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CaffeNet model
name: "AlexNet"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
# transform_param {
# mirror: true
# crop_size: 227
# mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
# }
# mean pixel / channel-wise mean instead of mean image
transform_param {
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
mirror: true
}
data_param {
source: "/data4/plankton_wi17/mpl/source_domain/spcombo/combo_finetune/allv1b-noise100/allv1b-noise100_100-100/code/train.LMDB"
batch_size: 256
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
# transform_param {
# mirror: false
# crop_size: 227
# mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
# }
# mean pixel / channel-wise mean instead of mean image
transform_param {
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
mirror: true
}
data_param {
source: "/data4/plankton_wi17/mpl/source_domain/spcombo/combo_finetune/allv1b-noise100/allv1b-noise100_100-100/code/val.LMDB"
batch_size: 50
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm1"
type: "LRN"
bottom: "pool1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv2_a"
type: "Convolution"
bottom: "norm1"
top: "conv2_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu2_a"
type: "ReLU"
bottom: "conv2_a"
top: "conv2_a"
}
layer {
name: "pool2_a"
type: "Pooling"
bottom: "conv2_a"
top: "pool2_a"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm2_a"
type: "LRN"
bottom: "pool2_a"
top: "norm2_a"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv3_a"
type: "Convolution"
bottom: "norm2_a"
top: "conv3_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3_a"
type: "ReLU"
bottom: "conv3_a"
top: "conv3_a"
}
layer {
name: "conv4_a"
type: "Convolution"
bottom: "conv3_a"
top: "conv4_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu4_a"
type: "ReLU"
bottom: "conv4_a"
top: "conv4_a"
}
layer {
name: "conv5_a"
type: "Convolution"
bottom: "conv4_a"
top: "conv5_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu5_a"
type: "ReLU"
bottom: "conv5_a"
top: "conv5_a"
}
layer {
name: "pool5_a"
type: "Pooling"
bottom: "conv5_a"
top: "pool5_a"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6_a"
type: "InnerProduct"
bottom: "pool5_a"
top: "fc6_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu6_a"
type: "ReLU"
bottom: "fc6_a"
top: "fc6_a"
}
layer {
name: "drop6_a"
type: "Dropout"
bottom: "fc6_a"
top: "fc6_a"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7_a"
type: "InnerProduct"
bottom: "fc6_a"
top: "fc7_a"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu7_a"
type: "ReLU"
bottom: "fc7_a"
top: "fc7_a"
}
layer {
name: "drop7_a"
type: "Dropout"
bottom: "fc7_a"
top: "fc7_a"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8_cayman"
type: "InnerProduct"
bottom: "fc7_a"
top: "fc8_cayman"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fc8_cayman"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8_cayman"
bottom: "label"
top: "loss"
}
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