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train_test.prototxt
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name: "GoogleNet"
layers {
top: "data"
top: "label"
name: "data"
type: DATA
data_param {
source: "POSEIDON_ROOT/example/imagenet/ilsvrc12_train_lmdb"
batch_size: 32
backend: LMDB
shared_file_system: true
}
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
}
}
layers {
top: "data"
top: "label"
name: "data"
type: DATA
data_param {
source: "POSEIDON_ROOT/example/imagenet/ilsvrc12_val_lmdb"
batch_size: 50
backend: LMDB
shared_file_system: true
}
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
}
}
layers {
bottom: "data"
top: "conv1/7x7_s2"
name: "conv1/7x7_s2"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 64
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "xavier"
std: 0.1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "conv1/7x7_s2"
top: "conv1/7x7_s2"
name: "conv1/relu_7x7"
type: RELU
}
layers {
bottom: "conv1/7x7_s2"
top: "pool1/3x3_s2"
name: "pool1/3x3_s2"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layers {
bottom: "pool1/3x3_s2"
top: "pool1/norm1"
name: "pool1/norm1"
type: LRN
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layers {
bottom: "pool1/norm1"
top: "conv2/3x3_reduce"
name: "conv2/3x3_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "conv2/3x3_reduce"
top: "conv2/3x3_reduce"
name: "conv2/relu_3x3_reduce"
type: RELU
}
layers {
bottom: "conv2/3x3_reduce"
top: "conv2/3x3"
name: "conv2/3x3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "conv2/3x3"
top: "conv2/3x3"
name: "conv2/relu_3x3"
type: RELU
}
layers {
bottom: "conv2/3x3"
top: "conv2/norm2"
name: "conv2/norm2"
type: LRN
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layers {
bottom: "conv2/norm2"
top: "pool2/3x3_s2"
name: "pool2/3x3_s2"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layers {
bottom: "pool2/3x3_s2"
top: "inception_3a/1x1"
name: "inception_3a/1x1"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/1x1"
top: "inception_3a/1x1"
name: "inception_3a/relu_1x1"
type: RELU
}
layers {
bottom: "pool2/3x3_s2"
top: "inception_3a/3x3_reduce"
name: "inception_3a/3x3_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.09
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/3x3_reduce"
top: "inception_3a/3x3_reduce"
name: "inception_3a/relu_3x3_reduce"
type: RELU
}
layers {
bottom: "inception_3a/3x3_reduce"
top: "inception_3a/3x3"
name: "inception_3a/3x3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/3x3"
top: "inception_3a/3x3"
name: "inception_3a/relu_3x3"
type: RELU
}
layers {
bottom: "pool2/3x3_s2"
top: "inception_3a/5x5_reduce"
name: "inception_3a/5x5_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.2
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/5x5_reduce"
top: "inception_3a/5x5_reduce"
name: "inception_3a/relu_5x5_reduce"
type: RELU
}
layers {
bottom: "inception_3a/5x5_reduce"
top: "inception_3a/5x5"
name: "inception_3a/5x5"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/5x5"
top: "inception_3a/5x5"
name: "inception_3a/relu_5x5"
type: RELU
}
layers {
bottom: "pool2/3x3_s2"
top: "inception_3a/pool"
name: "inception_3a/pool"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layers {
bottom: "inception_3a/pool"
top: "inception_3a/pool_proj"
name: "inception_3a/pool_proj"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3a/pool_proj"
top: "inception_3a/pool_proj"
name: "inception_3a/relu_pool_proj"
type: RELU
}
layers {
bottom: "inception_3a/1x1"
bottom: "inception_3a/3x3"
bottom: "inception_3a/5x5"
bottom: "inception_3a/pool_proj"
top: "inception_3a/output"
name: "inception_3a/output"
type: CONCAT
}
layers {
bottom: "inception_3a/output"
top: "inception_3b/1x1"
name: "inception_3b/1x1"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/1x1"
top: "inception_3b/1x1"
name: "inception_3b/relu_1x1"
type: RELU
}
layers {
bottom: "inception_3a/output"
top: "inception_3b/3x3_reduce"
name: "inception_3b/3x3_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.09
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/3x3_reduce"
top: "inception_3b/3x3_reduce"
name: "inception_3b/relu_3x3_reduce"
type: RELU
}
layers {
bottom: "inception_3b/3x3_reduce"
top: "inception_3b/3x3"
name: "inception_3b/3x3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/3x3"
top: "inception_3b/3x3"
name: "inception_3b/relu_3x3"
type: RELU
}
layers {
bottom: "inception_3a/output"
top: "inception_3b/5x5_reduce"
name: "inception_3b/5x5_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.2
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/5x5_reduce"
top: "inception_3b/5x5_reduce"
name: "inception_3b/relu_5x5_reduce"
type: RELU
}
layers {
bottom: "inception_3b/5x5_reduce"
top: "inception_3b/5x5"
name: "inception_3b/5x5"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 96
pad: 2
kernel_size: 5
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/5x5"
top: "inception_3b/5x5"
name: "inception_3b/relu_5x5"
type: RELU
}
layers {
bottom: "inception_3a/output"
top: "inception_3b/pool"
name: "inception_3b/pool"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layers {
bottom: "inception_3b/pool"
top: "inception_3b/pool_proj"
name: "inception_3b/pool_proj"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_3b/pool_proj"
top: "inception_3b/pool_proj"
name: "inception_3b/relu_pool_proj"
type: RELU
}
layers {
bottom: "inception_3b/1x1"
bottom: "inception_3b/3x3"
bottom: "inception_3b/5x5"
bottom: "inception_3b/pool_proj"
top: "inception_3b/output"
name: "inception_3b/output"
type: CONCAT
}
layers {
bottom: "inception_3b/output"
top: "pool3/3x3_s2"
name: "pool3/3x3_s2"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layers {
bottom: "pool3/3x3_s2"
top: "inception_4a/1x1"
name: "inception_4a/1x1"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/1x1"
top: "inception_4a/1x1"
name: "inception_4a/relu_1x1"
type: RELU
}
layers {
bottom: "pool3/3x3_s2"
top: "inception_4a/3x3_reduce"
name: "inception_4a/3x3_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.09
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/3x3_reduce"
top: "inception_4a/3x3_reduce"
name: "inception_4a/relu_3x3_reduce"
type: RELU
}
layers {
bottom: "inception_4a/3x3_reduce"
top: "inception_4a/3x3"
name: "inception_4a/3x3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 208
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/3x3"
top: "inception_4a/3x3"
name: "inception_4a/relu_3x3"
type: RELU
}
layers {
bottom: "pool3/3x3_s2"
top: "inception_4a/5x5_reduce"
name: "inception_4a/5x5_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.2
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/5x5_reduce"
top: "inception_4a/5x5_reduce"
name: "inception_4a/relu_5x5_reduce"
type: RELU
}
layers {
bottom: "inception_4a/5x5_reduce"
top: "inception_4a/5x5"
name: "inception_4a/5x5"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 48
pad: 2
kernel_size: 5
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/5x5"
top: "inception_4a/5x5"
name: "inception_4a/relu_5x5"
type: RELU
}
layers {
bottom: "pool3/3x3_s2"
top: "inception_4a/pool"
name: "inception_4a/pool"
type: POOLING
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layers {
bottom: "inception_4a/pool"
top: "inception_4a/pool_proj"
name: "inception_4a/pool_proj"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4a/pool_proj"
top: "inception_4a/pool_proj"
name: "inception_4a/relu_pool_proj"
type: RELU
}
layers {
bottom: "inception_4a/1x1"
bottom: "inception_4a/3x3"
bottom: "inception_4a/5x5"
bottom: "inception_4a/pool_proj"
top: "inception_4a/output"
name: "inception_4a/output"
type: CONCAT
}
layers {
bottom: "inception_4a/output"
top: "loss1/ave_pool"
name: "loss1/ave_pool"
type: POOLING
pooling_param {
pool: AVE
kernel_size: 5
stride: 3
}
}
layers {
bottom: "loss1/ave_pool"
top: "loss1/conv"
name: "loss1/conv"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.08
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "loss1/conv"
top: "loss1/conv"
name: "loss1/relu_conv"
type: RELU
}
layers {
bottom: "loss1/conv"
top: "loss1/fc"
name: "loss1/fc"
type: INNER_PRODUCT
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
inner_product_param {
num_output: 1024
weight_filler {
type: "xavier"
std: 0.02
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "loss1/fc"
top: "loss1/fc"
name: "loss1/relu_fc"
type: RELU
}
layers {
bottom: "loss1/fc"
top: "loss1/fc"
name: "loss1/drop_fc"
type: DROPOUT
dropout_param {
dropout_ratio: 0.7
}
}
layers {
bottom: "loss1/fc"
top: "loss1/classifier"
name: "loss1/classifier"
type: INNER_PRODUCT
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
inner_product_param {
num_output: 1000
weight_filler {
type: "xavier"
std: 0.0009765625
}
bias_filler {
type: "constant"
value: 0
}
}
}
layers {
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/loss1"
name: "loss1/loss"
type: SOFTMAX_LOSS
loss_weight: 0.3
}
layers {
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/top-1"
name: "loss1/top-1"
type: ACCURACY
include {
phase: TEST
}
}
layers {
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/top-5"
name: "loss1/top-5"
type: ACCURACY
accuracy_param {
top_k: 5
}
include {
phase: TEST
}
}
layers {
bottom: "inception_4a/output"
top: "inception_4b/1x1"
name: "inception_4b/1x1"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 160
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4b/1x1"
top: "inception_4b/1x1"
name: "inception_4b/relu_1x1"
type: RELU
}
layers {
bottom: "inception_4a/output"
top: "inception_4b/3x3_reduce"
name: "inception_4b/3x3_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 112
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.09
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4b/3x3_reduce"
top: "inception_4b/3x3_reduce"
name: "inception_4b/relu_3x3_reduce"
type: RELU
}
layers {
bottom: "inception_4b/3x3_reduce"
top: "inception_4b/3x3"
name: "inception_4b/3x3"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
std: 0.03
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4b/3x3"
top: "inception_4b/3x3"
name: "inception_4b/relu_3x3"
type: RELU
}
layers {
bottom: "inception_4a/output"
top: "inception_4b/5x5_reduce"
name: "inception_4b/5x5_reduce"
type: CONVOLUTION
blobs_lr: 1
blobs_lr: 2
weight_decay: 1
weight_decay: 0
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.2
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layers {
bottom: "inception_4b/5x5_reduce"
top: "inception_4b/5x5_reduce"
name: "inception_4b/relu_5x5_reduce"
type: RELU
}