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roachsinai/CornerNet.prototxt

Created March 6, 2020 14:39
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CornerNet.prototxt
name: "cornernet"
input: "blob1"
input_dim: 1
input_dim: 3
input_dim: 511
input_dim: 511
layer {
name: "conv1"
type: "Convolution"
bottom: "blob1"
top: "conv_blob1"
convolution_param {
num_output: 128
bias_term: false
pad: 3
kernel_size: 7
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm1"
type: "BatchNorm"
bottom: "conv_blob1"
top: "batch_norm_blob1"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale1"
type: "Scale"
bottom: "batch_norm_blob1"
top: "batch_norm_blob1"
scale_param {
bias_term: true
}
}
layer {
name: "relu1"
type: "CPP"
bottom: "batch_norm_blob1"
top: "relu_blob1"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "relu_blob1"
top: "conv_blob2"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm2"
type: "BatchNorm"
bottom: "conv_blob2"
top: "batch_norm_blob2"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale2"
type: "Scale"
bottom: "batch_norm_blob2"
top: "batch_norm_blob2"
scale_param {
bias_term: true
}
}
layer {
name: "relu2"
type: "CPP"
bottom: "batch_norm_blob2"
top: "relu_blob2"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "relu_blob2"
top: "conv_blob3"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm3"
type: "BatchNorm"
bottom: "conv_blob3"
top: "batch_norm_blob3"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale3"
type: "Scale"
bottom: "batch_norm_blob3"
top: "batch_norm_blob3"
scale_param {
bias_term: true
}
}
layer {
name: "conv4"
type: "Convolution"
bottom: "relu_blob1"
top: "conv_blob4"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm4"
type: "BatchNorm"
bottom: "conv_blob4"
top: "batch_norm_blob4"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale4"
type: "Scale"
bottom: "batch_norm_blob4"
top: "batch_norm_blob4"
scale_param {
bias_term: true
}
}
layer {
name: "add1"
type: "Eltwise"
bottom: "batch_norm_blob3"
bottom: "batch_norm_blob4"
top: "add_blob1"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu3"
type: "CPP"
bottom: "add_blob1"
top: "relu_blob3"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv5"
type: "Convolution"
bottom: "relu_blob3"
top: "conv_blob5"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm5"
type: "BatchNorm"
bottom: "conv_blob5"
top: "batch_norm_blob5"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale5"
type: "Scale"
bottom: "batch_norm_blob5"
top: "batch_norm_blob5"
scale_param {
bias_term: true
}
}
layer {
name: "relu4"
type: "CPP"
bottom: "batch_norm_blob5"
top: "relu_blob4"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv6"
type: "Convolution"
bottom: "relu_blob4"
top: "conv_blob6"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm6"
type: "BatchNorm"
bottom: "conv_blob6"
top: "batch_norm_blob6"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale6"
type: "Scale"
bottom: "batch_norm_blob6"
top: "batch_norm_blob6"
scale_param {
bias_term: true
}
}
layer {
name: "add2"
type: "Eltwise"
bottom: "batch_norm_blob6"
bottom: "relu_blob3"
top: "add_blob2"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu5"
type: "CPP"
bottom: "add_blob2"
top: "relu_blob5"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv7"
type: "Convolution"
bottom: "relu_blob5"
top: "conv_blob7"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm7"
type: "BatchNorm"
bottom: "conv_blob7"
top: "batch_norm_blob7"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale7"
type: "Scale"
bottom: "batch_norm_blob7"
top: "batch_norm_blob7"
scale_param {
bias_term: true
}
}
layer {
name: "relu6"
type: "CPP"
bottom: "batch_norm_blob7"
top: "relu_blob6"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv8"
type: "Convolution"
bottom: "relu_blob6"
top: "conv_blob8"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm8"
type: "BatchNorm"
bottom: "conv_blob8"
top: "batch_norm_blob8"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale8"
type: "Scale"
bottom: "batch_norm_blob8"
top: "batch_norm_blob8"
scale_param {
bias_term: true
}
}
layer {
name: "add3"
type: "Eltwise"
bottom: "batch_norm_blob8"
bottom: "relu_blob5"
top: "add_blob3"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu7"
type: "CPP"
bottom: "add_blob3"
top: "relu_blob7"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv9"
type: "Convolution"
bottom: "relu_blob3"
top: "conv_blob9"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm9"
type: "BatchNorm"
bottom: "conv_blob9"
top: "batch_norm_blob9"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale9"
type: "Scale"
bottom: "batch_norm_blob9"
top: "batch_norm_blob9"
scale_param {
bias_term: true
}
}
layer {
name: "relu8"
type: "CPP"
bottom: "batch_norm_blob9"
top: "relu_blob8"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv10"
type: "Convolution"
bottom: "relu_blob8"
top: "conv_blob10"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm10"
type: "BatchNorm"
bottom: "conv_blob10"
top: "batch_norm_blob10"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale10"
type: "Scale"
bottom: "batch_norm_blob10"
top: "batch_norm_blob10"
scale_param {
bias_term: true
}
}
layer {
name: "conv11"
type: "Convolution"
bottom: "relu_blob3"
top: "conv_blob11"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm11"
type: "BatchNorm"
bottom: "conv_blob11"
top: "batch_norm_blob11"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale11"
type: "Scale"
bottom: "batch_norm_blob11"
top: "batch_norm_blob11"
scale_param {
bias_term: true
}
}
layer {
name: "add4"
type: "Eltwise"
bottom: "batch_norm_blob10"
bottom: "batch_norm_blob11"
top: "add_blob4"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu9"
type: "CPP"
bottom: "add_blob4"
top: "relu_blob9"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv12"
type: "Convolution"
bottom: "relu_blob9"
top: "conv_blob12"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm12"
type: "BatchNorm"
bottom: "conv_blob12"
top: "batch_norm_blob12"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale12"
type: "Scale"
bottom: "batch_norm_blob12"
top: "batch_norm_blob12"
scale_param {
bias_term: true
}
}
layer {
name: "relu10"
type: "CPP"
bottom: "batch_norm_blob12"
top: "relu_blob10"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv13"
type: "Convolution"
bottom: "relu_blob10"
top: "conv_blob13"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm13"
type: "BatchNorm"
bottom: "conv_blob13"
top: "batch_norm_blob13"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale13"
type: "Scale"
bottom: "batch_norm_blob13"
top: "batch_norm_blob13"
scale_param {
bias_term: true
}
}
layer {
name: "add5"
type: "Eltwise"
bottom: "batch_norm_blob13"
bottom: "relu_blob9"
top: "add_blob5"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu11"
type: "CPP"
bottom: "add_blob5"
top: "relu_blob11"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv14"
type: "Convolution"
bottom: "relu_blob11"
top: "conv_blob14"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm14"
type: "BatchNorm"
bottom: "conv_blob14"
top: "batch_norm_blob14"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale14"
type: "Scale"
bottom: "batch_norm_blob14"
top: "batch_norm_blob14"
scale_param {
bias_term: true
}
}
layer {
name: "relu12"
type: "CPP"
bottom: "batch_norm_blob14"
top: "relu_blob12"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv15"
type: "Convolution"
bottom: "relu_blob12"
top: "conv_blob15"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm15"
type: "BatchNorm"
bottom: "conv_blob15"
top: "batch_norm_blob15"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale15"
type: "Scale"
bottom: "batch_norm_blob15"
top: "batch_norm_blob15"
scale_param {
bias_term: true
}
}
layer {
name: "add6"
type: "Eltwise"
bottom: "batch_norm_blob15"
bottom: "relu_blob11"
top: "add_blob6"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu13"
type: "CPP"
bottom: "add_blob6"
top: "relu_blob13"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv16"
type: "Convolution"
bottom: "relu_blob13"
top: "conv_blob16"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm16"
type: "BatchNorm"
bottom: "conv_blob16"
top: "batch_norm_blob16"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale16"
type: "Scale"
bottom: "batch_norm_blob16"
top: "batch_norm_blob16"
scale_param {
bias_term: true
}
}
layer {
name: "relu14"
type: "CPP"
bottom: "batch_norm_blob16"
top: "relu_blob14"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv17"
type: "Convolution"
bottom: "relu_blob14"
top: "conv_blob17"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm17"
type: "BatchNorm"
bottom: "conv_blob17"
top: "batch_norm_blob17"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale17"
type: "Scale"
bottom: "batch_norm_blob17"
top: "batch_norm_blob17"
scale_param {
bias_term: true
}
}
layer {
name: "add7"
type: "Eltwise"
bottom: "batch_norm_blob17"
bottom: "relu_blob13"
top: "add_blob7"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu15"
type: "CPP"
bottom: "add_blob7"
top: "relu_blob15"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv18"
type: "Convolution"
bottom: "relu_blob11"
top: "conv_blob18"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm18"
type: "BatchNorm"
bottom: "conv_blob18"
top: "batch_norm_blob18"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale18"
type: "Scale"
bottom: "batch_norm_blob18"
top: "batch_norm_blob18"
scale_param {
bias_term: true
}
}
layer {
name: "relu16"
type: "CPP"
bottom: "batch_norm_blob18"
top: "relu_blob16"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv19"
type: "Convolution"
bottom: "relu_blob16"
top: "conv_blob19"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm19"
type: "BatchNorm"
bottom: "conv_blob19"
top: "batch_norm_blob19"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale19"
type: "Scale"
bottom: "batch_norm_blob19"
top: "batch_norm_blob19"
scale_param {
bias_term: true
}
}
layer {
name: "conv20"
type: "Convolution"
bottom: "relu_blob11"
top: "conv_blob20"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm20"
type: "BatchNorm"
bottom: "conv_blob20"
top: "batch_norm_blob20"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale20"
type: "Scale"
bottom: "batch_norm_blob20"
top: "batch_norm_blob20"
scale_param {
bias_term: true
}
}
layer {
name: "add8"
type: "Eltwise"
bottom: "batch_norm_blob19"
bottom: "batch_norm_blob20"
top: "add_blob8"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu17"
type: "CPP"
bottom: "add_blob8"
top: "relu_blob17"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv21"
type: "Convolution"
bottom: "relu_blob17"
top: "conv_blob21"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm21"
type: "BatchNorm"
bottom: "conv_blob21"
top: "batch_norm_blob21"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale21"
type: "Scale"
bottom: "batch_norm_blob21"
top: "batch_norm_blob21"
scale_param {
bias_term: true
}
}
layer {
name: "relu18"
type: "CPP"
bottom: "batch_norm_blob21"
top: "relu_blob18"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv22"
type: "Convolution"
bottom: "relu_blob18"
top: "conv_blob22"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm22"
type: "BatchNorm"
bottom: "conv_blob22"
top: "batch_norm_blob22"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale22"
type: "Scale"
bottom: "batch_norm_blob22"
top: "batch_norm_blob22"
scale_param {
bias_term: true
}
}
layer {
name: "add9"
type: "Eltwise"
bottom: "batch_norm_blob22"
bottom: "relu_blob17"
top: "add_blob9"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu19"
type: "CPP"
bottom: "add_blob9"
top: "relu_blob19"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv23"
type: "Convolution"
bottom: "relu_blob19"
top: "conv_blob23"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm23"
type: "BatchNorm"
bottom: "conv_blob23"
top: "batch_norm_blob23"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale23"
type: "Scale"
bottom: "batch_norm_blob23"
top: "batch_norm_blob23"
scale_param {
bias_term: true
}
}
layer {
name: "relu20"
type: "CPP"
bottom: "batch_norm_blob23"
top: "relu_blob20"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv24"
type: "Convolution"
bottom: "relu_blob20"
top: "conv_blob24"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm24"
type: "BatchNorm"
bottom: "conv_blob24"
top: "batch_norm_blob24"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale24"
type: "Scale"
bottom: "batch_norm_blob24"
top: "batch_norm_blob24"
scale_param {
bias_term: true
}
}
layer {
name: "add10"
type: "Eltwise"
bottom: "batch_norm_blob24"
bottom: "relu_blob19"
top: "add_blob10"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu21"
type: "CPP"
bottom: "add_blob10"
top: "relu_blob21"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv25"
type: "Convolution"
bottom: "relu_blob21"
top: "conv_blob25"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm25"
type: "BatchNorm"
bottom: "conv_blob25"
top: "batch_norm_blob25"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale25"
type: "Scale"
bottom: "batch_norm_blob25"
top: "batch_norm_blob25"
scale_param {
bias_term: true
}
}
layer {
name: "relu22"
type: "CPP"
bottom: "batch_norm_blob25"
top: "relu_blob22"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv26"
type: "Convolution"
bottom: "relu_blob22"
top: "conv_blob26"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm26"
type: "BatchNorm"
bottom: "conv_blob26"
top: "batch_norm_blob26"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale26"
type: "Scale"
bottom: "batch_norm_blob26"
top: "batch_norm_blob26"
scale_param {
bias_term: true
}
}
layer {
name: "add11"
type: "Eltwise"
bottom: "batch_norm_blob26"
bottom: "relu_blob21"
top: "add_blob11"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu23"
type: "CPP"
bottom: "add_blob11"
top: "relu_blob23"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv27"
type: "Convolution"
bottom: "relu_blob19"
top: "conv_blob27"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm27"
type: "BatchNorm"
bottom: "conv_blob27"
top: "batch_norm_blob27"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale27"
type: "Scale"
bottom: "batch_norm_blob27"
top: "batch_norm_blob27"
scale_param {
bias_term: true
}
}
layer {
name: "relu24"
type: "CPP"
bottom: "batch_norm_blob27"
top: "relu_blob24"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv28"
type: "Convolution"
bottom: "relu_blob24"
top: "conv_blob28"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm28"
type: "BatchNorm"
bottom: "conv_blob28"
top: "batch_norm_blob28"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale28"
type: "Scale"
bottom: "batch_norm_blob28"
top: "batch_norm_blob28"
scale_param {
bias_term: true
}
}
layer {
name: "conv29"
type: "Convolution"
bottom: "relu_blob19"
top: "conv_blob29"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm29"
type: "BatchNorm"
bottom: "conv_blob29"
top: "batch_norm_blob29"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale29"
type: "Scale"
bottom: "batch_norm_blob29"
top: "batch_norm_blob29"
scale_param {
bias_term: true
}
}
layer {
name: "add12"
type: "Eltwise"
bottom: "batch_norm_blob28"
bottom: "batch_norm_blob29"
top: "add_blob12"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu25"
type: "CPP"
bottom: "add_blob12"
top: "relu_blob25"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv30"
type: "Convolution"
bottom: "relu_blob25"
top: "conv_blob30"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm30"
type: "BatchNorm"
bottom: "conv_blob30"
top: "batch_norm_blob30"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale30"
type: "Scale"
bottom: "batch_norm_blob30"
top: "batch_norm_blob30"
scale_param {
bias_term: true
}
}
layer {
name: "relu26"
type: "CPP"
bottom: "batch_norm_blob30"
top: "relu_blob26"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv31"
type: "Convolution"
bottom: "relu_blob26"
top: "conv_blob31"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm31"
type: "BatchNorm"
bottom: "conv_blob31"
top: "batch_norm_blob31"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale31"
type: "Scale"
bottom: "batch_norm_blob31"
top: "batch_norm_blob31"
scale_param {
bias_term: true
}
}
layer {
name: "add13"
type: "Eltwise"
bottom: "batch_norm_blob31"
bottom: "relu_blob25"
top: "add_blob13"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu27"
type: "CPP"
bottom: "add_blob13"
top: "relu_blob27"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv32"
type: "Convolution"
bottom: "relu_blob27"
top: "conv_blob32"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm32"
type: "BatchNorm"
bottom: "conv_blob32"
top: "batch_norm_blob32"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale32"
type: "Scale"
bottom: "batch_norm_blob32"
top: "batch_norm_blob32"
scale_param {
bias_term: true
}
}
layer {
name: "relu28"
type: "CPP"
bottom: "batch_norm_blob32"
top: "relu_blob28"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv33"
type: "Convolution"
bottom: "relu_blob28"
top: "conv_blob33"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm33"
type: "BatchNorm"
bottom: "conv_blob33"
top: "batch_norm_blob33"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale33"
type: "Scale"
bottom: "batch_norm_blob33"
top: "batch_norm_blob33"
scale_param {
bias_term: true
}
}
layer {
name: "add14"
type: "Eltwise"
bottom: "batch_norm_blob33"
bottom: "relu_blob27"
top: "add_blob14"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu29"
type: "CPP"
bottom: "add_blob14"
top: "relu_blob29"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv34"
type: "Convolution"
bottom: "relu_blob29"
top: "conv_blob34"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm34"
type: "BatchNorm"
bottom: "conv_blob34"
top: "batch_norm_blob34"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale34"
type: "Scale"
bottom: "batch_norm_blob34"
top: "batch_norm_blob34"
scale_param {
bias_term: true
}
}
layer {
name: "relu30"
type: "CPP"
bottom: "batch_norm_blob34"
top: "relu_blob30"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv35"
type: "Convolution"
bottom: "relu_blob30"
top: "conv_blob35"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm35"
type: "BatchNorm"
bottom: "conv_blob35"
top: "batch_norm_blob35"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale35"
type: "Scale"
bottom: "batch_norm_blob35"
top: "batch_norm_blob35"
scale_param {
bias_term: true
}
}
layer {
name: "add15"
type: "Eltwise"
bottom: "batch_norm_blob35"
bottom: "relu_blob29"
top: "add_blob15"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu31"
type: "CPP"
bottom: "add_blob15"
top: "relu_blob31"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv36"
type: "Convolution"
bottom: "relu_blob27"
top: "conv_blob36"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm36"
type: "BatchNorm"
bottom: "conv_blob36"
top: "batch_norm_blob36"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale36"
type: "Scale"
bottom: "batch_norm_blob36"
top: "batch_norm_blob36"
scale_param {
bias_term: true
}
}
layer {
name: "relu32"
type: "CPP"
bottom: "batch_norm_blob36"
top: "relu_blob32"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv37"
type: "Convolution"
bottom: "relu_blob32"
top: "conv_blob37"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm37"
type: "BatchNorm"
bottom: "conv_blob37"
top: "batch_norm_blob37"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale37"
type: "Scale"
bottom: "batch_norm_blob37"
top: "batch_norm_blob37"
scale_param {
bias_term: true
}
}
layer {
name: "conv38"
type: "Convolution"
bottom: "relu_blob27"
top: "conv_blob38"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm38"
type: "BatchNorm"
bottom: "conv_blob38"
top: "batch_norm_blob38"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale38"
type: "Scale"
bottom: "batch_norm_blob38"
top: "batch_norm_blob38"
scale_param {
bias_term: true
}
}
layer {
name: "add16"
type: "Eltwise"
bottom: "batch_norm_blob37"
bottom: "batch_norm_blob38"
top: "add_blob16"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu33"
type: "CPP"
bottom: "add_blob16"
top: "relu_blob33"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv39"
type: "Convolution"
bottom: "relu_blob33"
top: "conv_blob39"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm39"
type: "BatchNorm"
bottom: "conv_blob39"
top: "batch_norm_blob39"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale39"
type: "Scale"
bottom: "batch_norm_blob39"
top: "batch_norm_blob39"
scale_param {
bias_term: true
}
}
layer {
name: "relu34"
type: "CPP"
bottom: "batch_norm_blob39"
top: "relu_blob34"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv40"
type: "Convolution"
bottom: "relu_blob34"
top: "conv_blob40"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm40"
type: "BatchNorm"
bottom: "conv_blob40"
top: "batch_norm_blob40"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale40"
type: "Scale"
bottom: "batch_norm_blob40"
top: "batch_norm_blob40"
scale_param {
bias_term: true
}
}
layer {
name: "add17"
type: "Eltwise"
bottom: "batch_norm_blob40"
bottom: "relu_blob33"
top: "add_blob17"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu35"
type: "CPP"
bottom: "add_blob17"
top: "relu_blob35"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv41"
type: "Convolution"
bottom: "relu_blob35"
top: "conv_blob41"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm41"
type: "BatchNorm"
bottom: "conv_blob41"
top: "batch_norm_blob41"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale41"
type: "Scale"
bottom: "batch_norm_blob41"
top: "batch_norm_blob41"
scale_param {
bias_term: true
}
}
layer {
name: "relu36"
type: "CPP"
bottom: "batch_norm_blob41"
top: "relu_blob36"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv42"
type: "Convolution"
bottom: "relu_blob36"
top: "conv_blob42"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm42"
type: "BatchNorm"
bottom: "conv_blob42"
top: "batch_norm_blob42"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale42"
type: "Scale"
bottom: "batch_norm_blob42"
top: "batch_norm_blob42"
scale_param {
bias_term: true
}
}
layer {
name: "add18"
type: "Eltwise"
bottom: "batch_norm_blob42"
bottom: "relu_blob35"
top: "add_blob18"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu37"
type: "CPP"
bottom: "add_blob18"
top: "relu_blob37"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv43"
type: "Convolution"
bottom: "relu_blob37"
top: "conv_blob43"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm43"
type: "BatchNorm"
bottom: "conv_blob43"
top: "batch_norm_blob43"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale43"
type: "Scale"
bottom: "batch_norm_blob43"
top: "batch_norm_blob43"
scale_param {
bias_term: true
}
}
layer {
name: "relu38"
type: "CPP"
bottom: "batch_norm_blob43"
top: "relu_blob38"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv44"
type: "Convolution"
bottom: "relu_blob38"
top: "conv_blob44"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm44"
type: "BatchNorm"
bottom: "conv_blob44"
top: "batch_norm_blob44"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale44"
type: "Scale"
bottom: "batch_norm_blob44"
top: "batch_norm_blob44"
scale_param {
bias_term: true
}
}
layer {
name: "add19"
type: "Eltwise"
bottom: "batch_norm_blob44"
bottom: "relu_blob37"
top: "add_blob19"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu39"
type: "CPP"
bottom: "add_blob19"
top: "relu_blob39"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv45"
type: "Convolution"
bottom: "relu_blob35"
top: "conv_blob45"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm45"
type: "BatchNorm"
bottom: "conv_blob45"
top: "batch_norm_blob45"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale45"
type: "Scale"
bottom: "batch_norm_blob45"
top: "batch_norm_blob45"
scale_param {
bias_term: true
}
}
layer {
name: "relu40"
type: "CPP"
bottom: "batch_norm_blob45"
top: "relu_blob40"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv46"
type: "Convolution"
bottom: "relu_blob40"
top: "conv_blob46"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm46"
type: "BatchNorm"
bottom: "conv_blob46"
top: "batch_norm_blob46"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale46"
type: "Scale"
bottom: "batch_norm_blob46"
top: "batch_norm_blob46"
scale_param {
bias_term: true
}
}
layer {
name: "conv47"
type: "Convolution"
bottom: "relu_blob35"
top: "conv_blob47"
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm47"
type: "BatchNorm"
bottom: "conv_blob47"
top: "batch_norm_blob47"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale47"
type: "Scale"
bottom: "batch_norm_blob47"
top: "batch_norm_blob47"
scale_param {
bias_term: true
}
}
layer {
name: "add20"
type: "Eltwise"
bottom: "batch_norm_blob46"
bottom: "batch_norm_blob47"
top: "add_blob20"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu41"
type: "CPP"
bottom: "add_blob20"
top: "relu_blob41"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv48"
type: "Convolution"
bottom: "relu_blob41"
top: "conv_blob48"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm48"
type: "BatchNorm"
bottom: "conv_blob48"
top: "batch_norm_blob48"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale48"
type: "Scale"
bottom: "batch_norm_blob48"
top: "batch_norm_blob48"
scale_param {
bias_term: true
}
}
layer {
name: "relu42"
type: "CPP"
bottom: "batch_norm_blob48"
top: "relu_blob42"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv49"
type: "Convolution"
bottom: "relu_blob42"
top: "conv_blob49"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm49"
type: "BatchNorm"
bottom: "conv_blob49"
top: "batch_norm_blob49"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale49"
type: "Scale"
bottom: "batch_norm_blob49"
top: "batch_norm_blob49"
scale_param {
bias_term: true
}
}
layer {
name: "add21"
type: "Eltwise"
bottom: "batch_norm_blob49"
bottom: "relu_blob41"
top: "add_blob21"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu43"
type: "CPP"
bottom: "add_blob21"
top: "relu_blob43"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv50"
type: "Convolution"
bottom: "relu_blob43"
top: "conv_blob50"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm50"
type: "BatchNorm"
bottom: "conv_blob50"
top: "batch_norm_blob50"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale50"
type: "Scale"
bottom: "batch_norm_blob50"
top: "batch_norm_blob50"
scale_param {
bias_term: true
}
}
layer {
name: "relu44"
type: "CPP"
bottom: "batch_norm_blob50"
top: "relu_blob44"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv51"
type: "Convolution"
bottom: "relu_blob44"
top: "conv_blob51"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm51"
type: "BatchNorm"
bottom: "conv_blob51"
top: "batch_norm_blob51"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale51"
type: "Scale"
bottom: "batch_norm_blob51"
top: "batch_norm_blob51"
scale_param {
bias_term: true
}
}
layer {
name: "add22"
type: "Eltwise"
bottom: "batch_norm_blob51"
bottom: "relu_blob43"
top: "add_blob22"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu45"
type: "CPP"
bottom: "add_blob22"
top: "relu_blob45"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv52"
type: "Convolution"
bottom: "relu_blob45"
top: "conv_blob52"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm52"
type: "BatchNorm"
bottom: "conv_blob52"
top: "batch_norm_blob52"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale52"
type: "Scale"
bottom: "batch_norm_blob52"
top: "batch_norm_blob52"
scale_param {
bias_term: true
}
}
layer {
name: "relu46"
type: "CPP"
bottom: "batch_norm_blob52"
top: "relu_blob46"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv53"
type: "Convolution"
bottom: "relu_blob46"
top: "conv_blob53"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm53"
type: "BatchNorm"
bottom: "conv_blob53"
top: "batch_norm_blob53"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale53"
type: "Scale"
bottom: "batch_norm_blob53"
top: "batch_norm_blob53"
scale_param {
bias_term: true
}
}
layer {
name: "add23"
type: "Eltwise"
bottom: "batch_norm_blob53"
bottom: "relu_blob45"
top: "add_blob23"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu47"
type: "CPP"
bottom: "add_blob23"
top: "relu_blob47"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv54"
type: "Convolution"
bottom: "relu_blob47"
top: "conv_blob54"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm54"
type: "BatchNorm"
bottom: "conv_blob54"
top: "batch_norm_blob54"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale54"
type: "Scale"
bottom: "batch_norm_blob54"
top: "batch_norm_blob54"
scale_param {
bias_term: true
}
}
layer {
name: "relu48"
type: "CPP"
bottom: "batch_norm_blob54"
top: "relu_blob48"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv55"
type: "Convolution"
bottom: "relu_blob48"
top: "conv_blob55"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm55"
type: "BatchNorm"
bottom: "conv_blob55"
top: "batch_norm_blob55"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale55"
type: "Scale"
bottom: "batch_norm_blob55"
top: "batch_norm_blob55"
scale_param {
bias_term: true
}
}
layer {
name: "add24"
type: "Eltwise"
bottom: "batch_norm_blob55"
bottom: "relu_blob47"
top: "add_blob24"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu49"
type: "CPP"
bottom: "add_blob24"
top: "relu_blob49"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv56"
type: "Convolution"
bottom: "relu_blob49"
top: "conv_blob56"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm56"
type: "BatchNorm"
bottom: "conv_blob56"
top: "batch_norm_blob56"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale56"
type: "Scale"
bottom: "batch_norm_blob56"
top: "batch_norm_blob56"
scale_param {
bias_term: true
}
}
layer {
name: "relu50"
type: "CPP"
bottom: "batch_norm_blob56"
top: "relu_blob50"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv57"
type: "Convolution"
bottom: "relu_blob50"
top: "conv_blob57"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm57"
type: "BatchNorm"
bottom: "conv_blob57"
top: "batch_norm_blob57"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale57"
type: "Scale"
bottom: "batch_norm_blob57"
top: "batch_norm_blob57"
scale_param {
bias_term: true
}
}
layer {
name: "add25"
type: "Eltwise"
bottom: "batch_norm_blob57"
bottom: "relu_blob49"
top: "add_blob25"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu51"
type: "CPP"
bottom: "add_blob25"
top: "relu_blob51"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv58"
type: "Convolution"
bottom: "relu_blob51"
top: "conv_blob58"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm58"
type: "BatchNorm"
bottom: "conv_blob58"
top: "batch_norm_blob58"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale58"
type: "Scale"
bottom: "batch_norm_blob58"
top: "batch_norm_blob58"
scale_param {
bias_term: true
}
}
layer {
name: "relu52"
type: "CPP"
bottom: "batch_norm_blob58"
top: "relu_blob52"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv59"
type: "Convolution"
bottom: "relu_blob52"
top: "conv_blob59"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm59"
type: "BatchNorm"
bottom: "conv_blob59"
top: "batch_norm_blob59"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale59"
type: "Scale"
bottom: "batch_norm_blob59"
top: "batch_norm_blob59"
scale_param {
bias_term: true
}
}
layer {
name: "add26"
type: "Eltwise"
bottom: "batch_norm_blob59"
bottom: "relu_blob51"
top: "add_blob26"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu53"
type: "CPP"
bottom: "add_blob26"
top: "relu_blob53"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv60"
type: "Convolution"
bottom: "relu_blob53"
top: "conv_blob60"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm60"
type: "BatchNorm"
bottom: "conv_blob60"
top: "batch_norm_blob60"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale60"
type: "Scale"
bottom: "batch_norm_blob60"
top: "batch_norm_blob60"
scale_param {
bias_term: true
}
}
layer {
name: "relu54"
type: "CPP"
bottom: "batch_norm_blob60"
top: "relu_blob54"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv61"
type: "Convolution"
bottom: "relu_blob54"
top: "conv_blob61"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm61"
type: "BatchNorm"
bottom: "conv_blob61"
top: "batch_norm_blob61"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale61"
type: "Scale"
bottom: "batch_norm_blob61"
top: "batch_norm_blob61"
scale_param {
bias_term: true
}
}
layer {
name: "conv62"
type: "Convolution"
bottom: "relu_blob53"
top: "conv_blob62"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm62"
type: "BatchNorm"
bottom: "conv_blob62"
top: "batch_norm_blob62"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale62"
type: "Scale"
bottom: "batch_norm_blob62"
top: "batch_norm_blob62"
scale_param {
bias_term: true
}
}
layer {
name: "add27"
type: "Eltwise"
bottom: "batch_norm_blob61"
bottom: "batch_norm_blob62"
top: "add_blob27"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu55"
type: "CPP"
bottom: "add_blob27"
top: "relu_blob55"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample1"
type: "CPP"
bottom: "relu_blob55"
top: "upsample_blob1"
cpp_param {
param_str: "scale:2; upsample_h: 8; upsample_w: 8"
type: "Upsample"
}
}
layer {
name: "add28"
type: "Eltwise"
bottom: "relu_blob39"
bottom: "upsample_blob1"
top: "add_blob28"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv63"
type: "Convolution"
bottom: "add_blob28"
top: "conv_blob63"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm63"
type: "BatchNorm"
bottom: "conv_blob63"
top: "batch_norm_blob63"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale63"
type: "Scale"
bottom: "batch_norm_blob63"
top: "batch_norm_blob63"
scale_param {
bias_term: true
}
}
layer {
name: "relu56"
type: "CPP"
bottom: "batch_norm_blob63"
top: "relu_blob56"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv64"
type: "Convolution"
bottom: "relu_blob56"
top: "conv_blob64"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm64"
type: "BatchNorm"
bottom: "conv_blob64"
top: "batch_norm_blob64"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale64"
type: "Scale"
bottom: "batch_norm_blob64"
top: "batch_norm_blob64"
scale_param {
bias_term: true
}
}
layer {
name: "add29"
type: "Eltwise"
bottom: "batch_norm_blob64"
bottom: "add_blob28"
top: "add_blob29"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu57"
type: "CPP"
bottom: "add_blob29"
top: "relu_blob57"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv65"
type: "Convolution"
bottom: "relu_blob57"
top: "conv_blob65"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm65"
type: "BatchNorm"
bottom: "conv_blob65"
top: "batch_norm_blob65"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale65"
type: "Scale"
bottom: "batch_norm_blob65"
top: "batch_norm_blob65"
scale_param {
bias_term: true
}
}
layer {
name: "relu58"
type: "CPP"
bottom: "batch_norm_blob65"
top: "relu_blob58"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv66"
type: "Convolution"
bottom: "relu_blob58"
top: "conv_blob66"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm66"
type: "BatchNorm"
bottom: "conv_blob66"
top: "batch_norm_blob66"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale66"
type: "Scale"
bottom: "batch_norm_blob66"
top: "batch_norm_blob66"
scale_param {
bias_term: true
}
}
layer {
name: "add30"
type: "Eltwise"
bottom: "batch_norm_blob66"
bottom: "relu_blob57"
top: "add_blob30"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu59"
type: "CPP"
bottom: "add_blob30"
top: "relu_blob59"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample2"
type: "CPP"
bottom: "relu_blob59"
top: "upsample_blob2"
cpp_param {
param_str: "scale:2; upsample_h: 16; upsample_w: 16"
type: "Upsample"
}
}
layer {
name: "add31"
type: "Eltwise"
bottom: "relu_blob31"
bottom: "upsample_blob2"
top: "add_blob31"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv67"
type: "Convolution"
bottom: "add_blob31"
top: "conv_blob67"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm67"
type: "BatchNorm"
bottom: "conv_blob67"
top: "batch_norm_blob67"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale67"
type: "Scale"
bottom: "batch_norm_blob67"
top: "batch_norm_blob67"
scale_param {
bias_term: true
}
}
layer {
name: "relu60"
type: "CPP"
bottom: "batch_norm_blob67"
top: "relu_blob60"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv68"
type: "Convolution"
bottom: "relu_blob60"
top: "conv_blob68"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm68"
type: "BatchNorm"
bottom: "conv_blob68"
top: "batch_norm_blob68"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale68"
type: "Scale"
bottom: "batch_norm_blob68"
top: "batch_norm_blob68"
scale_param {
bias_term: true
}
}
layer {
name: "add32"
type: "Eltwise"
bottom: "batch_norm_blob68"
bottom: "add_blob31"
top: "add_blob32"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu61"
type: "CPP"
bottom: "add_blob32"
top: "relu_blob61"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv69"
type: "Convolution"
bottom: "relu_blob61"
top: "conv_blob69"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm69"
type: "BatchNorm"
bottom: "conv_blob69"
top: "batch_norm_blob69"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale69"
type: "Scale"
bottom: "batch_norm_blob69"
top: "batch_norm_blob69"
scale_param {
bias_term: true
}
}
layer {
name: "relu62"
type: "CPP"
bottom: "batch_norm_blob69"
top: "relu_blob62"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv70"
type: "Convolution"
bottom: "relu_blob62"
top: "conv_blob70"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm70"
type: "BatchNorm"
bottom: "conv_blob70"
top: "batch_norm_blob70"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale70"
type: "Scale"
bottom: "batch_norm_blob70"
top: "batch_norm_blob70"
scale_param {
bias_term: true
}
}
layer {
name: "add33"
type: "Eltwise"
bottom: "batch_norm_blob70"
bottom: "relu_blob61"
top: "add_blob33"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu63"
type: "CPP"
bottom: "add_blob33"
top: "relu_blob63"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample3"
type: "CPP"
bottom: "relu_blob63"
top: "upsample_blob3"
cpp_param {
param_str: "scale:2; upsample_h: 32; upsample_w: 32"
type: "Upsample"
}
}
layer {
name: "add34"
type: "Eltwise"
bottom: "relu_blob23"
bottom: "upsample_blob3"
top: "add_blob34"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv71"
type: "Convolution"
bottom: "add_blob34"
top: "conv_blob71"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm71"
type: "BatchNorm"
bottom: "conv_blob71"
top: "batch_norm_blob71"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale71"
type: "Scale"
bottom: "batch_norm_blob71"
top: "batch_norm_blob71"
scale_param {
bias_term: true
}
}
layer {
name: "relu64"
type: "CPP"
bottom: "batch_norm_blob71"
top: "relu_blob64"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv72"
type: "Convolution"
bottom: "relu_blob64"
top: "conv_blob72"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm72"
type: "BatchNorm"
bottom: "conv_blob72"
top: "batch_norm_blob72"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale72"
type: "Scale"
bottom: "batch_norm_blob72"
top: "batch_norm_blob72"
scale_param {
bias_term: true
}
}
layer {
name: "add35"
type: "Eltwise"
bottom: "batch_norm_blob72"
bottom: "add_blob34"
top: "add_blob35"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu65"
type: "CPP"
bottom: "add_blob35"
top: "relu_blob65"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv73"
type: "Convolution"
bottom: "relu_blob65"
top: "conv_blob73"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm73"
type: "BatchNorm"
bottom: "conv_blob73"
top: "batch_norm_blob73"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale73"
type: "Scale"
bottom: "batch_norm_blob73"
top: "batch_norm_blob73"
scale_param {
bias_term: true
}
}
layer {
name: "relu66"
type: "CPP"
bottom: "batch_norm_blob73"
top: "relu_blob66"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv74"
type: "Convolution"
bottom: "relu_blob66"
top: "conv_blob74"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm74"
type: "BatchNorm"
bottom: "conv_blob74"
top: "batch_norm_blob74"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale74"
type: "Scale"
bottom: "batch_norm_blob74"
top: "batch_norm_blob74"
scale_param {
bias_term: true
}
}
layer {
name: "conv75"
type: "Convolution"
bottom: "relu_blob65"
top: "conv_blob75"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm75"
type: "BatchNorm"
bottom: "conv_blob75"
top: "batch_norm_blob75"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale75"
type: "Scale"
bottom: "batch_norm_blob75"
top: "batch_norm_blob75"
scale_param {
bias_term: true
}
}
layer {
name: "add36"
type: "Eltwise"
bottom: "batch_norm_blob74"
bottom: "batch_norm_blob75"
top: "add_blob36"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu67"
type: "CPP"
bottom: "add_blob36"
top: "relu_blob67"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample4"
type: "CPP"
bottom: "relu_blob67"
top: "upsample_blob4"
cpp_param {
param_str: "scale:2; upsample_h: 64; upsample_w: 64"
type: "Upsample"
}
}
layer {
name: "add37"
type: "Eltwise"
bottom: "relu_blob15"
bottom: "upsample_blob4"
top: "add_blob37"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv76"
type: "Convolution"
bottom: "add_blob37"
top: "conv_blob76"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm76"
type: "BatchNorm"
bottom: "conv_blob76"
top: "batch_norm_blob76"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale76"
type: "Scale"
bottom: "batch_norm_blob76"
top: "batch_norm_blob76"
scale_param {
bias_term: true
}
}
layer {
name: "relu68"
type: "CPP"
bottom: "batch_norm_blob76"
top: "relu_blob68"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv77"
type: "Convolution"
bottom: "relu_blob68"
top: "conv_blob77"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm77"
type: "BatchNorm"
bottom: "conv_blob77"
top: "batch_norm_blob77"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale77"
type: "Scale"
bottom: "batch_norm_blob77"
top: "batch_norm_blob77"
scale_param {
bias_term: true
}
}
layer {
name: "add38"
type: "Eltwise"
bottom: "batch_norm_blob77"
bottom: "add_blob37"
top: "add_blob38"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu69"
type: "CPP"
bottom: "add_blob38"
top: "relu_blob69"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv78"
type: "Convolution"
bottom: "relu_blob69"
top: "conv_blob78"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm78"
type: "BatchNorm"
bottom: "conv_blob78"
top: "batch_norm_blob78"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale78"
type: "Scale"
bottom: "batch_norm_blob78"
top: "batch_norm_blob78"
scale_param {
bias_term: true
}
}
layer {
name: "relu70"
type: "CPP"
bottom: "batch_norm_blob78"
top: "relu_blob70"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv79"
type: "Convolution"
bottom: "relu_blob70"
top: "conv_blob79"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm79"
type: "BatchNorm"
bottom: "conv_blob79"
top: "batch_norm_blob79"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale79"
type: "Scale"
bottom: "batch_norm_blob79"
top: "batch_norm_blob79"
scale_param {
bias_term: true
}
}
layer {
name: "add39"
type: "Eltwise"
bottom: "batch_norm_blob79"
bottom: "relu_blob69"
top: "add_blob39"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu71"
type: "CPP"
bottom: "add_blob39"
top: "relu_blob71"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample5"
type: "CPP"
bottom: "relu_blob71"
top: "upsample_blob5"
cpp_param {
param_str: "scale:2; upsample_h: 128; upsample_w: 128"
type: "Upsample"
}
}
layer {
name: "add40"
type: "Eltwise"
bottom: "relu_blob7"
bottom: "upsample_blob5"
top: "add_blob40"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv80"
type: "Convolution"
bottom: "add_blob40"
top: "conv_blob80"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm80"
type: "BatchNorm"
bottom: "conv_blob80"
top: "batch_norm_blob80"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale80"
type: "Scale"
bottom: "batch_norm_blob80"
top: "batch_norm_blob80"
scale_param {
bias_term: true
}
}
layer {
name: "relu72"
type: "CPP"
bottom: "batch_norm_blob80"
top: "relu_blob72"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv81"
type: "Convolution"
bottom: "relu_blob3"
top: "conv_blob81"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm81"
type: "BatchNorm"
bottom: "conv_blob81"
top: "batch_norm_blob81"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale81"
type: "Scale"
bottom: "batch_norm_blob81"
top: "batch_norm_blob81"
scale_param {
bias_term: true
}
}
layer {
name: "conv82"
type: "Convolution"
bottom: "relu_blob72"
top: "conv_blob82"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm82"
type: "BatchNorm"
bottom: "conv_blob82"
top: "batch_norm_blob82"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale82"
type: "Scale"
bottom: "batch_norm_blob82"
top: "batch_norm_blob82"
scale_param {
bias_term: true
}
}
layer {
name: "add41"
type: "Eltwise"
bottom: "batch_norm_blob81"
bottom: "batch_norm_blob82"
top: "add_blob41"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu73"
type: "CPP"
bottom: "add_blob41"
top: "relu_blob73"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv83"
type: "Convolution"
bottom: "relu_blob73"
top: "conv_blob83"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm83"
type: "BatchNorm"
bottom: "conv_blob83"
top: "batch_norm_blob83"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale83"
type: "Scale"
bottom: "batch_norm_blob83"
top: "batch_norm_blob83"
scale_param {
bias_term: true
}
}
layer {
name: "relu74"
type: "CPP"
bottom: "batch_norm_blob83"
top: "relu_blob74"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv84"
type: "Convolution"
bottom: "relu_blob74"
top: "conv_blob84"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm84"
type: "BatchNorm"
bottom: "conv_blob84"
top: "batch_norm_blob84"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale84"
type: "Scale"
bottom: "batch_norm_blob84"
top: "batch_norm_blob84"
scale_param {
bias_term: true
}
}
layer {
name: "add42"
type: "Eltwise"
bottom: "batch_norm_blob84"
bottom: "relu_blob73"
top: "add_blob42"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu75"
type: "CPP"
bottom: "add_blob42"
top: "relu_blob75"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv85"
type: "Convolution"
bottom: "relu_blob75"
top: "conv_blob85"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm85"
type: "BatchNorm"
bottom: "conv_blob85"
top: "batch_norm_blob85"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale85"
type: "Scale"
bottom: "batch_norm_blob85"
top: "batch_norm_blob85"
scale_param {
bias_term: true
}
}
layer {
name: "relu76"
type: "CPP"
bottom: "batch_norm_blob85"
top: "relu_blob76"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv86"
type: "Convolution"
bottom: "relu_blob76"
top: "conv_blob86"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm86"
type: "BatchNorm"
bottom: "conv_blob86"
top: "batch_norm_blob86"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale86"
type: "Scale"
bottom: "batch_norm_blob86"
top: "batch_norm_blob86"
scale_param {
bias_term: true
}
}
layer {
name: "add43"
type: "Eltwise"
bottom: "batch_norm_blob86"
bottom: "relu_blob75"
top: "add_blob43"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu77"
type: "CPP"
bottom: "add_blob43"
top: "relu_blob77"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv87"
type: "Convolution"
bottom: "relu_blob77"
top: "conv_blob87"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm87"
type: "BatchNorm"
bottom: "conv_blob87"
top: "batch_norm_blob87"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale87"
type: "Scale"
bottom: "batch_norm_blob87"
top: "batch_norm_blob87"
scale_param {
bias_term: true
}
}
layer {
name: "relu78"
type: "CPP"
bottom: "batch_norm_blob87"
top: "relu_blob78"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv88"
type: "Convolution"
bottom: "relu_blob78"
top: "conv_blob88"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm88"
type: "BatchNorm"
bottom: "conv_blob88"
top: "batch_norm_blob88"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale88"
type: "Scale"
bottom: "batch_norm_blob88"
top: "batch_norm_blob88"
scale_param {
bias_term: true
}
}
layer {
name: "add44"
type: "Eltwise"
bottom: "batch_norm_blob88"
bottom: "relu_blob77"
top: "add_blob44"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu79"
type: "CPP"
bottom: "add_blob44"
top: "relu_blob79"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv89"
type: "Convolution"
bottom: "relu_blob75"
top: "conv_blob89"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm89"
type: "BatchNorm"
bottom: "conv_blob89"
top: "batch_norm_blob89"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale89"
type: "Scale"
bottom: "batch_norm_blob89"
top: "batch_norm_blob89"
scale_param {
bias_term: true
}
}
layer {
name: "relu80"
type: "CPP"
bottom: "batch_norm_blob89"
top: "relu_blob80"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv90"
type: "Convolution"
bottom: "relu_blob80"
top: "conv_blob90"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm90"
type: "BatchNorm"
bottom: "conv_blob90"
top: "batch_norm_blob90"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale90"
type: "Scale"
bottom: "batch_norm_blob90"
top: "batch_norm_blob90"
scale_param {
bias_term: true
}
}
layer {
name: "conv91"
type: "Convolution"
bottom: "relu_blob75"
top: "conv_blob91"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm91"
type: "BatchNorm"
bottom: "conv_blob91"
top: "batch_norm_blob91"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale91"
type: "Scale"
bottom: "batch_norm_blob91"
top: "batch_norm_blob91"
scale_param {
bias_term: true
}
}
layer {
name: "add45"
type: "Eltwise"
bottom: "batch_norm_blob90"
bottom: "batch_norm_blob91"
top: "add_blob45"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu81"
type: "CPP"
bottom: "add_blob45"
top: "relu_blob81"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv92"
type: "Convolution"
bottom: "relu_blob81"
top: "conv_blob92"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm92"
type: "BatchNorm"
bottom: "conv_blob92"
top: "batch_norm_blob92"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale92"
type: "Scale"
bottom: "batch_norm_blob92"
top: "batch_norm_blob92"
scale_param {
bias_term: true
}
}
layer {
name: "relu82"
type: "CPP"
bottom: "batch_norm_blob92"
top: "relu_blob82"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv93"
type: "Convolution"
bottom: "relu_blob82"
top: "conv_blob93"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm93"
type: "BatchNorm"
bottom: "conv_blob93"
top: "batch_norm_blob93"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale93"
type: "Scale"
bottom: "batch_norm_blob93"
top: "batch_norm_blob93"
scale_param {
bias_term: true
}
}
layer {
name: "add46"
type: "Eltwise"
bottom: "batch_norm_blob93"
bottom: "relu_blob81"
top: "add_blob46"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu83"
type: "CPP"
bottom: "add_blob46"
top: "relu_blob83"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv94"
type: "Convolution"
bottom: "relu_blob83"
top: "conv_blob94"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm94"
type: "BatchNorm"
bottom: "conv_blob94"
top: "batch_norm_blob94"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale94"
type: "Scale"
bottom: "batch_norm_blob94"
top: "batch_norm_blob94"
scale_param {
bias_term: true
}
}
layer {
name: "relu84"
type: "CPP"
bottom: "batch_norm_blob94"
top: "relu_blob84"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv95"
type: "Convolution"
bottom: "relu_blob84"
top: "conv_blob95"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm95"
type: "BatchNorm"
bottom: "conv_blob95"
top: "batch_norm_blob95"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale95"
type: "Scale"
bottom: "batch_norm_blob95"
top: "batch_norm_blob95"
scale_param {
bias_term: true
}
}
layer {
name: "add47"
type: "Eltwise"
bottom: "batch_norm_blob95"
bottom: "relu_blob83"
top: "add_blob47"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu85"
type: "CPP"
bottom: "add_blob47"
top: "relu_blob85"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv96"
type: "Convolution"
bottom: "relu_blob85"
top: "conv_blob96"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm96"
type: "BatchNorm"
bottom: "conv_blob96"
top: "batch_norm_blob96"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale96"
type: "Scale"
bottom: "batch_norm_blob96"
top: "batch_norm_blob96"
scale_param {
bias_term: true
}
}
layer {
name: "relu86"
type: "CPP"
bottom: "batch_norm_blob96"
top: "relu_blob86"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv97"
type: "Convolution"
bottom: "relu_blob86"
top: "conv_blob97"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm97"
type: "BatchNorm"
bottom: "conv_blob97"
top: "batch_norm_blob97"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale97"
type: "Scale"
bottom: "batch_norm_blob97"
top: "batch_norm_blob97"
scale_param {
bias_term: true
}
}
layer {
name: "add48"
type: "Eltwise"
bottom: "batch_norm_blob97"
bottom: "relu_blob85"
top: "add_blob48"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu87"
type: "CPP"
bottom: "add_blob48"
top: "relu_blob87"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv98"
type: "Convolution"
bottom: "relu_blob83"
top: "conv_blob98"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm98"
type: "BatchNorm"
bottom: "conv_blob98"
top: "batch_norm_blob98"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale98"
type: "Scale"
bottom: "batch_norm_blob98"
top: "batch_norm_blob98"
scale_param {
bias_term: true
}
}
layer {
name: "relu88"
type: "CPP"
bottom: "batch_norm_blob98"
top: "relu_blob88"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv99"
type: "Convolution"
bottom: "relu_blob88"
top: "conv_blob99"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm99"
type: "BatchNorm"
bottom: "conv_blob99"
top: "batch_norm_blob99"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale99"
type: "Scale"
bottom: "batch_norm_blob99"
top: "batch_norm_blob99"
scale_param {
bias_term: true
}
}
layer {
name: "conv100"
type: "Convolution"
bottom: "relu_blob83"
top: "conv_blob100"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm100"
type: "BatchNorm"
bottom: "conv_blob100"
top: "batch_norm_blob100"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale100"
type: "Scale"
bottom: "batch_norm_blob100"
top: "batch_norm_blob100"
scale_param {
bias_term: true
}
}
layer {
name: "add49"
type: "Eltwise"
bottom: "batch_norm_blob99"
bottom: "batch_norm_blob100"
top: "add_blob49"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu89"
type: "CPP"
bottom: "add_blob49"
top: "relu_blob89"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv101"
type: "Convolution"
bottom: "relu_blob89"
top: "conv_blob101"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm101"
type: "BatchNorm"
bottom: "conv_blob101"
top: "batch_norm_blob101"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale101"
type: "Scale"
bottom: "batch_norm_blob101"
top: "batch_norm_blob101"
scale_param {
bias_term: true
}
}
layer {
name: "relu90"
type: "CPP"
bottom: "batch_norm_blob101"
top: "relu_blob90"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv102"
type: "Convolution"
bottom: "relu_blob90"
top: "conv_blob102"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm102"
type: "BatchNorm"
bottom: "conv_blob102"
top: "batch_norm_blob102"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale102"
type: "Scale"
bottom: "batch_norm_blob102"
top: "batch_norm_blob102"
scale_param {
bias_term: true
}
}
layer {
name: "add50"
type: "Eltwise"
bottom: "batch_norm_blob102"
bottom: "relu_blob89"
top: "add_blob50"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu91"
type: "CPP"
bottom: "add_blob50"
top: "relu_blob91"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv103"
type: "Convolution"
bottom: "relu_blob91"
top: "conv_blob103"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm103"
type: "BatchNorm"
bottom: "conv_blob103"
top: "batch_norm_blob103"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale103"
type: "Scale"
bottom: "batch_norm_blob103"
top: "batch_norm_blob103"
scale_param {
bias_term: true
}
}
layer {
name: "relu92"
type: "CPP"
bottom: "batch_norm_blob103"
top: "relu_blob92"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv104"
type: "Convolution"
bottom: "relu_blob92"
top: "conv_blob104"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm104"
type: "BatchNorm"
bottom: "conv_blob104"
top: "batch_norm_blob104"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale104"
type: "Scale"
bottom: "batch_norm_blob104"
top: "batch_norm_blob104"
scale_param {
bias_term: true
}
}
layer {
name: "add51"
type: "Eltwise"
bottom: "batch_norm_blob104"
bottom: "relu_blob91"
top: "add_blob51"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu93"
type: "CPP"
bottom: "add_blob51"
top: "relu_blob93"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv105"
type: "Convolution"
bottom: "relu_blob93"
top: "conv_blob105"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm105"
type: "BatchNorm"
bottom: "conv_blob105"
top: "batch_norm_blob105"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale105"
type: "Scale"
bottom: "batch_norm_blob105"
top: "batch_norm_blob105"
scale_param {
bias_term: true
}
}
layer {
name: "relu94"
type: "CPP"
bottom: "batch_norm_blob105"
top: "relu_blob94"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv106"
type: "Convolution"
bottom: "relu_blob94"
top: "conv_blob106"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm106"
type: "BatchNorm"
bottom: "conv_blob106"
top: "batch_norm_blob106"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale106"
type: "Scale"
bottom: "batch_norm_blob106"
top: "batch_norm_blob106"
scale_param {
bias_term: true
}
}
layer {
name: "add52"
type: "Eltwise"
bottom: "batch_norm_blob106"
bottom: "relu_blob93"
top: "add_blob52"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu95"
type: "CPP"
bottom: "add_blob52"
top: "relu_blob95"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv107"
type: "Convolution"
bottom: "relu_blob91"
top: "conv_blob107"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm107"
type: "BatchNorm"
bottom: "conv_blob107"
top: "batch_norm_blob107"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale107"
type: "Scale"
bottom: "batch_norm_blob107"
top: "batch_norm_blob107"
scale_param {
bias_term: true
}
}
layer {
name: "relu96"
type: "CPP"
bottom: "batch_norm_blob107"
top: "relu_blob96"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv108"
type: "Convolution"
bottom: "relu_blob96"
top: "conv_blob108"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm108"
type: "BatchNorm"
bottom: "conv_blob108"
top: "batch_norm_blob108"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale108"
type: "Scale"
bottom: "batch_norm_blob108"
top: "batch_norm_blob108"
scale_param {
bias_term: true
}
}
layer {
name: "conv109"
type: "Convolution"
bottom: "relu_blob91"
top: "conv_blob109"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm109"
type: "BatchNorm"
bottom: "conv_blob109"
top: "batch_norm_blob109"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale109"
type: "Scale"
bottom: "batch_norm_blob109"
top: "batch_norm_blob109"
scale_param {
bias_term: true
}
}
layer {
name: "add53"
type: "Eltwise"
bottom: "batch_norm_blob108"
bottom: "batch_norm_blob109"
top: "add_blob53"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu97"
type: "CPP"
bottom: "add_blob53"
top: "relu_blob97"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv110"
type: "Convolution"
bottom: "relu_blob97"
top: "conv_blob110"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm110"
type: "BatchNorm"
bottom: "conv_blob110"
top: "batch_norm_blob110"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale110"
type: "Scale"
bottom: "batch_norm_blob110"
top: "batch_norm_blob110"
scale_param {
bias_term: true
}
}
layer {
name: "relu98"
type: "CPP"
bottom: "batch_norm_blob110"
top: "relu_blob98"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv111"
type: "Convolution"
bottom: "relu_blob98"
top: "conv_blob111"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm111"
type: "BatchNorm"
bottom: "conv_blob111"
top: "batch_norm_blob111"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale111"
type: "Scale"
bottom: "batch_norm_blob111"
top: "batch_norm_blob111"
scale_param {
bias_term: true
}
}
layer {
name: "add54"
type: "Eltwise"
bottom: "batch_norm_blob111"
bottom: "relu_blob97"
top: "add_blob54"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu99"
type: "CPP"
bottom: "add_blob54"
top: "relu_blob99"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv112"
type: "Convolution"
bottom: "relu_blob99"
top: "conv_blob112"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm112"
type: "BatchNorm"
bottom: "conv_blob112"
top: "batch_norm_blob112"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale112"
type: "Scale"
bottom: "batch_norm_blob112"
top: "batch_norm_blob112"
scale_param {
bias_term: true
}
}
layer {
name: "relu100"
type: "CPP"
bottom: "batch_norm_blob112"
top: "relu_blob100"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv113"
type: "Convolution"
bottom: "relu_blob100"
top: "conv_blob113"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm113"
type: "BatchNorm"
bottom: "conv_blob113"
top: "batch_norm_blob113"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale113"
type: "Scale"
bottom: "batch_norm_blob113"
top: "batch_norm_blob113"
scale_param {
bias_term: true
}
}
layer {
name: "add55"
type: "Eltwise"
bottom: "batch_norm_blob113"
bottom: "relu_blob99"
top: "add_blob55"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu101"
type: "CPP"
bottom: "add_blob55"
top: "relu_blob101"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv114"
type: "Convolution"
bottom: "relu_blob101"
top: "conv_blob114"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm114"
type: "BatchNorm"
bottom: "conv_blob114"
top: "batch_norm_blob114"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale114"
type: "Scale"
bottom: "batch_norm_blob114"
top: "batch_norm_blob114"
scale_param {
bias_term: true
}
}
layer {
name: "relu102"
type: "CPP"
bottom: "batch_norm_blob114"
top: "relu_blob102"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv115"
type: "Convolution"
bottom: "relu_blob102"
top: "conv_blob115"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm115"
type: "BatchNorm"
bottom: "conv_blob115"
top: "batch_norm_blob115"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale115"
type: "Scale"
bottom: "batch_norm_blob115"
top: "batch_norm_blob115"
scale_param {
bias_term: true
}
}
layer {
name: "add56"
type: "Eltwise"
bottom: "batch_norm_blob115"
bottom: "relu_blob101"
top: "add_blob56"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu103"
type: "CPP"
bottom: "add_blob56"
top: "relu_blob103"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv116"
type: "Convolution"
bottom: "relu_blob99"
top: "conv_blob116"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm116"
type: "BatchNorm"
bottom: "conv_blob116"
top: "batch_norm_blob116"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale116"
type: "Scale"
bottom: "batch_norm_blob116"
top: "batch_norm_blob116"
scale_param {
bias_term: true
}
}
layer {
name: "relu104"
type: "CPP"
bottom: "batch_norm_blob116"
top: "relu_blob104"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv117"
type: "Convolution"
bottom: "relu_blob104"
top: "conv_blob117"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm117"
type: "BatchNorm"
bottom: "conv_blob117"
top: "batch_norm_blob117"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale117"
type: "Scale"
bottom: "batch_norm_blob117"
top: "batch_norm_blob117"
scale_param {
bias_term: true
}
}
layer {
name: "conv118"
type: "Convolution"
bottom: "relu_blob99"
top: "conv_blob118"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm118"
type: "BatchNorm"
bottom: "conv_blob118"
top: "batch_norm_blob118"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale118"
type: "Scale"
bottom: "batch_norm_blob118"
top: "batch_norm_blob118"
scale_param {
bias_term: true
}
}
layer {
name: "add57"
type: "Eltwise"
bottom: "batch_norm_blob117"
bottom: "batch_norm_blob118"
top: "add_blob57"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu105"
type: "CPP"
bottom: "add_blob57"
top: "relu_blob105"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv119"
type: "Convolution"
bottom: "relu_blob105"
top: "conv_blob119"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm119"
type: "BatchNorm"
bottom: "conv_blob119"
top: "batch_norm_blob119"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale119"
type: "Scale"
bottom: "batch_norm_blob119"
top: "batch_norm_blob119"
scale_param {
bias_term: true
}
}
layer {
name: "relu106"
type: "CPP"
bottom: "batch_norm_blob119"
top: "relu_blob106"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv120"
type: "Convolution"
bottom: "relu_blob106"
top: "conv_blob120"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm120"
type: "BatchNorm"
bottom: "conv_blob120"
top: "batch_norm_blob120"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale120"
type: "Scale"
bottom: "batch_norm_blob120"
top: "batch_norm_blob120"
scale_param {
bias_term: true
}
}
layer {
name: "add58"
type: "Eltwise"
bottom: "batch_norm_blob120"
bottom: "relu_blob105"
top: "add_blob58"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu107"
type: "CPP"
bottom: "add_blob58"
top: "relu_blob107"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv121"
type: "Convolution"
bottom: "relu_blob107"
top: "conv_blob121"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm121"
type: "BatchNorm"
bottom: "conv_blob121"
top: "batch_norm_blob121"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale121"
type: "Scale"
bottom: "batch_norm_blob121"
top: "batch_norm_blob121"
scale_param {
bias_term: true
}
}
layer {
name: "relu108"
type: "CPP"
bottom: "batch_norm_blob121"
top: "relu_blob108"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv122"
type: "Convolution"
bottom: "relu_blob108"
top: "conv_blob122"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm122"
type: "BatchNorm"
bottom: "conv_blob122"
top: "batch_norm_blob122"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale122"
type: "Scale"
bottom: "batch_norm_blob122"
top: "batch_norm_blob122"
scale_param {
bias_term: true
}
}
layer {
name: "add59"
type: "Eltwise"
bottom: "batch_norm_blob122"
bottom: "relu_blob107"
top: "add_blob59"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu109"
type: "CPP"
bottom: "add_blob59"
top: "relu_blob109"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv123"
type: "Convolution"
bottom: "relu_blob109"
top: "conv_blob123"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm123"
type: "BatchNorm"
bottom: "conv_blob123"
top: "batch_norm_blob123"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale123"
type: "Scale"
bottom: "batch_norm_blob123"
top: "batch_norm_blob123"
scale_param {
bias_term: true
}
}
layer {
name: "relu110"
type: "CPP"
bottom: "batch_norm_blob123"
top: "relu_blob110"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv124"
type: "Convolution"
bottom: "relu_blob110"
top: "conv_blob124"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm124"
type: "BatchNorm"
bottom: "conv_blob124"
top: "batch_norm_blob124"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale124"
type: "Scale"
bottom: "batch_norm_blob124"
top: "batch_norm_blob124"
scale_param {
bias_term: true
}
}
layer {
name: "add60"
type: "Eltwise"
bottom: "batch_norm_blob124"
bottom: "relu_blob109"
top: "add_blob60"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu111"
type: "CPP"
bottom: "add_blob60"
top: "relu_blob111"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv125"
type: "Convolution"
bottom: "relu_blob107"
top: "conv_blob125"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm125"
type: "BatchNorm"
bottom: "conv_blob125"
top: "batch_norm_blob125"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale125"
type: "Scale"
bottom: "batch_norm_blob125"
top: "batch_norm_blob125"
scale_param {
bias_term: true
}
}
layer {
name: "relu112"
type: "CPP"
bottom: "batch_norm_blob125"
top: "relu_blob112"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv126"
type: "Convolution"
bottom: "relu_blob112"
top: "conv_blob126"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm126"
type: "BatchNorm"
bottom: "conv_blob126"
top: "batch_norm_blob126"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale126"
type: "Scale"
bottom: "batch_norm_blob126"
top: "batch_norm_blob126"
scale_param {
bias_term: true
}
}
layer {
name: "conv127"
type: "Convolution"
bottom: "relu_blob107"
top: "conv_blob127"
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 2
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm127"
type: "BatchNorm"
bottom: "conv_blob127"
top: "batch_norm_blob127"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale127"
type: "Scale"
bottom: "batch_norm_blob127"
top: "batch_norm_blob127"
scale_param {
bias_term: true
}
}
layer {
name: "add61"
type: "Eltwise"
bottom: "batch_norm_blob126"
bottom: "batch_norm_blob127"
top: "add_blob61"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu113"
type: "CPP"
bottom: "add_blob61"
top: "relu_blob113"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv128"
type: "Convolution"
bottom: "relu_blob113"
top: "conv_blob128"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm128"
type: "BatchNorm"
bottom: "conv_blob128"
top: "batch_norm_blob128"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale128"
type: "Scale"
bottom: "batch_norm_blob128"
top: "batch_norm_blob128"
scale_param {
bias_term: true
}
}
layer {
name: "relu114"
type: "CPP"
bottom: "batch_norm_blob128"
top: "relu_blob114"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv129"
type: "Convolution"
bottom: "relu_blob114"
top: "conv_blob129"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm129"
type: "BatchNorm"
bottom: "conv_blob129"
top: "batch_norm_blob129"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale129"
type: "Scale"
bottom: "batch_norm_blob129"
top: "batch_norm_blob129"
scale_param {
bias_term: true
}
}
layer {
name: "add62"
type: "Eltwise"
bottom: "batch_norm_blob129"
bottom: "relu_blob113"
top: "add_blob62"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu115"
type: "CPP"
bottom: "add_blob62"
top: "relu_blob115"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv130"
type: "Convolution"
bottom: "relu_blob115"
top: "conv_blob130"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm130"
type: "BatchNorm"
bottom: "conv_blob130"
top: "batch_norm_blob130"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale130"
type: "Scale"
bottom: "batch_norm_blob130"
top: "batch_norm_blob130"
scale_param {
bias_term: true
}
}
layer {
name: "relu116"
type: "CPP"
bottom: "batch_norm_blob130"
top: "relu_blob116"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv131"
type: "Convolution"
bottom: "relu_blob116"
top: "conv_blob131"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm131"
type: "BatchNorm"
bottom: "conv_blob131"
top: "batch_norm_blob131"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale131"
type: "Scale"
bottom: "batch_norm_blob131"
top: "batch_norm_blob131"
scale_param {
bias_term: true
}
}
layer {
name: "add63"
type: "Eltwise"
bottom: "batch_norm_blob131"
bottom: "relu_blob115"
top: "add_blob63"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu117"
type: "CPP"
bottom: "add_blob63"
top: "relu_blob117"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv132"
type: "Convolution"
bottom: "relu_blob117"
top: "conv_blob132"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm132"
type: "BatchNorm"
bottom: "conv_blob132"
top: "batch_norm_blob132"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale132"
type: "Scale"
bottom: "batch_norm_blob132"
top: "batch_norm_blob132"
scale_param {
bias_term: true
}
}
layer {
name: "relu118"
type: "CPP"
bottom: "batch_norm_blob132"
top: "relu_blob118"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv133"
type: "Convolution"
bottom: "relu_blob118"
top: "conv_blob133"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm133"
type: "BatchNorm"
bottom: "conv_blob133"
top: "batch_norm_blob133"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale133"
type: "Scale"
bottom: "batch_norm_blob133"
top: "batch_norm_blob133"
scale_param {
bias_term: true
}
}
layer {
name: "add64"
type: "Eltwise"
bottom: "batch_norm_blob133"
bottom: "relu_blob117"
top: "add_blob64"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu119"
type: "CPP"
bottom: "add_blob64"
top: "relu_blob119"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv134"
type: "Convolution"
bottom: "relu_blob119"
top: "conv_blob134"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm134"
type: "BatchNorm"
bottom: "conv_blob134"
top: "batch_norm_blob134"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale134"
type: "Scale"
bottom: "batch_norm_blob134"
top: "batch_norm_blob134"
scale_param {
bias_term: true
}
}
layer {
name: "relu120"
type: "CPP"
bottom: "batch_norm_blob134"
top: "relu_blob120"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv135"
type: "Convolution"
bottom: "relu_blob120"
top: "conv_blob135"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm135"
type: "BatchNorm"
bottom: "conv_blob135"
top: "batch_norm_blob135"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale135"
type: "Scale"
bottom: "batch_norm_blob135"
top: "batch_norm_blob135"
scale_param {
bias_term: true
}
}
layer {
name: "add65"
type: "Eltwise"
bottom: "batch_norm_blob135"
bottom: "relu_blob119"
top: "add_blob65"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu121"
type: "CPP"
bottom: "add_blob65"
top: "relu_blob121"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv136"
type: "Convolution"
bottom: "relu_blob121"
top: "conv_blob136"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm136"
type: "BatchNorm"
bottom: "conv_blob136"
top: "batch_norm_blob136"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale136"
type: "Scale"
bottom: "batch_norm_blob136"
top: "batch_norm_blob136"
scale_param {
bias_term: true
}
}
layer {
name: "relu122"
type: "CPP"
bottom: "batch_norm_blob136"
top: "relu_blob122"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv137"
type: "Convolution"
bottom: "relu_blob122"
top: "conv_blob137"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm137"
type: "BatchNorm"
bottom: "conv_blob137"
top: "batch_norm_blob137"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale137"
type: "Scale"
bottom: "batch_norm_blob137"
top: "batch_norm_blob137"
scale_param {
bias_term: true
}
}
layer {
name: "add66"
type: "Eltwise"
bottom: "batch_norm_blob137"
bottom: "relu_blob121"
top: "add_blob66"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu123"
type: "CPP"
bottom: "add_blob66"
top: "relu_blob123"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv138"
type: "Convolution"
bottom: "relu_blob123"
top: "conv_blob138"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm138"
type: "BatchNorm"
bottom: "conv_blob138"
top: "batch_norm_blob138"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale138"
type: "Scale"
bottom: "batch_norm_blob138"
top: "batch_norm_blob138"
scale_param {
bias_term: true
}
}
layer {
name: "relu124"
type: "CPP"
bottom: "batch_norm_blob138"
top: "relu_blob124"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv139"
type: "Convolution"
bottom: "relu_blob124"
top: "conv_blob139"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm139"
type: "BatchNorm"
bottom: "conv_blob139"
top: "batch_norm_blob139"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale139"
type: "Scale"
bottom: "batch_norm_blob139"
top: "batch_norm_blob139"
scale_param {
bias_term: true
}
}
layer {
name: "add67"
type: "Eltwise"
bottom: "batch_norm_blob139"
bottom: "relu_blob123"
top: "add_blob67"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu125"
type: "CPP"
bottom: "add_blob67"
top: "relu_blob125"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv140"
type: "Convolution"
bottom: "relu_blob125"
top: "conv_blob140"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm140"
type: "BatchNorm"
bottom: "conv_blob140"
top: "batch_norm_blob140"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale140"
type: "Scale"
bottom: "batch_norm_blob140"
top: "batch_norm_blob140"
scale_param {
bias_term: true
}
}
layer {
name: "relu126"
type: "CPP"
bottom: "batch_norm_blob140"
top: "relu_blob126"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv141"
type: "Convolution"
bottom: "relu_blob126"
top: "conv_blob141"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm141"
type: "BatchNorm"
bottom: "conv_blob141"
top: "batch_norm_blob141"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale141"
type: "Scale"
bottom: "batch_norm_blob141"
top: "batch_norm_blob141"
scale_param {
bias_term: true
}
}
layer {
name: "conv142"
type: "Convolution"
bottom: "relu_blob125"
top: "conv_blob142"
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm142"
type: "BatchNorm"
bottom: "conv_blob142"
top: "batch_norm_blob142"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale142"
type: "Scale"
bottom: "batch_norm_blob142"
top: "batch_norm_blob142"
scale_param {
bias_term: true
}
}
layer {
name: "add68"
type: "Eltwise"
bottom: "batch_norm_blob141"
bottom: "batch_norm_blob142"
top: "add_blob68"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu127"
type: "CPP"
bottom: "add_blob68"
top: "relu_blob127"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample6"
type: "CPP"
bottom: "relu_blob127"
top: "upsample_blob6"
cpp_param {
param_str: "scale:2; upsample_h: 8; upsample_w: 8"
type: "Upsample"
}
}
layer {
name: "add69"
type: "Eltwise"
bottom: "relu_blob111"
bottom: "upsample_blob6"
top: "add_blob69"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv143"
type: "Convolution"
bottom: "add_blob69"
top: "conv_blob143"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm143"
type: "BatchNorm"
bottom: "conv_blob143"
top: "batch_norm_blob143"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale143"
type: "Scale"
bottom: "batch_norm_blob143"
top: "batch_norm_blob143"
scale_param {
bias_term: true
}
}
layer {
name: "relu128"
type: "CPP"
bottom: "batch_norm_blob143"
top: "relu_blob128"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv144"
type: "Convolution"
bottom: "relu_blob128"
top: "conv_blob144"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm144"
type: "BatchNorm"
bottom: "conv_blob144"
top: "batch_norm_blob144"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale144"
type: "Scale"
bottom: "batch_norm_blob144"
top: "batch_norm_blob144"
scale_param {
bias_term: true
}
}
layer {
name: "add70"
type: "Eltwise"
bottom: "batch_norm_blob144"
bottom: "add_blob69"
top: "add_blob70"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu129"
type: "CPP"
bottom: "add_blob70"
top: "relu_blob129"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv145"
type: "Convolution"
bottom: "relu_blob129"
top: "conv_blob145"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm145"
type: "BatchNorm"
bottom: "conv_blob145"
top: "batch_norm_blob145"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale145"
type: "Scale"
bottom: "batch_norm_blob145"
top: "batch_norm_blob145"
scale_param {
bias_term: true
}
}
layer {
name: "relu130"
type: "CPP"
bottom: "batch_norm_blob145"
top: "relu_blob130"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv146"
type: "Convolution"
bottom: "relu_blob130"
top: "conv_blob146"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm146"
type: "BatchNorm"
bottom: "conv_blob146"
top: "batch_norm_blob146"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale146"
type: "Scale"
bottom: "batch_norm_blob146"
top: "batch_norm_blob146"
scale_param {
bias_term: true
}
}
layer {
name: "add71"
type: "Eltwise"
bottom: "batch_norm_blob146"
bottom: "relu_blob129"
top: "add_blob71"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu131"
type: "CPP"
bottom: "add_blob71"
top: "relu_blob131"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample7"
type: "CPP"
bottom: "relu_blob131"
top: "upsample_blob7"
cpp_param {
param_str: "scale:2; upsample_h: 16; upsample_w: 16"
type: "Upsample"
}
}
layer {
name: "add72"
type: "Eltwise"
bottom: "relu_blob103"
bottom: "upsample_blob7"
top: "add_blob72"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv147"
type: "Convolution"
bottom: "add_blob72"
top: "conv_blob147"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm147"
type: "BatchNorm"
bottom: "conv_blob147"
top: "batch_norm_blob147"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale147"
type: "Scale"
bottom: "batch_norm_blob147"
top: "batch_norm_blob147"
scale_param {
bias_term: true
}
}
layer {
name: "relu132"
type: "CPP"
bottom: "batch_norm_blob147"
top: "relu_blob132"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv148"
type: "Convolution"
bottom: "relu_blob132"
top: "conv_blob148"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm148"
type: "BatchNorm"
bottom: "conv_blob148"
top: "batch_norm_blob148"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale148"
type: "Scale"
bottom: "batch_norm_blob148"
top: "batch_norm_blob148"
scale_param {
bias_term: true
}
}
layer {
name: "add73"
type: "Eltwise"
bottom: "batch_norm_blob148"
bottom: "add_blob72"
top: "add_blob73"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu133"
type: "CPP"
bottom: "add_blob73"
top: "relu_blob133"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv149"
type: "Convolution"
bottom: "relu_blob133"
top: "conv_blob149"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm149"
type: "BatchNorm"
bottom: "conv_blob149"
top: "batch_norm_blob149"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale149"
type: "Scale"
bottom: "batch_norm_blob149"
top: "batch_norm_blob149"
scale_param {
bias_term: true
}
}
layer {
name: "relu134"
type: "CPP"
bottom: "batch_norm_blob149"
top: "relu_blob134"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv150"
type: "Convolution"
bottom: "relu_blob134"
top: "conv_blob150"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm150"
type: "BatchNorm"
bottom: "conv_blob150"
top: "batch_norm_blob150"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale150"
type: "Scale"
bottom: "batch_norm_blob150"
top: "batch_norm_blob150"
scale_param {
bias_term: true
}
}
layer {
name: "add74"
type: "Eltwise"
bottom: "batch_norm_blob150"
bottom: "relu_blob133"
top: "add_blob74"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu135"
type: "CPP"
bottom: "add_blob74"
top: "relu_blob135"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample8"
type: "CPP"
bottom: "relu_blob135"
top: "upsample_blob8"
cpp_param {
param_str: "scale:2; upsample_h: 32; upsample_w: 32"
type: "Upsample"
}
}
layer {
name: "add75"
type: "Eltwise"
bottom: "relu_blob95"
bottom: "upsample_blob8"
top: "add_blob75"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv151"
type: "Convolution"
bottom: "add_blob75"
top: "conv_blob151"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm151"
type: "BatchNorm"
bottom: "conv_blob151"
top: "batch_norm_blob151"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale151"
type: "Scale"
bottom: "batch_norm_blob151"
top: "batch_norm_blob151"
scale_param {
bias_term: true
}
}
layer {
name: "relu136"
type: "CPP"
bottom: "batch_norm_blob151"
top: "relu_blob136"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv152"
type: "Convolution"
bottom: "relu_blob136"
top: "conv_blob152"
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm152"
type: "BatchNorm"
bottom: "conv_blob152"
top: "batch_norm_blob152"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale152"
type: "Scale"
bottom: "batch_norm_blob152"
top: "batch_norm_blob152"
scale_param {
bias_term: true
}
}
layer {
name: "add76"
type: "Eltwise"
bottom: "batch_norm_blob152"
bottom: "add_blob75"
top: "add_blob76"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu137"
type: "CPP"
bottom: "add_blob76"
top: "relu_blob137"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv153"
type: "Convolution"
bottom: "relu_blob137"
top: "conv_blob153"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm153"
type: "BatchNorm"
bottom: "conv_blob153"
top: "batch_norm_blob153"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale153"
type: "Scale"
bottom: "batch_norm_blob153"
top: "batch_norm_blob153"
scale_param {
bias_term: true
}
}
layer {
name: "relu138"
type: "CPP"
bottom: "batch_norm_blob153"
top: "relu_blob138"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv154"
type: "Convolution"
bottom: "relu_blob138"
top: "conv_blob154"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm154"
type: "BatchNorm"
bottom: "conv_blob154"
top: "batch_norm_blob154"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale154"
type: "Scale"
bottom: "batch_norm_blob154"
top: "batch_norm_blob154"
scale_param {
bias_term: true
}
}
layer {
name: "conv155"
type: "Convolution"
bottom: "relu_blob137"
top: "conv_blob155"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm155"
type: "BatchNorm"
bottom: "conv_blob155"
top: "batch_norm_blob155"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale155"
type: "Scale"
bottom: "batch_norm_blob155"
top: "batch_norm_blob155"
scale_param {
bias_term: true
}
}
layer {
name: "add77"
type: "Eltwise"
bottom: "batch_norm_blob154"
bottom: "batch_norm_blob155"
top: "add_blob77"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu139"
type: "CPP"
bottom: "add_blob77"
top: "relu_blob139"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample9"
type: "CPP"
bottom: "relu_blob139"
top: "upsample_blob9"
cpp_param {
param_str: "scale:2; upsample_h: 64; upsample_w: 64"
type: "Upsample"
}
}
layer {
name: "add78"
type: "Eltwise"
bottom: "relu_blob87"
bottom: "upsample_blob9"
top: "add_blob78"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv156"
type: "Convolution"
bottom: "add_blob78"
top: "conv_blob156"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm156"
type: "BatchNorm"
bottom: "conv_blob156"
top: "batch_norm_blob156"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale156"
type: "Scale"
bottom: "batch_norm_blob156"
top: "batch_norm_blob156"
scale_param {
bias_term: true
}
}
layer {
name: "relu140"
type: "CPP"
bottom: "batch_norm_blob156"
top: "relu_blob140"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv157"
type: "Convolution"
bottom: "relu_blob140"
top: "conv_blob157"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm157"
type: "BatchNorm"
bottom: "conv_blob157"
top: "batch_norm_blob157"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale157"
type: "Scale"
bottom: "batch_norm_blob157"
top: "batch_norm_blob157"
scale_param {
bias_term: true
}
}
layer {
name: "add79"
type: "Eltwise"
bottom: "batch_norm_blob157"
bottom: "add_blob78"
top: "add_blob79"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu141"
type: "CPP"
bottom: "add_blob79"
top: "relu_blob141"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv158"
type: "Convolution"
bottom: "relu_blob141"
top: "conv_blob158"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm158"
type: "BatchNorm"
bottom: "conv_blob158"
top: "batch_norm_blob158"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale158"
type: "Scale"
bottom: "batch_norm_blob158"
top: "batch_norm_blob158"
scale_param {
bias_term: true
}
}
layer {
name: "relu142"
type: "CPP"
bottom: "batch_norm_blob158"
top: "relu_blob142"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv159"
type: "Convolution"
bottom: "relu_blob142"
top: "conv_blob159"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm159"
type: "BatchNorm"
bottom: "conv_blob159"
top: "batch_norm_blob159"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale159"
type: "Scale"
bottom: "batch_norm_blob159"
top: "batch_norm_blob159"
scale_param {
bias_term: true
}
}
layer {
name: "add80"
type: "Eltwise"
bottom: "batch_norm_blob159"
bottom: "relu_blob141"
top: "add_blob80"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu143"
type: "CPP"
bottom: "add_blob80"
top: "relu_blob143"
cpp_param {
type: "ReLU"
}
}
layer {
name: "upsample10"
type: "CPP"
bottom: "relu_blob143"
top: "upsample_blob10"
cpp_param {
param_str: "scale:2; upsample_h: 128; upsample_w: 128"
type: "Upsample"
}
}
layer {
name: "add81"
type: "Eltwise"
bottom: "relu_blob79"
bottom: "upsample_blob10"
top: "add_blob81"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv160"
type: "Convolution"
bottom: "add_blob81"
top: "conv_blob160"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm160"
type: "BatchNorm"
bottom: "conv_blob160"
top: "batch_norm_blob160"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale160"
type: "Scale"
bottom: "batch_norm_blob160"
top: "batch_norm_blob160"
scale_param {
bias_term: true
}
}
layer {
name: "relu144"
type: "CPP"
bottom: "batch_norm_blob160"
top: "relu_blob144"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv161"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob161"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm161"
type: "BatchNorm"
bottom: "conv_blob161"
top: "batch_norm_blob161"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale161"
type: "Scale"
bottom: "batch_norm_blob161"
top: "batch_norm_blob161"
scale_param {
bias_term: true
}
}
layer {
name: "relu145"
type: "CPP"
bottom: "batch_norm_blob161"
top: "relu_blob145"
cpp_param {
type: "ReLU"
}
}
layer {
name: "top_pool1"
type: "CPP"
bottom: "relu_blob145"
top: "top_pool_blob1"
cpp_param {
type: "TopCornerPoolLayer"
}
}
layer {
name: "conv162"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob162"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm162"
type: "BatchNorm"
bottom: "conv_blob162"
top: "batch_norm_blob162"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale162"
type: "Scale"
bottom: "batch_norm_blob162"
top: "batch_norm_blob162"
scale_param {
bias_term: true
}
}
layer {
name: "relu146"
type: "CPP"
bottom: "batch_norm_blob162"
top: "relu_blob146"
cpp_param {
type: "ReLU"
}
}
layer {
name: "left_pool1"
type: "CPP"
bottom: "relu_blob146"
top: "left_pool_blob1"
cpp_param {
type: "LeftCornerPoolLayer"
}
}
layer {
name: "add82"
type: "Eltwise"
bottom: "top_pool_blob1"
bottom: "left_pool_blob1"
top: "add_blob82"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv163"
type: "Convolution"
bottom: "add_blob82"
top: "conv_blob163"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm163"
type: "BatchNorm"
bottom: "conv_blob163"
top: "batch_norm_blob163"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale163"
type: "Scale"
bottom: "batch_norm_blob163"
top: "batch_norm_blob163"
scale_param {
bias_term: true
}
}
layer {
name: "conv164"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob164"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm164"
type: "BatchNorm"
bottom: "conv_blob164"
top: "batch_norm_blob164"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale164"
type: "Scale"
bottom: "batch_norm_blob164"
top: "batch_norm_blob164"
scale_param {
bias_term: true
}
}
layer {
name: "add83"
type: "Eltwise"
bottom: "batch_norm_blob163"
bottom: "batch_norm_blob164"
top: "add_blob83"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu147"
type: "CPP"
bottom: "add_blob83"
top: "relu_blob147"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv165"
type: "Convolution"
bottom: "relu_blob147"
top: "conv_blob165"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm165"
type: "BatchNorm"
bottom: "conv_blob165"
top: "batch_norm_blob165"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale165"
type: "Scale"
bottom: "batch_norm_blob165"
top: "batch_norm_blob165"
scale_param {
bias_term: true
}
}
layer {
name: "relu148"
type: "CPP"
bottom: "batch_norm_blob165"
top: "relu_blob148"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv166"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob166"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm166"
type: "BatchNorm"
bottom: "conv_blob166"
top: "batch_norm_blob166"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale166"
type: "Scale"
bottom: "batch_norm_blob166"
top: "batch_norm_blob166"
scale_param {
bias_term: true
}
}
layer {
name: "relu149"
type: "CPP"
bottom: "batch_norm_blob166"
top: "relu_blob149"
cpp_param {
type: "ReLU"
}
}
layer {
name: "bottom_pool1"
type: "CPP"
bottom: "relu_blob149"
top: "bottom_pool_blob1"
cpp_param {
type: "BottomCornerPoolLayer"
}
}
layer {
name: "conv167"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob167"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm167"
type: "BatchNorm"
bottom: "conv_blob167"
top: "batch_norm_blob167"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale167"
type: "Scale"
bottom: "batch_norm_blob167"
top: "batch_norm_blob167"
scale_param {
bias_term: true
}
}
layer {
name: "relu150"
type: "CPP"
bottom: "batch_norm_blob167"
top: "relu_blob150"
cpp_param {
type: "ReLU"
}
}
layer {
name: "right_pool1"
type: "CPP"
bottom: "relu_blob150"
top: "right_pool_blob1"
cpp_param {
type: "RightCornerPoolLayer"
}
}
layer {
name: "add84"
type: "Eltwise"
bottom: "bottom_pool_blob1"
bottom: "right_pool_blob1"
top: "add_blob84"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv168"
type: "Convolution"
bottom: "add_blob84"
top: "conv_blob168"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm168"
type: "BatchNorm"
bottom: "conv_blob168"
top: "batch_norm_blob168"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale168"
type: "Scale"
bottom: "batch_norm_blob168"
top: "batch_norm_blob168"
scale_param {
bias_term: true
}
}
layer {
name: "conv169"
type: "Convolution"
bottom: "relu_blob144"
top: "conv_blob169"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm169"
type: "BatchNorm"
bottom: "conv_blob169"
top: "batch_norm_blob169"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale169"
type: "Scale"
bottom: "batch_norm_blob169"
top: "batch_norm_blob169"
scale_param {
bias_term: true
}
}
layer {
name: "add85"
type: "Eltwise"
bottom: "batch_norm_blob168"
bottom: "batch_norm_blob169"
top: "add_blob85"
eltwise_param {
operation: SUM
}
}
layer {
name: "relu151"
type: "CPP"
bottom: "add_blob85"
top: "relu_blob151"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv170"
type: "Convolution"
bottom: "relu_blob151"
top: "conv_blob170"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
dilation: 1
}
}
layer {
name: "batch_norm170"
type: "BatchNorm"
bottom: "conv_blob170"
top: "batch_norm_blob170"
batch_norm_param {
eps: 9.999999747378752e-06
}
}
layer {
name: "bn_scale170"
type: "Scale"
bottom: "batch_norm_blob170"
top: "batch_norm_blob170"
scale_param {
bias_term: true
}
}
layer {
name: "relu152"
type: "CPP"
bottom: "batch_norm_blob170"
top: "relu_blob152"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv171"
type: "Convolution"
bottom: "relu_blob148"
top: "conv_blob171"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu153"
type: "CPP"
bottom: "conv_blob171"
top: "relu_blob153"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv172"
type: "Convolution"
bottom: "relu_blob153"
top: "conv_blob172"
convolution_param {
num_output: 80
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "conv173"
type: "Convolution"
bottom: "relu_blob152"
top: "conv_blob173"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu154"
type: "CPP"
bottom: "conv_blob173"
top: "relu_blob154"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv174"
type: "Convolution"
bottom: "relu_blob154"
top: "conv_blob174"
convolution_param {
num_output: 80
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "conv175"
type: "Convolution"
bottom: "relu_blob148"
top: "conv_blob175"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu155"
type: "CPP"
bottom: "conv_blob175"
top: "relu_blob155"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv176"
type: "Convolution"
bottom: "relu_blob155"
top: "conv_blob176"
convolution_param {
num_output: 1
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "conv177"
type: "Convolution"
bottom: "relu_blob152"
top: "conv_blob177"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu156"
type: "CPP"
bottom: "conv_blob177"
top: "relu_blob156"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv178"
type: "Convolution"
bottom: "relu_blob156"
top: "conv_blob178"
convolution_param {
num_output: 1
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "conv179"
type: "Convolution"
bottom: "relu_blob148"
top: "conv_blob179"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu157"
type: "CPP"
bottom: "conv_blob179"
top: "relu_blob157"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv180"
type: "Convolution"
bottom: "relu_blob157"
top: "conv_blob180"
convolution_param {
num_output: 2
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "conv181"
type: "Convolution"
bottom: "relu_blob152"
top: "conv_blob181"
convolution_param {
num_output: 256
bias_term: true
pad: 1
kernel_size: 3
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
layer {
name: "relu158"
type: "CPP"
bottom: "conv_blob181"
top: "relu_blob158"
cpp_param {
type: "ReLU"
}
}
layer {
name: "conv182"
type: "Convolution"
bottom: "relu_blob158"
top: "conv_blob182"
convolution_param {
num_output: 2
bias_term: true
pad: 0
kernel_size: 1
group: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
dilation: 1
}
}
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