Created
December 13, 2017 10:32
-
-
Save sriharsha0806/2819fc5fbd9de8f1a39773b72a6ca064 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 473 | |
input_dim: 473 | |
layer { | |
name: "conv1_1_3x3_s2" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1_1_3x3_s2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv1_1_3x3_s2/bn" | |
type: "BN" | |
bottom: "conv1_1_3x3_s2" | |
top: "conv1_1_3x3_s2" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv1_1_3x3_s2/relu" | |
type: "ReLU" | |
bottom: "conv1_1_3x3_s2" | |
top: "conv1_1_3x3_s2" | |
} | |
layer { | |
name: "conv1_2_3x3" | |
type: "Convolution" | |
bottom: "conv1_1_3x3_s2" | |
top: "conv1_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv1_2_3x3/bn" | |
type: "BN" | |
bottom: "conv1_2_3x3" | |
top: "conv1_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv1_2_3x3/relu" | |
type: "ReLU" | |
bottom: "conv1_2_3x3" | |
top: "conv1_2_3x3" | |
} | |
layer { | |
name: "conv1_3_3x3" | |
type: "Convolution" | |
bottom: "conv1_2_3x3" | |
top: "conv1_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv1_3_3x3/bn" | |
type: "BN" | |
bottom: "conv1_3_3x3" | |
top: "conv1_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv1_3_3x3/relu" | |
type: "ReLU" | |
bottom: "conv1_3_3x3" | |
top: "conv1_3_3x3" | |
} | |
layer { | |
name: "pool1_3x3_s2" | |
type: "Pooling" | |
bottom: "conv1_3_3x3" | |
top: "pool1_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_reduce" | |
type: "Convolution" | |
bottom: "pool1_3x3_s2" | |
top: "conv2_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv2_1_1x1_reduce" | |
top: "conv2_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv2_1_1x1_reduce" | |
top: "conv2_1_1x1_reduce" | |
} | |
layer { | |
name: "conv2_1_3x3" | |
type: "Convolution" | |
bottom: "conv2_1_1x1_reduce" | |
top: "conv2_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_1_3x3/bn" | |
type: "BN" | |
bottom: "conv2_1_3x3" | |
top: "conv2_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_1_3x3/relu" | |
type: "ReLU" | |
bottom: "conv2_1_3x3" | |
top: "conv2_1_3x3" | |
} | |
layer { | |
name: "conv2_1_1x1_increase" | |
type: "Convolution" | |
bottom: "conv2_1_3x3" | |
top: "conv2_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv2_1_1x1_increase" | |
top: "conv2_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_proj" | |
type: "Convolution" | |
bottom: "pool1_3x3_s2" | |
top: "conv2_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_1_1x1_proj/bn" | |
type: "BN" | |
bottom: "conv2_1_1x1_proj" | |
top: "conv2_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_1" | |
type: "Eltwise" | |
bottom: "conv2_1_1x1_proj" | |
bottom: "conv2_1_1x1_increase" | |
top: "conv2_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv2_1/relu" | |
type: "ReLU" | |
bottom: "conv2_1" | |
top: "conv2_1" | |
} | |
layer { | |
name: "conv2_2_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv2_1" | |
top: "conv2_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_2_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv2_2_1x1_reduce" | |
top: "conv2_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_2_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv2_2_1x1_reduce" | |
top: "conv2_2_1x1_reduce" | |
} | |
layer { | |
name: "conv2_2_3x3" | |
type: "Convolution" | |
bottom: "conv2_2_1x1_reduce" | |
top: "conv2_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_2_3x3/bn" | |
type: "BN" | |
bottom: "conv2_2_3x3" | |
top: "conv2_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_2_3x3/relu" | |
type: "ReLU" | |
bottom: "conv2_2_3x3" | |
top: "conv2_2_3x3" | |
} | |
layer { | |
name: "conv2_2_1x1_increase" | |
type: "Convolution" | |
bottom: "conv2_2_3x3" | |
top: "conv2_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_2_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv2_2_1x1_increase" | |
top: "conv2_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_2" | |
type: "Eltwise" | |
bottom: "conv2_1" | |
bottom: "conv2_2_1x1_increase" | |
top: "conv2_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv2_2/relu" | |
type: "ReLU" | |
bottom: "conv2_2" | |
top: "conv2_2" | |
} | |
layer { | |
name: "conv2_3_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv2_2" | |
top: "conv2_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_3_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv2_3_1x1_reduce" | |
top: "conv2_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_3_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv2_3_1x1_reduce" | |
top: "conv2_3_1x1_reduce" | |
} | |
layer { | |
name: "conv2_3_3x3" | |
type: "Convolution" | |
bottom: "conv2_3_1x1_reduce" | |
top: "conv2_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_3_3x3/bn" | |
type: "BN" | |
bottom: "conv2_3_3x3" | |
top: "conv2_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_3_3x3/relu" | |
type: "ReLU" | |
bottom: "conv2_3_3x3" | |
top: "conv2_3_3x3" | |
} | |
layer { | |
name: "conv2_3_1x1_increase" | |
type: "Convolution" | |
bottom: "conv2_3_3x3" | |
top: "conv2_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv2_3_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv2_3_1x1_increase" | |
top: "conv2_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv2_3" | |
type: "Eltwise" | |
bottom: "conv2_2" | |
bottom: "conv2_3_1x1_increase" | |
top: "conv2_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv2_3/relu" | |
type: "ReLU" | |
bottom: "conv2_3" | |
top: "conv2_3" | |
} | |
layer { | |
name: "conv3_1_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv2_3" | |
top: "conv3_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_1_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv3_1_1x1_reduce" | |
top: "conv3_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_1_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv3_1_1x1_reduce" | |
top: "conv3_1_1x1_reduce" | |
} | |
layer { | |
name: "conv3_1_3x3" | |
type: "Convolution" | |
bottom: "conv3_1_1x1_reduce" | |
top: "conv3_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_1_3x3/bn" | |
type: "BN" | |
bottom: "conv3_1_3x3" | |
top: "conv3_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_1_3x3/relu" | |
type: "ReLU" | |
bottom: "conv3_1_3x3" | |
top: "conv3_1_3x3" | |
} | |
layer { | |
name: "conv3_1_1x1_increase" | |
type: "Convolution" | |
bottom: "conv3_1_3x3" | |
top: "conv3_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_1_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv3_1_1x1_increase" | |
top: "conv3_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_1_1x1_proj" | |
type: "Convolution" | |
bottom: "conv2_3" | |
top: "conv3_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_1_1x1_proj/bn" | |
type: "BN" | |
bottom: "conv3_1_1x1_proj" | |
top: "conv3_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_1" | |
type: "Eltwise" | |
bottom: "conv3_1_1x1_proj" | |
bottom: "conv3_1_1x1_increase" | |
top: "conv3_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv3_1/relu" | |
type: "ReLU" | |
bottom: "conv3_1" | |
top: "conv3_1" | |
} | |
layer { | |
name: "conv3_2_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv3_1" | |
top: "conv3_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_2_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv3_2_1x1_reduce" | |
top: "conv3_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_2_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv3_2_1x1_reduce" | |
top: "conv3_2_1x1_reduce" | |
} | |
layer { | |
name: "conv3_2_3x3" | |
type: "Convolution" | |
bottom: "conv3_2_1x1_reduce" | |
top: "conv3_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_2_3x3/bn" | |
type: "BN" | |
bottom: "conv3_2_3x3" | |
top: "conv3_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_2_3x3/relu" | |
type: "ReLU" | |
bottom: "conv3_2_3x3" | |
top: "conv3_2_3x3" | |
} | |
layer { | |
name: "conv3_2_1x1_increase" | |
type: "Convolution" | |
bottom: "conv3_2_3x3" | |
top: "conv3_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_2_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv3_2_1x1_increase" | |
top: "conv3_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_2" | |
type: "Eltwise" | |
bottom: "conv3_1" | |
bottom: "conv3_2_1x1_increase" | |
top: "conv3_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv3_2/relu" | |
type: "ReLU" | |
bottom: "conv3_2" | |
top: "conv3_2" | |
} | |
layer { | |
name: "conv3_3_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv3_2" | |
top: "conv3_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_3_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv3_3_1x1_reduce" | |
top: "conv3_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_3_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv3_3_1x1_reduce" | |
top: "conv3_3_1x1_reduce" | |
} | |
layer { | |
name: "conv3_3_3x3" | |
type: "Convolution" | |
bottom: "conv3_3_1x1_reduce" | |
top: "conv3_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_3_3x3/bn" | |
type: "BN" | |
bottom: "conv3_3_3x3" | |
top: "conv3_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_3_3x3/relu" | |
type: "ReLU" | |
bottom: "conv3_3_3x3" | |
top: "conv3_3_3x3" | |
} | |
layer { | |
name: "conv3_3_1x1_increase" | |
type: "Convolution" | |
bottom: "conv3_3_3x3" | |
top: "conv3_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_3_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv3_3_1x1_increase" | |
top: "conv3_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_3" | |
type: "Eltwise" | |
bottom: "conv3_2" | |
bottom: "conv3_3_1x1_increase" | |
top: "conv3_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv3_3/relu" | |
type: "ReLU" | |
bottom: "conv3_3" | |
top: "conv3_3" | |
} | |
layer { | |
name: "conv3_4_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv3_3" | |
top: "conv3_4_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_4_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv3_4_1x1_reduce" | |
top: "conv3_4_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_4_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv3_4_1x1_reduce" | |
top: "conv3_4_1x1_reduce" | |
} | |
layer { | |
name: "conv3_4_3x3" | |
type: "Convolution" | |
bottom: "conv3_4_1x1_reduce" | |
top: "conv3_4_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_4_3x3/bn" | |
type: "BN" | |
bottom: "conv3_4_3x3" | |
top: "conv3_4_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_4_3x3/relu" | |
type: "ReLU" | |
bottom: "conv3_4_3x3" | |
top: "conv3_4_3x3" | |
} | |
layer { | |
name: "conv3_4_1x1_increase" | |
type: "Convolution" | |
bottom: "conv3_4_3x3" | |
top: "conv3_4_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv3_4_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv3_4_1x1_increase" | |
top: "conv3_4_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv3_4" | |
type: "Eltwise" | |
bottom: "conv3_3" | |
bottom: "conv3_4_1x1_increase" | |
top: "conv3_4" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv3_4/relu" | |
type: "ReLU" | |
bottom: "conv3_4" | |
top: "conv3_4" | |
} | |
layer { | |
name: "conv4_1_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv3_4" | |
top: "conv4_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_1_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_1_1x1_reduce" | |
top: "conv4_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_1_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_1_1x1_reduce" | |
top: "conv4_1_1x1_reduce" | |
} | |
layer { | |
name: "conv4_1_3x3" | |
type: "Convolution" | |
bottom: "conv4_1_1x1_reduce" | |
top: "conv4_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_1_3x3/bn" | |
type: "BN" | |
bottom: "conv4_1_3x3" | |
top: "conv4_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_1_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_1_3x3" | |
top: "conv4_1_3x3" | |
} | |
layer { | |
name: "conv4_1_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_1_3x3" | |
top: "conv4_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_1_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_1_1x1_increase" | |
top: "conv4_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_1_1x1_proj" | |
type: "Convolution" | |
bottom: "conv3_4" | |
top: "conv4_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_1_1x1_proj/bn" | |
type: "BN" | |
bottom: "conv4_1_1x1_proj" | |
top: "conv4_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_1" | |
type: "Eltwise" | |
bottom: "conv4_1_1x1_proj" | |
bottom: "conv4_1_1x1_increase" | |
top: "conv4_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_1/relu" | |
type: "ReLU" | |
bottom: "conv4_1" | |
top: "conv4_1" | |
} | |
layer { | |
name: "conv4_2_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_1" | |
top: "conv4_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_2_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_2_1x1_reduce" | |
top: "conv4_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_2_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_2_1x1_reduce" | |
top: "conv4_2_1x1_reduce" | |
} | |
layer { | |
name: "conv4_2_3x3" | |
type: "Convolution" | |
bottom: "conv4_2_1x1_reduce" | |
top: "conv4_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_2_3x3/bn" | |
type: "BN" | |
bottom: "conv4_2_3x3" | |
top: "conv4_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_2_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_2_3x3" | |
top: "conv4_2_3x3" | |
} | |
layer { | |
name: "conv4_2_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_2_3x3" | |
top: "conv4_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_2_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_2_1x1_increase" | |
top: "conv4_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_2" | |
type: "Eltwise" | |
bottom: "conv4_1" | |
bottom: "conv4_2_1x1_increase" | |
top: "conv4_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_2/relu" | |
type: "ReLU" | |
bottom: "conv4_2" | |
top: "conv4_2" | |
} | |
layer { | |
name: "conv4_3_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_2" | |
top: "conv4_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_3_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_3_1x1_reduce" | |
top: "conv4_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_3_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_3_1x1_reduce" | |
top: "conv4_3_1x1_reduce" | |
} | |
layer { | |
name: "conv4_3_3x3" | |
type: "Convolution" | |
bottom: "conv4_3_1x1_reduce" | |
top: "conv4_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_3_3x3/bn" | |
type: "BN" | |
bottom: "conv4_3_3x3" | |
top: "conv4_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_3_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_3_3x3" | |
top: "conv4_3_3x3" | |
} | |
layer { | |
name: "conv4_3_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_3_3x3" | |
top: "conv4_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_3_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_3_1x1_increase" | |
top: "conv4_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_3" | |
type: "Eltwise" | |
bottom: "conv4_2" | |
bottom: "conv4_3_1x1_increase" | |
top: "conv4_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_3/relu" | |
type: "ReLU" | |
bottom: "conv4_3" | |
top: "conv4_3" | |
} | |
layer { | |
name: "conv4_4_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_3" | |
top: "conv4_4_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_4_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_4_1x1_reduce" | |
top: "conv4_4_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_4_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_4_1x1_reduce" | |
top: "conv4_4_1x1_reduce" | |
} | |
layer { | |
name: "conv4_4_3x3" | |
type: "Convolution" | |
bottom: "conv4_4_1x1_reduce" | |
top: "conv4_4_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_4_3x3/bn" | |
type: "BN" | |
bottom: "conv4_4_3x3" | |
top: "conv4_4_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_4_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_4_3x3" | |
top: "conv4_4_3x3" | |
} | |
layer { | |
name: "conv4_4_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_4_3x3" | |
top: "conv4_4_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_4_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_4_1x1_increase" | |
top: "conv4_4_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_4" | |
type: "Eltwise" | |
bottom: "conv4_3" | |
bottom: "conv4_4_1x1_increase" | |
top: "conv4_4" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_4/relu" | |
type: "ReLU" | |
bottom: "conv4_4" | |
top: "conv4_4" | |
} | |
layer { | |
name: "conv4_5_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_4" | |
top: "conv4_5_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_5_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_5_1x1_reduce" | |
top: "conv4_5_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_5_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_5_1x1_reduce" | |
top: "conv4_5_1x1_reduce" | |
} | |
layer { | |
name: "conv4_5_3x3" | |
type: "Convolution" | |
bottom: "conv4_5_1x1_reduce" | |
top: "conv4_5_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_5_3x3/bn" | |
type: "BN" | |
bottom: "conv4_5_3x3" | |
top: "conv4_5_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_5_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_5_3x3" | |
top: "conv4_5_3x3" | |
} | |
layer { | |
name: "conv4_5_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_5_3x3" | |
top: "conv4_5_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_5_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_5_1x1_increase" | |
top: "conv4_5_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_5" | |
type: "Eltwise" | |
bottom: "conv4_4" | |
bottom: "conv4_5_1x1_increase" | |
top: "conv4_5" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_5/relu" | |
type: "ReLU" | |
bottom: "conv4_5" | |
top: "conv4_5" | |
} | |
layer { | |
name: "conv4_6_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_5" | |
top: "conv4_6_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_6_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_6_1x1_reduce" | |
top: "conv4_6_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_6_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_6_1x1_reduce" | |
top: "conv4_6_1x1_reduce" | |
} | |
layer { | |
name: "conv4_6_3x3" | |
type: "Convolution" | |
bottom: "conv4_6_1x1_reduce" | |
top: "conv4_6_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_6_3x3/bn" | |
type: "BN" | |
bottom: "conv4_6_3x3" | |
top: "conv4_6_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_6_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_6_3x3" | |
top: "conv4_6_3x3" | |
} | |
layer { | |
name: "conv4_6_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_6_3x3" | |
top: "conv4_6_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_6_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_6_1x1_increase" | |
top: "conv4_6_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_6" | |
type: "Eltwise" | |
bottom: "conv4_5" | |
bottom: "conv4_6_1x1_increase" | |
top: "conv4_6" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_6/relu" | |
type: "ReLU" | |
bottom: "conv4_6" | |
top: "conv4_6" | |
} | |
layer { | |
name: "conv4_7_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_6" | |
top: "conv4_7_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_7_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_7_1x1_reduce" | |
top: "conv4_7_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_7_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_7_1x1_reduce" | |
top: "conv4_7_1x1_reduce" | |
} | |
layer { | |
name: "conv4_7_3x3" | |
type: "Convolution" | |
bottom: "conv4_7_1x1_reduce" | |
top: "conv4_7_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_7_3x3/bn" | |
type: "BN" | |
bottom: "conv4_7_3x3" | |
top: "conv4_7_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_7_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_7_3x3" | |
top: "conv4_7_3x3" | |
} | |
layer { | |
name: "conv4_7_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_7_3x3" | |
top: "conv4_7_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_7_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_7_1x1_increase" | |
top: "conv4_7_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_7" | |
type: "Eltwise" | |
bottom: "conv4_6" | |
bottom: "conv4_7_1x1_increase" | |
top: "conv4_7" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_7/relu" | |
type: "ReLU" | |
bottom: "conv4_7" | |
top: "conv4_7" | |
} | |
layer { | |
name: "conv4_8_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_7" | |
top: "conv4_8_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_8_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_8_1x1_reduce" | |
top: "conv4_8_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_8_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_8_1x1_reduce" | |
top: "conv4_8_1x1_reduce" | |
} | |
layer { | |
name: "conv4_8_3x3" | |
type: "Convolution" | |
bottom: "conv4_8_1x1_reduce" | |
top: "conv4_8_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_8_3x3/bn" | |
type: "BN" | |
bottom: "conv4_8_3x3" | |
top: "conv4_8_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_8_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_8_3x3" | |
top: "conv4_8_3x3" | |
} | |
layer { | |
name: "conv4_8_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_8_3x3" | |
top: "conv4_8_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_8_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_8_1x1_increase" | |
top: "conv4_8_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_8" | |
type: "Eltwise" | |
bottom: "conv4_7" | |
bottom: "conv4_8_1x1_increase" | |
top: "conv4_8" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_8/relu" | |
type: "ReLU" | |
bottom: "conv4_8" | |
top: "conv4_8" | |
} | |
layer { | |
name: "conv4_9_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_8" | |
top: "conv4_9_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_9_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_9_1x1_reduce" | |
top: "conv4_9_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_9_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_9_1x1_reduce" | |
top: "conv4_9_1x1_reduce" | |
} | |
layer { | |
name: "conv4_9_3x3" | |
type: "Convolution" | |
bottom: "conv4_9_1x1_reduce" | |
top: "conv4_9_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_9_3x3/bn" | |
type: "BN" | |
bottom: "conv4_9_3x3" | |
top: "conv4_9_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_9_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_9_3x3" | |
top: "conv4_9_3x3" | |
} | |
layer { | |
name: "conv4_9_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_9_3x3" | |
top: "conv4_9_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_9_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_9_1x1_increase" | |
top: "conv4_9_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_9" | |
type: "Eltwise" | |
bottom: "conv4_8" | |
bottom: "conv4_9_1x1_increase" | |
top: "conv4_9" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_9/relu" | |
type: "ReLU" | |
bottom: "conv4_9" | |
top: "conv4_9" | |
} | |
layer { | |
name: "conv4_10_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_9" | |
top: "conv4_10_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_10_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_10_1x1_reduce" | |
top: "conv4_10_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_10_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_10_1x1_reduce" | |
top: "conv4_10_1x1_reduce" | |
} | |
layer { | |
name: "conv4_10_3x3" | |
type: "Convolution" | |
bottom: "conv4_10_1x1_reduce" | |
top: "conv4_10_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_10_3x3/bn" | |
type: "BN" | |
bottom: "conv4_10_3x3" | |
top: "conv4_10_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_10_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_10_3x3" | |
top: "conv4_10_3x3" | |
} | |
layer { | |
name: "conv4_10_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_10_3x3" | |
top: "conv4_10_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_10_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_10_1x1_increase" | |
top: "conv4_10_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_10" | |
type: "Eltwise" | |
bottom: "conv4_9" | |
bottom: "conv4_10_1x1_increase" | |
top: "conv4_10" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_10/relu" | |
type: "ReLU" | |
bottom: "conv4_10" | |
top: "conv4_10" | |
} | |
layer { | |
name: "conv4_11_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_10" | |
top: "conv4_11_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_11_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_11_1x1_reduce" | |
top: "conv4_11_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_11_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_11_1x1_reduce" | |
top: "conv4_11_1x1_reduce" | |
} | |
layer { | |
name: "conv4_11_3x3" | |
type: "Convolution" | |
bottom: "conv4_11_1x1_reduce" | |
top: "conv4_11_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_11_3x3/bn" | |
type: "BN" | |
bottom: "conv4_11_3x3" | |
top: "conv4_11_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_11_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_11_3x3" | |
top: "conv4_11_3x3" | |
} | |
layer { | |
name: "conv4_11_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_11_3x3" | |
top: "conv4_11_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_11_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_11_1x1_increase" | |
top: "conv4_11_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_11" | |
type: "Eltwise" | |
bottom: "conv4_10" | |
bottom: "conv4_11_1x1_increase" | |
top: "conv4_11" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_11/relu" | |
type: "ReLU" | |
bottom: "conv4_11" | |
top: "conv4_11" | |
} | |
layer { | |
name: "conv4_12_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_11" | |
top: "conv4_12_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_12_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_12_1x1_reduce" | |
top: "conv4_12_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_12_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_12_1x1_reduce" | |
top: "conv4_12_1x1_reduce" | |
} | |
layer { | |
name: "conv4_12_3x3" | |
type: "Convolution" | |
bottom: "conv4_12_1x1_reduce" | |
top: "conv4_12_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_12_3x3/bn" | |
type: "BN" | |
bottom: "conv4_12_3x3" | |
top: "conv4_12_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_12_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_12_3x3" | |
top: "conv4_12_3x3" | |
} | |
layer { | |
name: "conv4_12_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_12_3x3" | |
top: "conv4_12_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_12_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_12_1x1_increase" | |
top: "conv4_12_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_12" | |
type: "Eltwise" | |
bottom: "conv4_11" | |
bottom: "conv4_12_1x1_increase" | |
top: "conv4_12" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_12/relu" | |
type: "ReLU" | |
bottom: "conv4_12" | |
top: "conv4_12" | |
} | |
layer { | |
name: "conv4_13_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_12" | |
top: "conv4_13_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_13_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_13_1x1_reduce" | |
top: "conv4_13_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_13_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_13_1x1_reduce" | |
top: "conv4_13_1x1_reduce" | |
} | |
layer { | |
name: "conv4_13_3x3" | |
type: "Convolution" | |
bottom: "conv4_13_1x1_reduce" | |
top: "conv4_13_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_13_3x3/bn" | |
type: "BN" | |
bottom: "conv4_13_3x3" | |
top: "conv4_13_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_13_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_13_3x3" | |
top: "conv4_13_3x3" | |
} | |
layer { | |
name: "conv4_13_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_13_3x3" | |
top: "conv4_13_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_13_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_13_1x1_increase" | |
top: "conv4_13_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_13" | |
type: "Eltwise" | |
bottom: "conv4_12" | |
bottom: "conv4_13_1x1_increase" | |
top: "conv4_13" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_13/relu" | |
type: "ReLU" | |
bottom: "conv4_13" | |
top: "conv4_13" | |
} | |
layer { | |
name: "conv4_14_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_13" | |
top: "conv4_14_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_14_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_14_1x1_reduce" | |
top: "conv4_14_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_14_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_14_1x1_reduce" | |
top: "conv4_14_1x1_reduce" | |
} | |
layer { | |
name: "conv4_14_3x3" | |
type: "Convolution" | |
bottom: "conv4_14_1x1_reduce" | |
top: "conv4_14_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_14_3x3/bn" | |
type: "BN" | |
bottom: "conv4_14_3x3" | |
top: "conv4_14_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_14_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_14_3x3" | |
top: "conv4_14_3x3" | |
} | |
layer { | |
name: "conv4_14_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_14_3x3" | |
top: "conv4_14_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_14_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_14_1x1_increase" | |
top: "conv4_14_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_14" | |
type: "Eltwise" | |
bottom: "conv4_13" | |
bottom: "conv4_14_1x1_increase" | |
top: "conv4_14" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_14/relu" | |
type: "ReLU" | |
bottom: "conv4_14" | |
top: "conv4_14" | |
} | |
layer { | |
name: "conv4_15_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_14" | |
top: "conv4_15_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_15_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_15_1x1_reduce" | |
top: "conv4_15_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_15_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_15_1x1_reduce" | |
top: "conv4_15_1x1_reduce" | |
} | |
layer { | |
name: "conv4_15_3x3" | |
type: "Convolution" | |
bottom: "conv4_15_1x1_reduce" | |
top: "conv4_15_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_15_3x3/bn" | |
type: "BN" | |
bottom: "conv4_15_3x3" | |
top: "conv4_15_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_15_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_15_3x3" | |
top: "conv4_15_3x3" | |
} | |
layer { | |
name: "conv4_15_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_15_3x3" | |
top: "conv4_15_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_15_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_15_1x1_increase" | |
top: "conv4_15_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_15" | |
type: "Eltwise" | |
bottom: "conv4_14" | |
bottom: "conv4_15_1x1_increase" | |
top: "conv4_15" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_15/relu" | |
type: "ReLU" | |
bottom: "conv4_15" | |
top: "conv4_15" | |
} | |
layer { | |
name: "conv4_16_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_15" | |
top: "conv4_16_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_16_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_16_1x1_reduce" | |
top: "conv4_16_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_16_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_16_1x1_reduce" | |
top: "conv4_16_1x1_reduce" | |
} | |
layer { | |
name: "conv4_16_3x3" | |
type: "Convolution" | |
bottom: "conv4_16_1x1_reduce" | |
top: "conv4_16_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_16_3x3/bn" | |
type: "BN" | |
bottom: "conv4_16_3x3" | |
top: "conv4_16_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_16_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_16_3x3" | |
top: "conv4_16_3x3" | |
} | |
layer { | |
name: "conv4_16_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_16_3x3" | |
top: "conv4_16_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_16_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_16_1x1_increase" | |
top: "conv4_16_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_16" | |
type: "Eltwise" | |
bottom: "conv4_15" | |
bottom: "conv4_16_1x1_increase" | |
top: "conv4_16" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_16/relu" | |
type: "ReLU" | |
bottom: "conv4_16" | |
top: "conv4_16" | |
} | |
layer { | |
name: "conv4_17_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_16" | |
top: "conv4_17_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_17_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_17_1x1_reduce" | |
top: "conv4_17_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_17_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_17_1x1_reduce" | |
top: "conv4_17_1x1_reduce" | |
} | |
layer { | |
name: "conv4_17_3x3" | |
type: "Convolution" | |
bottom: "conv4_17_1x1_reduce" | |
top: "conv4_17_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_17_3x3/bn" | |
type: "BN" | |
bottom: "conv4_17_3x3" | |
top: "conv4_17_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_17_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_17_3x3" | |
top: "conv4_17_3x3" | |
} | |
layer { | |
name: "conv4_17_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_17_3x3" | |
top: "conv4_17_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_17_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_17_1x1_increase" | |
top: "conv4_17_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_17" | |
type: "Eltwise" | |
bottom: "conv4_16" | |
bottom: "conv4_17_1x1_increase" | |
top: "conv4_17" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_17/relu" | |
type: "ReLU" | |
bottom: "conv4_17" | |
top: "conv4_17" | |
} | |
layer { | |
name: "conv4_18_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_17" | |
top: "conv4_18_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_18_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_18_1x1_reduce" | |
top: "conv4_18_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_18_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_18_1x1_reduce" | |
top: "conv4_18_1x1_reduce" | |
} | |
layer { | |
name: "conv4_18_3x3" | |
type: "Convolution" | |
bottom: "conv4_18_1x1_reduce" | |
top: "conv4_18_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_18_3x3/bn" | |
type: "BN" | |
bottom: "conv4_18_3x3" | |
top: "conv4_18_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_18_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_18_3x3" | |
top: "conv4_18_3x3" | |
} | |
layer { | |
name: "conv4_18_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_18_3x3" | |
top: "conv4_18_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_18_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_18_1x1_increase" | |
top: "conv4_18_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_18" | |
type: "Eltwise" | |
bottom: "conv4_17" | |
bottom: "conv4_18_1x1_increase" | |
top: "conv4_18" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_18/relu" | |
type: "ReLU" | |
bottom: "conv4_18" | |
top: "conv4_18" | |
} | |
layer { | |
name: "conv4_19_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_18" | |
top: "conv4_19_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_19_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_19_1x1_reduce" | |
top: "conv4_19_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_19_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_19_1x1_reduce" | |
top: "conv4_19_1x1_reduce" | |
} | |
layer { | |
name: "conv4_19_3x3" | |
type: "Convolution" | |
bottom: "conv4_19_1x1_reduce" | |
top: "conv4_19_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_19_3x3/bn" | |
type: "BN" | |
bottom: "conv4_19_3x3" | |
top: "conv4_19_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_19_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_19_3x3" | |
top: "conv4_19_3x3" | |
} | |
layer { | |
name: "conv4_19_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_19_3x3" | |
top: "conv4_19_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_19_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_19_1x1_increase" | |
top: "conv4_19_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_19" | |
type: "Eltwise" | |
bottom: "conv4_18" | |
bottom: "conv4_19_1x1_increase" | |
top: "conv4_19" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_19/relu" | |
type: "ReLU" | |
bottom: "conv4_19" | |
top: "conv4_19" | |
} | |
layer { | |
name: "conv4_20_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_19" | |
top: "conv4_20_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_20_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_20_1x1_reduce" | |
top: "conv4_20_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_20_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_20_1x1_reduce" | |
top: "conv4_20_1x1_reduce" | |
} | |
layer { | |
name: "conv4_20_3x3" | |
type: "Convolution" | |
bottom: "conv4_20_1x1_reduce" | |
top: "conv4_20_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_20_3x3/bn" | |
type: "BN" | |
bottom: "conv4_20_3x3" | |
top: "conv4_20_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_20_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_20_3x3" | |
top: "conv4_20_3x3" | |
} | |
layer { | |
name: "conv4_20_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_20_3x3" | |
top: "conv4_20_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_20_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_20_1x1_increase" | |
top: "conv4_20_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_20" | |
type: "Eltwise" | |
bottom: "conv4_19" | |
bottom: "conv4_20_1x1_increase" | |
top: "conv4_20" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_20/relu" | |
type: "ReLU" | |
bottom: "conv4_20" | |
top: "conv4_20" | |
} | |
layer { | |
name: "conv4_21_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_20" | |
top: "conv4_21_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_21_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_21_1x1_reduce" | |
top: "conv4_21_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_21_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_21_1x1_reduce" | |
top: "conv4_21_1x1_reduce" | |
} | |
layer { | |
name: "conv4_21_3x3" | |
type: "Convolution" | |
bottom: "conv4_21_1x1_reduce" | |
top: "conv4_21_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_21_3x3/bn" | |
type: "BN" | |
bottom: "conv4_21_3x3" | |
top: "conv4_21_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_21_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_21_3x3" | |
top: "conv4_21_3x3" | |
} | |
layer { | |
name: "conv4_21_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_21_3x3" | |
top: "conv4_21_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_21_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_21_1x1_increase" | |
top: "conv4_21_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_21" | |
type: "Eltwise" | |
bottom: "conv4_20" | |
bottom: "conv4_21_1x1_increase" | |
top: "conv4_21" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_21/relu" | |
type: "ReLU" | |
bottom: "conv4_21" | |
top: "conv4_21" | |
} | |
layer { | |
name: "conv4_22_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_21" | |
top: "conv4_22_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_22_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_22_1x1_reduce" | |
top: "conv4_22_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_22_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_22_1x1_reduce" | |
top: "conv4_22_1x1_reduce" | |
} | |
layer { | |
name: "conv4_22_3x3" | |
type: "Convolution" | |
bottom: "conv4_22_1x1_reduce" | |
top: "conv4_22_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_22_3x3/bn" | |
type: "BN" | |
bottom: "conv4_22_3x3" | |
top: "conv4_22_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_22_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_22_3x3" | |
top: "conv4_22_3x3" | |
} | |
layer { | |
name: "conv4_22_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_22_3x3" | |
top: "conv4_22_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_22_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_22_1x1_increase" | |
top: "conv4_22_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_22" | |
type: "Eltwise" | |
bottom: "conv4_21" | |
bottom: "conv4_22_1x1_increase" | |
top: "conv4_22" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_22/relu" | |
type: "ReLU" | |
bottom: "conv4_22" | |
top: "conv4_22" | |
} | |
layer { | |
name: "conv4_23_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_22" | |
top: "conv4_23_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_23_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv4_23_1x1_reduce" | |
top: "conv4_23_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_23_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv4_23_1x1_reduce" | |
top: "conv4_23_1x1_reduce" | |
} | |
layer { | |
name: "conv4_23_3x3" | |
type: "Convolution" | |
bottom: "conv4_23_1x1_reduce" | |
top: "conv4_23_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 2 | |
dilation: 2 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_23_3x3/bn" | |
type: "BN" | |
bottom: "conv4_23_3x3" | |
top: "conv4_23_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_23_3x3/relu" | |
type: "ReLU" | |
bottom: "conv4_23_3x3" | |
top: "conv4_23_3x3" | |
} | |
layer { | |
name: "conv4_23_1x1_increase" | |
type: "Convolution" | |
bottom: "conv4_23_3x3" | |
top: "conv4_23_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv4_23_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv4_23_1x1_increase" | |
top: "conv4_23_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv4_23" | |
type: "Eltwise" | |
bottom: "conv4_22" | |
bottom: "conv4_23_1x1_increase" | |
top: "conv4_23" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv4_23/relu" | |
type: "ReLU" | |
bottom: "conv4_23" | |
top: "conv4_23" | |
} | |
layer { | |
name: "conv5_1_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv4_23" | |
top: "conv5_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_1_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv5_1_1x1_reduce" | |
top: "conv5_1_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_1_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv5_1_1x1_reduce" | |
top: "conv5_1_1x1_reduce" | |
} | |
layer { | |
name: "conv5_1_3x3" | |
type: "Convolution" | |
bottom: "conv5_1_1x1_reduce" | |
top: "conv5_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 4 | |
dilation: 4 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_1_3x3/bn" | |
type: "BN" | |
bottom: "conv5_1_3x3" | |
top: "conv5_1_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_1_3x3/relu" | |
type: "ReLU" | |
bottom: "conv5_1_3x3" | |
top: "conv5_1_3x3" | |
} | |
layer { | |
name: "conv5_1_1x1_increase" | |
type: "Convolution" | |
bottom: "conv5_1_3x3" | |
top: "conv5_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_1_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv5_1_1x1_increase" | |
top: "conv5_1_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_1_1x1_proj" | |
type: "Convolution" | |
bottom: "conv4_23" | |
top: "conv5_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_1_1x1_proj/bn" | |
type: "BN" | |
bottom: "conv5_1_1x1_proj" | |
top: "conv5_1_1x1_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_1" | |
type: "Eltwise" | |
bottom: "conv5_1_1x1_proj" | |
bottom: "conv5_1_1x1_increase" | |
top: "conv5_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv5_1/relu" | |
type: "ReLU" | |
bottom: "conv5_1" | |
top: "conv5_1" | |
} | |
layer { | |
name: "conv5_2_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv5_1" | |
top: "conv5_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_2_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv5_2_1x1_reduce" | |
top: "conv5_2_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_2_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv5_2_1x1_reduce" | |
top: "conv5_2_1x1_reduce" | |
} | |
layer { | |
name: "conv5_2_3x3" | |
type: "Convolution" | |
bottom: "conv5_2_1x1_reduce" | |
top: "conv5_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 4 | |
dilation: 4 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_2_3x3/bn" | |
type: "BN" | |
bottom: "conv5_2_3x3" | |
top: "conv5_2_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_2_3x3/relu" | |
type: "ReLU" | |
bottom: "conv5_2_3x3" | |
top: "conv5_2_3x3" | |
} | |
layer { | |
name: "conv5_2_1x1_increase" | |
type: "Convolution" | |
bottom: "conv5_2_3x3" | |
top: "conv5_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_2_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv5_2_1x1_increase" | |
top: "conv5_2_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_2" | |
type: "Eltwise" | |
bottom: "conv5_1" | |
bottom: "conv5_2_1x1_increase" | |
top: "conv5_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv5_2/relu" | |
type: "ReLU" | |
bottom: "conv5_2" | |
top: "conv5_2" | |
} | |
layer { | |
name: "conv5_3_1x1_reduce" | |
type: "Convolution" | |
bottom: "conv5_2" | |
top: "conv5_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_1x1_reduce/bn" | |
type: "BN" | |
bottom: "conv5_3_1x1_reduce" | |
top: "conv5_3_1x1_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_1x1_reduce/relu" | |
type: "ReLU" | |
bottom: "conv5_3_1x1_reduce" | |
top: "conv5_3_1x1_reduce" | |
} | |
layer { | |
name: "conv5_3_3x3" | |
type: "Convolution" | |
bottom: "conv5_3_1x1_reduce" | |
top: "conv5_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 4 | |
dilation: 4 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_3x3/bn" | |
type: "BN" | |
bottom: "conv5_3_3x3" | |
top: "conv5_3_3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_3x3/relu" | |
type: "ReLU" | |
bottom: "conv5_3_3x3" | |
top: "conv5_3_3x3" | |
} | |
layer { | |
name: "conv5_3_1x1_increase" | |
type: "Convolution" | |
bottom: "conv5_3_3x3" | |
top: "conv5_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_1x1_increase/bn" | |
type: "BN" | |
bottom: "conv5_3_1x1_increase" | |
top: "conv5_3_1x1_increase" | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 1 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3" | |
type: "Eltwise" | |
bottom: "conv5_2" | |
bottom: "conv5_3_1x1_increase" | |
top: "conv5_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer { | |
name: "conv5_3/relu" | |
type: "ReLU" | |
bottom: "conv5_3" | |
top: "conv5_3" | |
} | |
layer { | |
name: "conv5_3_pool1" | |
type: "Pooling" | |
bottom: "conv5_3" | |
top: "conv5_3_pool1" | |
pooling_param { | |
pool: AVE | |
kernel_size: 60 | |
stride: 60 | |
} | |
} | |
layer { | |
name: "conv5_3_pool1_conv" | |
type: "Convolution" | |
bottom: "conv5_3_pool1" | |
top: "conv5_3_pool1_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_pool1_conv/bn" | |
type: "BN" | |
bottom: "conv5_3_pool1_conv" | |
top: "conv5_3_pool1_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_pool1_conv/relu" | |
type: "ReLU" | |
bottom: "conv5_3_pool1_conv" | |
top: "conv5_3_pool1_conv" | |
} | |
layer { | |
name: "conv5_3_pool1_interp" | |
type: "Interp" | |
bottom: "conv5_3_pool1_conv" | |
top: "conv5_3_pool1_interp" | |
interp_param { | |
height: 60 | |
width: 60 | |
} | |
} | |
layer { | |
name: "conv5_3_pool2" | |
type: "Pooling" | |
bottom: "conv5_3" | |
top: "conv5_3_pool2" | |
pooling_param { | |
pool: AVE | |
kernel_size: 30 | |
stride: 30 | |
} | |
} | |
layer { | |
name: "conv5_3_pool2_conv" | |
type: "Convolution" | |
bottom: "conv5_3_pool2" | |
top: "conv5_3_pool2_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_pool2_conv/bn" | |
type: "BN" | |
bottom: "conv5_3_pool2_conv" | |
top: "conv5_3_pool2_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_pool2_conv/relu" | |
type: "ReLU" | |
bottom: "conv5_3_pool2_conv" | |
top: "conv5_3_pool2_conv" | |
} | |
layer { | |
name: "conv5_3_pool2_interp" | |
type: "Interp" | |
bottom: "conv5_3_pool2_conv" | |
top: "conv5_3_pool2_interp" | |
interp_param { | |
height: 60 | |
width: 60 | |
} | |
} | |
layer { | |
name: "conv5_3_pool3" | |
type: "Pooling" | |
bottom: "conv5_3" | |
top: "conv5_3_pool3" | |
pooling_param { | |
pool: AVE | |
kernel_size: 20 | |
stride: 20 | |
} | |
} | |
layer { | |
name: "conv5_3_pool3_conv" | |
type: "Convolution" | |
bottom: "conv5_3_pool3" | |
top: "conv5_3_pool3_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_pool3_conv/bn" | |
type: "BN" | |
bottom: "conv5_3_pool3_conv" | |
top: "conv5_3_pool3_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_pool3_conv/relu" | |
type: "ReLU" | |
bottom: "conv5_3_pool3_conv" | |
top: "conv5_3_pool3_conv" | |
} | |
layer { | |
name: "conv5_3_pool3_interp" | |
type: "Interp" | |
bottom: "conv5_3_pool3_conv" | |
top: "conv5_3_pool3_interp" | |
interp_param { | |
height: 60 | |
width: 60 | |
} | |
} | |
layer { | |
name: "conv5_3_pool6" | |
type: "Pooling" | |
bottom: "conv5_3" | |
top: "conv5_3_pool6" | |
pooling_param { | |
pool: AVE | |
kernel_size: 10 | |
stride: 10 | |
} | |
} | |
layer { | |
name: "conv5_3_pool6_conv" | |
type: "Convolution" | |
bottom: "conv5_3_pool6" | |
top: "conv5_3_pool6_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_3_pool6_conv/bn" | |
type: "BN" | |
bottom: "conv5_3_pool6_conv" | |
top: "conv5_3_pool6_conv" | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_3_pool6_conv/relu" | |
type: "ReLU" | |
bottom: "conv5_3_pool6_conv" | |
top: "conv5_3_pool6_conv" | |
} | |
layer { | |
name: "conv5_3_pool6_interp" | |
type: "Interp" | |
bottom: "conv5_3_pool6_conv" | |
top: "conv5_3_pool6_interp" | |
interp_param { | |
height: 60 | |
width: 60 | |
} | |
} | |
layer { | |
name: "conv5_3_concat" | |
type: "Concat" | |
bottom: "conv5_3" | |
bottom: "conv5_3_pool6_interp" | |
bottom: "conv5_3_pool3_interp" | |
bottom: "conv5_3_pool2_interp" | |
bottom: "conv5_3_pool1_interp" | |
top: "conv5_3_concat" | |
} | |
layer { | |
name: "conv5_4" | |
type: "Convolution" | |
bottom: "conv5_3_concat" | |
top: "conv5_4" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv5_4/bn" | |
type: "BN" | |
bottom: "conv5_4" | |
top: "conv5_4" | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 10 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
bn_param { | |
slope_filler { | |
type: "constant" | |
value: 1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
frozen: true | |
momentum: 0.95 | |
} | |
} | |
layer { | |
name: "conv5_4/relu" | |
type: "ReLU" | |
bottom: "conv5_4" | |
top: "conv5_4" | |
} | |
layer { | |
name: "conv5_4/dropout" | |
type: "Dropout" | |
bottom: "conv5_4" | |
top: "conv5_4" | |
dropout_param { | |
dropout_ratio: 0.1 | |
} | |
} | |
layer { | |
name: "conv6" | |
type: "Convolution" | |
bottom: "conv5_4" | |
top: "conv6" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 20 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 21 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv6_interp" | |
type: "Interp" | |
bottom: "conv6" | |
top: "conv6_interp" | |
interp_param { | |
zoom_factor: 8 | |
} | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment