
bottom: "dpn16_elewise"
bottom: "dpn16_concat"
top: "dpn17_concat_input"
}
layer {
name: "dpn17_bn"
type: "BatchNorm"
bottom: "dpn17_concat_input"
top: "dpn17_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_relu"
type: "ReLU"
bottom: "dpn17_bn"
top: "dpn17_bn"
}
layer {
name: "dpn17_conv1"
type: "Convolution"
bottom: "dpn17_bn"
top: "dpn17_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_conv1_bn"
type: "BatchNorm"
bottom: "dpn17_conv1"
top: "dpn17_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_conv1_relu"
type: "ReLU"
bottom: "dpn17_conv1_bn"
top: "dpn17_conv1_bn"
}
layer {
name: "dpn17_conv2"
type: "Convolution"
bottom: "dpn17_conv1_bn"
top: "dpn17_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_conv2_bn"
type: "BatchNorm"
bottom: "dpn17_conv2"
top: "dpn17_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_conv2_relu"
type: "ReLU"
bottom: "dpn17_conv2_bn"
top: "dpn17_conv2_bn"
}
layer {
name: "dpn17_conv3_branch1"
type: "Convolution"
bottom: "dpn17_conv2_bn"
top: "dpn17_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_conv3_branch2"
type: "Convolution"
bottom: "dpn17_conv2_bn"
top: "dpn17_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn17_elewise"
type: "Eltwise"
bottom: "dpn16_elewise"
bottom: "dpn17_conv3_branch1"
top: "dpn17_elewise"
}
layer {
name: "dpn17_concat"
type: "Concat"
bottom: "dpn16_concat"
bottom: "dpn17_conv3_branch2"
top: "dpn17_concat"
}
#################### dpn18 ####################
layer {
name: "dpn18_concat_input"
type: "Concat"
bottom: "dpn17_elewise"
bottom: "dpn17_concat"
top: "dpn18_concat_input"
}
layer {
name: "dpn18_bn"
type: "BatchNorm"
bottom: "dpn18_concat_input"
top: "dpn18_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_relu"
type: "ReLU"
bottom: "dpn18_bn"
top: "dpn18_bn"
}
layer {
name: "dpn18_conv1"
type: "Convolution"
bottom: "dpn18_bn"
top: "dpn18_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_conv1_bn"
type: "BatchNorm"
bottom: "dpn18_conv1"
top: "dpn18_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_conv1_relu"
type: "ReLU"
bottom: "dpn18_conv1_bn"
top: "dpn18_conv1_bn"
}
layer {
name: "dpn18_conv2"
type: "Convolution"
bottom: "dpn18_conv1_bn"
top: "dpn18_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_conv2_bn"
type: "BatchNorm"
bottom: "dpn18_conv2"
top: "dpn18_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_conv2_relu"
type: "ReLU"
bottom: "dpn18_conv2_bn"
top: "dpn18_conv2_bn"
}
layer {
name: "dpn18_conv3_branch1"
type: "Convolution"
bottom: "dpn18_conv2_bn"
top: "dpn18_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_conv3_branch2"
type: "Convolution"
bottom: "dpn18_conv2_bn"
top: "dpn18_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn18_elewise"
type: "Eltwise"
bottom: "dpn17_elewise"
bottom: "dpn18_conv3_branch1"
top: "dpn18_elewise"
}
layer {
name: "dpn18_concat"
type: "Concat"
bottom: "dpn17_concat"
bottom: "dpn18_conv3_branch2"
top: "dpn18_concat"
}
#################### dpn19 ####################
layer {
name: "dpn19_concat_input"
type: "Concat"
bottom: "dpn18_elewise"
bottom: "dpn18_concat"
top: "dpn19_concat_input"
}
layer {
name: "dpn19_bn"
type: "BatchNorm"
bottom: "dpn19_concat_input"
top: "dpn19_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_relu"
type: "ReLU"
bottom: "dpn19_bn"
top: "dpn19_bn"
}
layer {
name: "dpn19_conv1"
type: "Convolution"
bottom: "dpn19_bn"
top: "dpn19_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_conv1_bn"
type: "BatchNorm"
bottom: "dpn19_conv1"
top: "dpn19_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_conv1_relu"
type: "ReLU"
bottom: "dpn19_conv1_bn"
top: "dpn19_conv1_bn"
}
layer {
name: "dpn19_conv2"
type: "Convolution"
bottom: "dpn19_conv1_bn"
top: "dpn19_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_conv2_bn"
type: "BatchNorm"
bottom: "dpn19_conv2"
top: "dpn19_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_conv2_relu"
type: "ReLU"
bottom: "dpn19_conv2_bn"
top: "dpn19_conv2_bn"
}
layer {
name: "dpn19_conv3_branch1"
type: "Convolution"
bottom: "dpn19_conv2_bn"
top: "dpn19_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_conv3_branch2"
type: "Convolution"
bottom: "dpn19_conv2_bn"
top: "dpn19_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn19_elewise"
type: "Eltwise"
bottom: "dpn18_elewise"
bottom: "dpn19_conv3_branch1"
top: "dpn19_elewise"
}
layer {
name: "dpn19_concat"
type: "Concat"
bottom: "dpn18_concat"
bottom: "dpn19_conv3_branch2"
top: "dpn19_concat"
}
#################### dpn20 ####################
layer {
name: "dpn20_concat_input"
type: "Concat"
bottom: "dpn19_elewise"
bottom: "dpn19_concat"
top: "dpn20_concat_input"
}
layer {
name: "dpn20_match_bn"
type: "BatchNorm"
bottom: "dpn20_concat_input"
top: "dpn20_match_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_match_relu"
type: "ReLU"
bottom: "dpn20_match_bn"
top: "dpn20_match_bn"
}
layer {
name: "dpn20_match_conv"
type: "Convolution"
bottom: "dpn20_match_bn"
top: "dpn20_match_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 640
kernel_size: 1
pad: 0
stride: 2
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_match_conv_Slice"
type: "Slice"
bottom: "dpn20_match_conv"
top: "dpn20_match_conv_split1"
top: "dpn20_match_conv_split2" # 0~511, 512~639
slice_param {
axis: 1
slice_point: 512
}
}
layer {
name: "dpn20_bn"
type: "BatchNorm"
bottom: "dpn20_concat_input"
top: "dpn20_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_relu"
type: "ReLU"
bottom: "dpn20_bn"
top: "dpn20_bn"
}
layer {
name: "dpn20_conv1"
type: "Convolution"
bottom: "dpn20_bn"
top: "dpn20_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_conv1_bn"
type: "BatchNorm"
bottom: "dpn20_conv1"
top: "dpn20_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_conv1_relu"
type: "ReLU"
bottom: "dpn20_conv1_bn"
top: "dpn20_conv1_bn"
}
layer {
name: "dpn20_conv2"
type: "Convolution"
bottom: "dpn20_conv1_bn"
top: "dpn20_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 2
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_conv2_bn"
type: "BatchNorm"
bottom: "dpn20_conv2"
top: "dpn20_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_conv2_relu"
type: "ReLU"
bottom: "dpn20_conv2_bn"
top: "dpn20_conv2_bn"
}
layer {
name: "dpn20_conv3_branch1"
type: "Convolution"
bottom: "dpn20_conv2_bn"
top: "dpn20_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_conv3_branch2"
type: "Convolution"
bottom: "dpn20_conv2_bn"
top: "dpn20_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn20_elewise"
type: "Eltwise"
bottom: "dpn20_match_conv_split1"
bottom: "dpn20_conv3_branch1"
top: "dpn20_elewise"
}
layer {
name: "dpn20_concat"
type: "Concat"
bottom: "dpn20_match_conv_split2"
bottom: "dpn20_conv3_branch2"
top: "dpn20_concat"
}
#################### dpn21 ####################
layer {
name: "dpn21_concat_input"
type: "Concat"
bottom: "dpn20_elewise"
bottom: "dpn20_concat"
top: "dpn21_concat_input"
}
layer {
name: "dpn21_bn"
type: "BatchNorm"
bottom: "dpn21_concat_input"
top: "dpn21_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_relu"
type: "ReLU"
bottom: "dpn21_bn"
top: "dpn21_bn"
}
layer {
name: "dpn21_conv1"
type: "Convolution"
bottom: "dpn21_bn"
top: "dpn21_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_conv1_bn"
type: "BatchNorm"
bottom: "dpn21_conv1"
top: "dpn21_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_conv1_relu"
type: "ReLU"
bottom: "dpn21_conv1_bn"
top: "dpn21_conv1_bn"
}
layer {
name: "dpn21_conv2"
type: "Convolution"
bottom: "dpn21_conv1_bn"
top: "dpn21_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_conv2_bn"
type: "BatchNorm"
bottom: "dpn21_conv2"
top: "dpn21_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_conv2_relu"
type: "ReLU"
bottom: "dpn21_conv2_bn"
top: "dpn21_conv2_bn"
}
layer {
name: "dpn21_conv3_branch1"
type: "Convolution"
bottom: "dpn21_conv2_bn"
top: "dpn21_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_conv3_branch2"
type: "Convolution"
bottom: "dpn21_conv2_bn"
top: "dpn21_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn21_elewise"
type: "Eltwise"
bottom: "dpn20_elewise"
bottom: "dpn21_conv3_branch1"
top: "dpn21_elewise"
}
layer {
name: "dpn21_concat"
type: "Concat"
bottom: "dpn20_concat"
bottom: "dpn21_conv3_branch2"
top: "dpn21_concat"
}
#################### dpn22 ####################
layer {
name: "dpn22_concat_input"
type: "Concat"
bottom: "dpn21_elewise"
bottom: "dpn21_concat"
top: "dpn22_concat_input"
}
layer {
name: "dpn22_bn"
type: "BatchNorm"
bottom: "dpn22_concat_input"
top: "dpn22_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_relu"
type: "ReLU"
bottom: "dpn22_bn"
top: "dpn22_bn"
}
layer {
name: "dpn22_conv1"
type: "Convolution"
bottom: "dpn22_bn"
top: "dpn22_conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_conv1_bn"
type: "BatchNorm"
bottom: "dpn22_conv1"
top: "dpn22_conv1_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_conv1_relu"
type: "ReLU"
bottom: "dpn22_conv1_bn"
top: "dpn22_conv1_bn"
}
layer {
name: "dpn22_conv2"
type: "Convolution"
bottom: "dpn22_conv1_bn"
top: "dpn22_conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
group: 32
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_conv2_bn"
type: "BatchNorm"
bottom: "dpn22_conv2"
top: "dpn22_conv2_bn"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_conv2_relu"
type: "ReLU"
bottom: "dpn22_conv2_bn"
top: "dpn22_conv2_bn"
}
layer {
name: "dpn22_conv3_branch1"
type: "Convolution"
bottom: "dpn22_conv2_bn"
top: "dpn22_conv3_branch1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_conv3_branch2"
type: "Convolution"
bottom: "dpn22_conv2_bn"
top: "dpn22_conv3_branch2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
group: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "dpn22_elewise"
type: "Eltwise"
bottom: "dpn21_elewise"
bottom: "dpn22_conv3_branch1"
top: "dpn22_elewise"
}
layer {
name: "dpn22_concat"
type: "Concat"
bottom: "dpn21_concat"
bottom: "dpn22_conv3_branch2"
top: "dpn22_concat"
}
#################### pool_ave ####################
layer {
name: "pool_ave_concat_input"
type: "Concat"
bottom: "dpn22_elewise"
bottom: "dpn22_concat"
top: "pool_ave_concat_input"
}
layer {
name: "pool_ave_concat_bn"
bottom: "pool_ave_concat_input"
top: "pool_ave_concat_bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "pool_ave_concat_relu"
type: "ReLU"
bottom: "pool_ave_concat_bn"
top: "pool_ave_concat_bn"
}
layer {
name: "pool_ave"
type: "Pooling"
bottom: "pool_ave_concat_bn"
top: "pool_ave"
pooling_param {
global_pooling : true
pool: AVE
}
}
layer {
name: "pool_ave_flat"
type: "Flatten"
bottom: "pool_ave"
top: "pool_ave_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fclayer"
type: "InnerProduct"
bottom: "pool_ave_flat"
top: "fclayer"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fclayer"
bottom: "label"
top: "accuracy"
include { stage: "val" }
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fclayer"
bottom: "label"
top: "loss"
exclude { stage: "deploy" }
}
layer {
name: "softmax"
type: "Softmax"
bottom: "fclayer"
top: "softmax"
include { stage: "deploy" }
}
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