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Resnet56Cifar.prototxt
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Resnet56Cifar.prototxt
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name: "Cifar-Resnet"
layer { # TRAIN data layer
name: "dataLayer"
type: "Data"
top: "data_top"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 32
mean_file: "examples/cifar10/mean.binaryproto"
}
data_param {
source: "examples/cifar10/cifar10_train_lmdb"
batch_size: 125
backend: LMDB
}
image_data_param {
shuffle: true
}
}
layer { # TEST data layer
name: "dataLayer"
type: "Data"
top: "data_top"
top: "label"
include {
phase: TEST
}
transform_param {
crop_size: 32
mean_file: "examples/cifar10/mean.binaryproto"
}
data_param {
source: "examples/cifar10/cifar10_test_lmdb"
batch_size: 125
backend: LMDB
}
}
layer { # pre_conv
name: "pre_conv"
type: "Convolution"
bottom: "data_top"
top: "pre_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # pre_bn
name: "pre_bn"
type: "BatchNorm"
bottom: "pre_conv_top"
top: "pre_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # pre_bn
name: "pre_bn"
type: "BatchNorm"
bottom: "pre_conv_top"
top: "pre_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # pre_scale
name: "pre_scale"
type: "Scale"
bottom: "pre_bn_top"
top: "pre_bn_top"
scale_param {
bias_term: true
}
}
layer { # pre_relu
name: "pre_relu"
type: "ReLU"
bottom: "pre_bn_top"
top: "pre_bn_top"
}
#{ L1 start
#{ L1_b1 start
#{ L1_b1_cbr1 start
layer { # L1_b1_cbr1_conv
name: "L1_b1_cbr1_conv"
type: "Convolution"
bottom: "pre_bn_top"
top: "L1_b1_cbr1_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b1_cbr1_bn
name: "L1_b1_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b1_cbr1_conv_top"
top: "L1_b1_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b1_cbr1_bn
name: "L1_b1_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b1_cbr1_conv_top"
top: "L1_b1_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b1_cbr1_scale
name: "L1_b1_cbr1_scale"
type: "Scale"
bottom: "L1_b1_cbr1_bn_top"
top: "L1_b1_cbr1_bn_top"
scale_param {
bias_term: true
}
}
layer { # L1_b1_cbr1_relu
name: "L1_b1_cbr1_relu"
type: "ReLU"
bottom: "L1_b1_cbr1_bn_top"
top: "L1_b1_cbr1_bn_top"
}
#} L1_b1_cbr1 end
#{ L1_b1_cbr2 start
layer { # L1_b1_cbr2_conv
name: "L1_b1_cbr2_conv"
type: "Convolution"
bottom: "L1_b1_cbr1_bn_top"
top: "L1_b1_cbr2_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b1_cbr2_bn
name: "L1_b1_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b1_cbr2_conv_top"
top: "L1_b1_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b1_cbr2_bn
name: "L1_b1_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b1_cbr2_conv_top"
top: "L1_b1_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b1_cbr2_scale
name: "L1_b1_cbr2_scale"
type: "Scale"
bottom: "L1_b1_cbr2_bn_top"
top: "L1_b1_cbr2_bn_top"
scale_param {
bias_term: true
}
}
#} L1_b1_cbr2 end
layer { # L1_b1_sum_eltwise
name: "L1_b1_sum_eltwise"
type: "Eltwise"
bottom: "L1_b1_cbr2_bn_top"
bottom: "pre_bn_top"
top: "L1_b1_sum_eltwise_top"
eltwise_param {
operation: SUM
}
}
layer { # L1_b1_relu
name: "L1_b1_relu"
type: "ReLU"
bottom: "L1_b1_sum_eltwise_top"
top: "L1_b1_sum_eltwise_top"
}
#} L1_b1 end
#{ L1_b2 start
#{ L1_b2_cbr1 start
layer { # L1_b2_cbr1_conv
name: "L1_b2_cbr1_conv"
type: "Convolution"
bottom: "L1_b1_sum_eltwise_top"
top: "L1_b2_cbr1_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b2_cbr1_bn
name: "L1_b2_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b2_cbr1_conv_top"
top: "L1_b2_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b2_cbr1_bn
name: "L1_b2_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b2_cbr1_conv_top"
top: "L1_b2_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b2_cbr1_scale
name: "L1_b2_cbr1_scale"
type: "Scale"
bottom: "L1_b2_cbr1_bn_top"
top: "L1_b2_cbr1_bn_top"
scale_param {
bias_term: true
}
}
layer { # L1_b2_cbr1_relu
name: "L1_b2_cbr1_relu"
type: "ReLU"
bottom: "L1_b2_cbr1_bn_top"
top: "L1_b2_cbr1_bn_top"
}
#} L1_b2_cbr1 end
#{ L1_b2_cbr2 start
layer { # L1_b2_cbr2_conv
name: "L1_b2_cbr2_conv"
type: "Convolution"
bottom: "L1_b2_cbr1_bn_top"
top: "L1_b2_cbr2_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b2_cbr2_bn
name: "L1_b2_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b2_cbr2_conv_top"
top: "L1_b2_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b2_cbr2_bn
name: "L1_b2_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b2_cbr2_conv_top"
top: "L1_b2_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b2_cbr2_scale
name: "L1_b2_cbr2_scale"
type: "Scale"
bottom: "L1_b2_cbr2_bn_top"
top: "L1_b2_cbr2_bn_top"
scale_param {
bias_term: true
}
}
#} L1_b2_cbr2 end
layer { # L1_b2_sum_eltwise
name: "L1_b2_sum_eltwise"
type: "Eltwise"
bottom: "L1_b2_cbr2_bn_top"
bottom: "L1_b1_sum_eltwise_top"
top: "L1_b2_sum_eltwise_top"
eltwise_param {
operation: SUM
}
}
layer { # L1_b2_relu
name: "L1_b2_relu"
type: "ReLU"
bottom: "L1_b2_sum_eltwise_top"
top: "L1_b2_sum_eltwise_top"
}
#} L1_b2 end
#{ L1_b3 start
#{ L1_b3_cbr1 start
layer { # L1_b3_cbr1_conv
name: "L1_b3_cbr1_conv"
type: "Convolution"
bottom: "L1_b2_sum_eltwise_top"
top: "L1_b3_cbr1_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b3_cbr1_bn
name: "L1_b3_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b3_cbr1_conv_top"
top: "L1_b3_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b3_cbr1_bn
name: "L1_b3_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b3_cbr1_conv_top"
top: "L1_b3_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b3_cbr1_scale
name: "L1_b3_cbr1_scale"
type: "Scale"
bottom: "L1_b3_cbr1_bn_top"
top: "L1_b3_cbr1_bn_top"
scale_param {
bias_term: true
}
}
layer { # L1_b3_cbr1_relu
name: "L1_b3_cbr1_relu"
type: "ReLU"
bottom: "L1_b3_cbr1_bn_top"
top: "L1_b3_cbr1_bn_top"
}
#} L1_b3_cbr1 end
#{ L1_b3_cbr2 start
layer { # L1_b3_cbr2_conv
name: "L1_b3_cbr2_conv"
type: "Convolution"
bottom: "L1_b3_cbr1_bn_top"
top: "L1_b3_cbr2_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b3_cbr2_bn
name: "L1_b3_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b3_cbr2_conv_top"
top: "L1_b3_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b3_cbr2_bn
name: "L1_b3_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b3_cbr2_conv_top"
top: "L1_b3_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b3_cbr2_scale
name: "L1_b3_cbr2_scale"
type: "Scale"
bottom: "L1_b3_cbr2_bn_top"
top: "L1_b3_cbr2_bn_top"
scale_param {
bias_term: true
}
}
#} L1_b3_cbr2 end
layer { # L1_b3_sum_eltwise
name: "L1_b3_sum_eltwise"
type: "Eltwise"
bottom: "L1_b3_cbr2_bn_top"
bottom: "L1_b2_sum_eltwise_top"
top: "L1_b3_sum_eltwise_top"
eltwise_param {
operation: SUM
}
}
layer { # L1_b3_relu
name: "L1_b3_relu"
type: "ReLU"
bottom: "L1_b3_sum_eltwise_top"
top: "L1_b3_sum_eltwise_top"
}
#} L1_b3 end
#{ L1_b4 start
#{ L1_b4_cbr1 start
layer { # L1_b4_cbr1_conv
name: "L1_b4_cbr1_conv"
type: "Convolution"
bottom: "L1_b3_sum_eltwise_top"
top: "L1_b4_cbr1_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b4_cbr1_bn
name: "L1_b4_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b4_cbr1_conv_top"
top: "L1_b4_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b4_cbr1_bn
name: "L1_b4_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b4_cbr1_conv_top"
top: "L1_b4_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b4_cbr1_scale
name: "L1_b4_cbr1_scale"
type: "Scale"
bottom: "L1_b4_cbr1_bn_top"
top: "L1_b4_cbr1_bn_top"
scale_param {
bias_term: true
}
}
layer { # L1_b4_cbr1_relu
name: "L1_b4_cbr1_relu"
type: "ReLU"
bottom: "L1_b4_cbr1_bn_top"
top: "L1_b4_cbr1_bn_top"
}
#} L1_b4_cbr1 end
#{ L1_b4_cbr2 start
layer { # L1_b4_cbr2_conv
name: "L1_b4_cbr2_conv"
type: "Convolution"
bottom: "L1_b4_cbr1_bn_top"
top: "L1_b4_cbr2_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b4_cbr2_bn
name: "L1_b4_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b4_cbr2_conv_top"
top: "L1_b4_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b4_cbr2_bn
name: "L1_b4_cbr2_bn"
type: "BatchNorm"
bottom: "L1_b4_cbr2_conv_top"
top: "L1_b4_cbr2_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
moving_average_fraction: 0.999
}
}
layer { # L1_b4_cbr2_scale
name: "L1_b4_cbr2_scale"
type: "Scale"
bottom: "L1_b4_cbr2_bn_top"
top: "L1_b4_cbr2_bn_top"
scale_param {
bias_term: true
}
}
#} L1_b4_cbr2 end
layer { # L1_b4_sum_eltwise
name: "L1_b4_sum_eltwise"
type: "Eltwise"
bottom: "L1_b4_cbr2_bn_top"
bottom: "L1_b3_sum_eltwise_top"
top: "L1_b4_sum_eltwise_top"
eltwise_param {
operation: SUM
}
}
layer { # L1_b4_relu
name: "L1_b4_relu"
type: "ReLU"
bottom: "L1_b4_sum_eltwise_top"
top: "L1_b4_sum_eltwise_top"
}
#} L1_b4 end
#{ L1_b5 start
#{ L1_b5_cbr1 start
layer { # L1_b5_cbr1_conv
name: "L1_b5_cbr1_conv"
type: "Convolution"
bottom: "L1_b4_sum_eltwise_top"
top: "L1_b5_cbr1_conv_top"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer { # L1_b5_cbr1_bn
name: "L1_b5_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b5_cbr1_conv_top"
top: "L1_b5_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
batch_norm_param {
use_global_stats: false
moving_average_fraction: 0.999
}
}
layer { # L1_b5_cbr1_bn
name: "L1_b5_cbr1_bn"
type: "BatchNorm"
bottom: "L1_b5_cbr1_conv_top"
top: "L1_b5_cbr1_bn_top"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true