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ashutoshsatapathy1990/InceptionV2.prototxt (NVIDIA DIGITS)

Last active June 21, 2019 13:29
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InceptionV2.prototxt (NVIDIA DIGITS)
# Inception V2
name: "Inception V2"
layer {
name: "train-data"
type: "Data"
top: "data"
top: "label"
transform_param {
mirror: true
crop_size: 224
}
data_param {
batch_size: 32
}
include { stage: "train" }
}
layer {
name: "val-data"
type: "Data"
top: "data"
top: "label"
transform_param {
mirror: false
crop_size: 224
}
data_param {
batch_size: 16
}
include { stage: "val" }
}
layer {
name: "conv1/7x7_s2"
type: "Convolution"
bottom: "data"
top: "conv1/7x7_s2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv1/7x7_s2"
name: "conv1/7x7_s2/bn"
top: "conv1/7x7_s2/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv1/7x7_s2/bn"
top: "conv1/7x7_s2/bn"
name: "conv1/relu_7x7"
type: "ReLU"
}
layer {
bottom: "conv1/7x7_s2/bn"
top: "pool1/3x3_s2"
name: "pool1/3x3_s2"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
bottom: "pool1/3x3_s2"
top: "conv2/3x3_reduce"
name: "conv2/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv2/3x3_reduce"
name: "conv2/3x3_reduce/bn"
top: "conv2/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv2/3x3_reduce/bn"
top: "conv2/3x3_reduce/bn"
name: "conv2/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "conv2/3x3_reduce/bn"
top: "conv2/3x3"
name: "conv2/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv2/3x3"
name: "conv2/3x3/bn"
top: "conv2/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "conv2/3x3/bn"
top: "conv2/3x3/bn"
name: "conv2/relu_3x3"
type: "ReLU"
}
layer {
bottom: "conv2/3x3/bn"
top: "pool2/3x3_s2"
name: "pool2/3x3_s2"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
bottom: "pool2/3x3_s2"
top: "inception_3a/1x1"
name: "inception_3a/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/1x1"
name: "inception_3a/1x1/bn"
top: "inception_3a/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/1x1/bn"
top: "inception_3a/1x1/bn"
name: "inception_3a/relu_1x1"
type: "ReLU"
}
layer {
bottom: "pool2/3x3_s2"
top: "inception_3a/3x3_reduce"
name: "inception_3a/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/3x3_reduce"
name: "inception_3a/3x3_reduce/bn"
top: "inception_3a/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/3x3_reduce/bn"
top: "inception_3a/3x3_reduce/bn"
name: "inception_3a/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3a/3x3_reduce/bn"
top: "inception_3a/3x3"
name: "inception_3a/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/3x3"
name: "inception_3a/3x3/bn"
top: "inception_3a/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/3x3/bn"
top: "inception_3a/3x3/bn"
name: "inception_3a/relu_3x3"
type: "ReLU"
}
layer {
bottom: "pool2/3x3_s2"
top: "inception_3a/double3x3_reduce"
name: "inception_3a/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3_reduce"
name: "inception_3a/double3x3_reduce/bn"
top: "inception_3a/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3_reduce/bn"
top: "inception_3a/double3x3_reduce/bn"
name: "inception_3a/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3a/double3x3_reduce/bn"
top: "inception_3a/double3x3a"
name: "inception_3a/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3a"
name: "inception_3a/double3x3a/bn"
top: "inception_3a/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3a/bn"
top: "inception_3a/double3x3a/bn"
name: "inception_3a/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_3a/double3x3a/bn"
top: "inception_3a/double3x3b"
name: "inception_3a/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3b"
name: "inception_3a/double3x3b/bn"
top: "inception_3a/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/double3x3b/bn"
top: "inception_3a/double3x3b/bn"
name: "inception_3a/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "pool2/3x3_s2"
top: "inception_3a/pool"
name: "inception_3a/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_3a/pool"
top: "inception_3a/pool_proj"
name: "inception_3a/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/pool_proj"
name: "inception_3a/pool_proj/bn"
top: "inception_3a/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3a/pool_proj/bn"
top: "inception_3a/pool_proj/bn"
name: "inception_3a/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_3a/1x1/bn"
bottom: "inception_3a/3x3/bn"
bottom: "inception_3a/double3x3b/bn"
bottom: "inception_3a/pool_proj/bn"
top: "inception_3a/output"
name: "inception_3a/output"
type: "Concat"
}
layer {
bottom: "inception_3a/output"
top: "inception_3b/1x1"
name: "inception_3b/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/1x1"
name: "inception_3b/1x1/bn"
top: "inception_3b/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/1x1/bn"
top: "inception_3b/1x1/bn"
name: "inception_3b/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_3a/output"
top: "inception_3b/3x3_reduce"
name: "inception_3b/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/3x3_reduce"
name: "inception_3b/3x3_reduce/bn"
top: "inception_3b/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/3x3_reduce/bn"
top: "inception_3b/3x3_reduce/bn"
name: "inception_3b/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3b/3x3_reduce/bn"
top: "inception_3b/3x3"
name: "inception_3b/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/3x3"
name: "inception_3b/3x3/bn"
top: "inception_3b/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/3x3/bn"
top: "inception_3b/3x3/bn"
name: "inception_3b/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_3a/output"
top: "inception_3b/double3x3_reduce"
name: "inception_3b/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3_reduce"
name: "inception_3b/double3x3_reduce/bn"
top: "inception_3b/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3_reduce/bn"
top: "inception_3b/double3x3_reduce/bn"
name: "inception_3b/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3b/double3x3_reduce/bn"
top: "inception_3b/double3x3a"
name: "inception_3b/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3a"
name: "inception_3b/double3x3a/bn"
top: "inception_3b/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3a/bn"
top: "inception_3b/double3x3a/bn"
name: "inception_3b/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_3b/double3x3a/bn"
top: "inception_3b/double3x3b"
name: "inception_3b/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3b"
name: "inception_3b/double3x3b/bn"
top: "inception_3b/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/double3x3b/bn"
top: "inception_3b/double3x3b/bn"
name: "inception_3b/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_3a/output"
top: "inception_3b/pool"
name: "inception_3b/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_3b/pool"
top: "inception_3b/pool_proj"
name: "inception_3b/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/pool_proj"
name: "inception_3b/pool_proj/bn"
top: "inception_3b/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3b/pool_proj/bn"
top: "inception_3b/pool_proj/bn"
name: "inception_3b/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_3b/1x1/bn"
bottom: "inception_3b/3x3/bn"
bottom: "inception_3b/double3x3b/bn"
bottom: "inception_3b/pool_proj/bn"
top: "inception_3b/output"
name: "inception_3b/output"
type: "Concat"
}
layer {
bottom: "inception_3b/output"
top: "inception_3c/3x3_reduce"
name: "inception_3c/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/3x3_reduce"
name: "inception_3c/3x3_reduce/bn"
top: "inception_3c/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/3x3_reduce/bn"
top: "inception_3c/3x3_reduce/bn"
name: "inception_3c/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3c/3x3_reduce/bn"
top: "inception_3c/3x3"
name: "inception_3c/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 1
stride: 2
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/3x3"
name: "inception_3c/3x3/bn"
top: "inception_3c/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/3x3/bn"
top: "inception_3c/3x3/bn"
name: "inception_3c/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_3b/output"
top: "inception_3c/double3x3_reduce"
name: "inception_3c/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3_reduce"
name: "inception_3c/double3x3_reduce/bn"
top: "inception_3c/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3_reduce/bn"
top: "inception_3c/double3x3_reduce/bn"
name: "inception_3c/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_3c/double3x3_reduce/bn"
top: "inception_3c/double3x3a"
name: "inception_3c/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3a"
name: "inception_3c/double3x3a/bn"
top: "inception_3c/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3a/bn"
top: "inception_3c/double3x3a/bn"
name: "inception_3c/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_3c/double3x3a/bn"
top: "inception_3c/double3x3b"
name: "inception_3c/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
stride: 2
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3b"
name: "inception_3c/double3x3b/bn"
top: "inception_3c/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_3c/double3x3b/bn"
top: "inception_3c/double3x3b/bn"
name: "inception_3c/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_3b/output"
top: "inception_3c/pool/3x3_s2"
name: "inception_3c/pool/3x3_s2"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
bottom: "inception_3c/3x3/bn"
bottom: "inception_3c/double3x3b/bn"
bottom: "inception_3c/pool/3x3_s2"
top: "inception_3c/output"
name: "inception_3c/output"
type: "Concat"
}
layer {
bottom: "inception_3c/output"
top: "inception_4a/1x1"
name: "inception_4a/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/1x1"
name: "inception_4a/1x1/bn"
top: "inception_4a/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/1x1/bn"
top: "inception_4a/1x1/bn"
name: "inception_4a/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_3c/output"
top: "inception_4a/3x3_reduce"
name: "inception_4a/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/3x3_reduce"
name: "inception_4a/3x3_reduce/bn"
top: "inception_4a/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/3x3_reduce/bn"
top: "inception_4a/3x3_reduce/bn"
name: "inception_4a/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4a/3x3_reduce/bn"
top: "inception_4a/3x3"
name: "inception_4a/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/3x3"
name: "inception_4a/3x3/bn"
top: "inception_4a/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/3x3/bn"
top: "inception_4a/3x3/bn"
name: "inception_4a/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_3c/output"
top: "inception_4a/double3x3_reduce"
name: "inception_4a/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3_reduce"
name: "inception_4a/double3x3_reduce/bn"
top: "inception_4a/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3_reduce/bn"
top: "inception_4a/double3x3_reduce/bn"
name: "inception_4a/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4a/double3x3_reduce/bn"
top: "inception_4a/double3x3a"
name: "inception_4a/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3a"
name: "inception_4a/double3x3a/bn"
top: "inception_4a/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3a/bn"
top: "inception_4a/double3x3a/bn"
name: "inception_4a/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_4a/double3x3a/bn"
top: "inception_4a/double3x3b"
name: "inception_4a/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3b"
name: "inception_4a/double3x3b/bn"
top: "inception_4a/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/double3x3b/bn"
top: "inception_4a/double3x3b/bn"
name: "inception_4a/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_3c/output"
top: "inception_4a/pool"
name: "inception_4a/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_4a/pool"
top: "inception_4a/pool_proj"
name: "inception_4a/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/pool_proj"
name: "inception_4a/pool_proj/bn"
top: "inception_4a/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4a/pool_proj/bn"
top: "inception_4a/pool_proj/bn"
name: "inception_4a/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_4a/1x1/bn"
bottom: "inception_4a/3x3/bn"
bottom: "inception_4a/double3x3b/bn"
bottom: "inception_4a/pool_proj/bn"
top: "inception_4a/output"
name: "inception_4a/output"
type: "Concat"
}
layer {
bottom: "inception_4a/output"
top: "loss1/ave_pool"
name: "loss1/ave_pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 5
stride: 3
}
}
layer {
bottom: "loss1/ave_pool"
top: "loss1/conv"
name: "loss1/conv"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss1/conv"
name: "loss1/conv/bn"
top: "loss1/conv/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss1/conv/bn"
top: "loss1/conv/bn"
name: "loss1/relu_conv"
type: "ReLU"
}
layer {
bottom: "loss1/conv/bn"
top: "loss1/fc"
name: "loss1/fc"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss1/fc"
name: "loss1/fc/bn"
top: "loss1/fc/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss1/fc/bn"
top: "loss1/fc/bn"
name: "loss1/relu_fc"
type: "ReLU"
}
layer {
bottom: "loss1/fc/bn"
top: "loss1/classifier"
name: "loss1/classifier"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
exclude { stage: "deploy" }
}
layer {
name: "loss1/loss"
type: "SoftmaxWithLoss"
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/loss"
loss_weight: 0.3
exclude { stage: "deploy" }
}
layer {
name: "loss1/top-1"
type: "Accuracy"
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/accuracy"
include { stage: "val" }
}
layer {
name: "loss1/top-5"
type: "Accuracy"
bottom: "loss1/classifier"
bottom: "label"
top: "loss1/accuracy-top5"
include { stage: "val" }
accuracy_param {
top_k: 5
}
}
layer {
bottom: "inception_4a/output"
top: "inception_4b/1x1"
name: "inception_4b/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/1x1"
name: "inception_4b/1x1/bn"
top: "inception_4b/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/1x1/bn"
top: "inception_4b/1x1/bn"
name: "inception_4b/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_4a/output"
top: "inception_4b/3x3_reduce"
name: "inception_4b/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/3x3_reduce"
name: "inception_4b/3x3_reduce/bn"
top: "inception_4b/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/3x3_reduce/bn"
top: "inception_4b/3x3_reduce/bn"
name: "inception_4b/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4b/3x3_reduce/bn"
top: "inception_4b/3x3"
name: "inception_4b/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/3x3"
name: "inception_4b/3x3/bn"
top: "inception_4b/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/3x3/bn"
top: "inception_4b/3x3/bn"
name: "inception_4b/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_4a/output"
top: "inception_4b/double3x3_reduce"
name: "inception_4b/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3_reduce"
name: "inception_4b/double3x3_reduce/bn"
top: "inception_4b/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3_reduce/bn"
top: "inception_4b/double3x3_reduce/bn"
name: "inception_4b/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4b/double3x3_reduce/bn"
top: "inception_4b/double3x3a"
name: "inception_4b/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3a"
name: "inception_4b/double3x3a/bn"
top: "inception_4b/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3a/bn"
top: "inception_4b/double3x3a/bn"
name: "inception_4b/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_4b/double3x3a/bn"
top: "inception_4b/double3x3b"
name: "inception_4b/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3b"
name: "inception_4b/double3x3b/bn"
top: "inception_4b/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/double3x3b/bn"
top: "inception_4b/double3x3b/bn"
name: "inception_4b/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_4a/output"
top: "inception_4b/pool"
name: "inception_4b/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_4b/pool"
top: "inception_4b/pool_proj"
name: "inception_4b/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/pool_proj"
name: "inception_4b/pool_proj/bn"
top: "inception_4b/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4b/pool_proj/bn"
top: "inception_4b/pool_proj/bn"
name: "inception_4b/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_4b/1x1/bn"
bottom: "inception_4b/3x3/bn"
bottom: "inception_4b/double3x3b/bn"
bottom: "inception_4b/pool_proj/bn"
top: "inception_4b/output"
name: "inception_4b/output"
type: "Concat"
}
layer {
bottom: "inception_4b/output"
top: "inception_4c/1x1"
name: "inception_4c/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/1x1"
name: "inception_4c/1x1/bn"
top: "inception_4c/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/1x1/bn"
top: "inception_4c/1x1/bn"
name: "inception_4c/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_4b/output"
top: "inception_4c/3x3_reduce"
name: "inception_4c/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/3x3_reduce"
name: "inception_4c/3x3_reduce/bn"
top: "inception_4c/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/3x3_reduce/bn"
top: "inception_4c/3x3_reduce/bn"
name: "inception_4c/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4c/3x3_reduce/bn"
top: "inception_4c/3x3"
name: "inception_4c/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/3x3"
name: "inception_4c/3x3/bn"
top: "inception_4c/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/3x3/bn"
top: "inception_4c/3x3/bn"
name: "inception_4c/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_4b/output"
top: "inception_4c/double3x3_reduce"
name: "inception_4c/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3_reduce"
name: "inception_4c/double3x3_reduce/bn"
top: "inception_4c/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3_reduce/bn"
top: "inception_4c/double3x3_reduce/bn"
name: "inception_4c/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4c/double3x3_reduce/bn"
top: "inception_4c/double3x3a"
name: "inception_4c/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3a"
name: "inception_4c/double3x3a/bn"
top: "inception_4c/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3a/bn"
top: "inception_4c/double3x3a/bn"
name: "inception_4c/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_4c/double3x3a/bn"
top: "inception_4c/double3x3b"
name: "inception_4c/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3b"
name: "inception_4c/double3x3b/bn"
top: "inception_4c/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/double3x3b/bn"
top: "inception_4c/double3x3b/bn"
name: "inception_4c/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_4b/output"
top: "inception_4c/pool"
name: "inception_4c/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_4c/pool"
top: "inception_4c/pool_proj"
name: "inception_4c/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/pool_proj"
name: "inception_4c/pool_proj/bn"
top: "inception_4c/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4c/pool_proj/bn"
top: "inception_4c/pool_proj/bn"
name: "inception_4c/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_4c/1x1/bn"
bottom: "inception_4c/3x3/bn"
bottom: "inception_4c/double3x3b/bn"
bottom: "inception_4c/pool_proj/bn"
top: "inception_4c/output"
name: "inception_4c/output"
type: "Concat"
}
layer {
bottom: "inception_4c/output"
top: "inception_4d/1x1"
name: "inception_4d/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/1x1"
name: "inception_4d/1x1/bn"
top: "inception_4d/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/1x1/bn"
top: "inception_4d/1x1/bn"
name: "inception_4d/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_4c/output"
top: "inception_4d/3x3_reduce"
name: "inception_4d/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/3x3_reduce"
name: "inception_4d/3x3_reduce/bn"
top: "inception_4d/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/3x3_reduce/bn"
top: "inception_4d/3x3_reduce/bn"
name: "inception_4d/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4d/3x3_reduce/bn"
top: "inception_4d/3x3"
name: "inception_4d/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/3x3"
name: "inception_4d/3x3/bn"
top: "inception_4d/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/3x3/bn"
top: "inception_4d/3x3/bn"
name: "inception_4d/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_4c/output"
top: "inception_4d/double3x3_reduce"
name: "inception_4d/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3_reduce"
name: "inception_4d/double3x3_reduce/bn"
top: "inception_4d/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3_reduce/bn"
top: "inception_4d/double3x3_reduce/bn"
name: "inception_4d/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4d/double3x3_reduce/bn"
top: "inception_4d/double3x3a"
name: "inception_4d/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3a"
name: "inception_4d/double3x3a/bn"
top: "inception_4d/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3a/bn"
top: "inception_4d/double3x3a/bn"
name: "inception_4d/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_4d/double3x3a/bn"
top: "inception_4d/double3x3b"
name: "inception_4d/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3b"
name: "inception_4d/double3x3b/bn"
top: "inception_4d/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/double3x3b/bn"
top: "inception_4d/double3x3b/bn"
name: "inception_4d/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_4c/output"
top: "inception_4d/pool"
name: "inception_4d/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_4d/pool"
top: "inception_4d/pool_proj"
name: "inception_4d/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/pool_proj"
name: "inception_4d/pool_proj/bn"
top: "inception_4d/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4d/pool_proj/bn"
top: "inception_4d/pool_proj/bn"
name: "inception_4d/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_4d/1x1/bn"
bottom: "inception_4d/3x3/bn"
bottom: "inception_4d/double3x3b/bn"
bottom: "inception_4d/pool_proj/bn"
top: "inception_4d/output"
name: "inception_4d/output"
type: "Concat"
}
layer {
bottom: "inception_4d/output"
top: "loss2/ave_pool"
name: "loss2/ave_pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 5
stride: 3
}
}
layer {
bottom: "loss2/ave_pool"
top: "loss2/conv"
name: "loss2/conv"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss2/conv"
name: "loss2/conv/bn"
top: "loss2/conv/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss2/conv/bn"
top: "loss2/conv/bn"
name: "loss2/relu_conv"
type: "ReLU"
}
layer {
bottom: "loss2/conv/bn"
top: "loss2/fc"
name: "loss2/fc"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 1024
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss2/fc"
name: "loss2/fc/bn"
top: "loss2/fc/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "loss2/fc/bn"
top: "loss2/fc/bn"
name: "loss2/relu_fc"
type: "ReLU"
}
layer {
bottom: "loss2/fc/bn"
top: "loss2/classifier"
name: "loss2/classifier"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
exclude { stage: "deploy" }
}
layer {
name: "loss2/loss"
type: "SoftmaxWithLoss"
bottom: "loss2/classifier"
bottom: "label"
top: "loss2/loss"
loss_weight: 0.3
exclude { stage: "deploy" }
}
layer {
name: "loss2/top-1"
type: "Accuracy"
bottom: "loss2/classifier"
bottom: "label"
top: "loss2/accuracy"
include { stage: "val" }
}
layer {
name: "loss2/top-5"
type: "Accuracy"
bottom: "loss2/classifier"
bottom: "label"
top: "loss2/accuracy-top5"
include { stage: "val" }
accuracy_param {
top_k: 5
}
}
layer {
bottom: "inception_4d/output"
top: "inception_4e/3x3_reduce"
name: "inception_4e/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/3x3_reduce"
name: "inception_4e/3x3_reduce/bn"
top: "inception_4e/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/3x3_reduce/bn"
top: "inception_4e/3x3_reduce/bn"
name: "inception_4e/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4e/3x3_reduce/bn"
top: "inception_4e/3x3"
name: "inception_4e/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
stride: 2
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
## BatchNorm
layer {
bottom: "inception_4e/3x3"
name: "inception_4e/3x3/bn"
top: "inception_4e/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/3x3/bn"
top: "inception_4e/3x3/bn"
name: "inception_4e/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_4d/output"
top: "inception_4e/double3x3_reduce"
name: "inception_4e/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3_reduce"
name: "inception_4e/double3x3_reduce/bn"
top: "inception_4e/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3_reduce/bn"
top: "inception_4e/double3x3_reduce/bn"
name: "inception_4e/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_4e/double3x3_reduce/bn"
top: "inception_4e/double3x3a"
name: "inception_4e/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3a"
name: "inception_4e/double3x3a/bn"
top: "inception_4e/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3a/bn"
top: "inception_4e/double3x3a/bn"
name: "inception_4e/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_4e/double3x3a/bn"
top: "inception_4e/double3x3b"
name: "inception_4e/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
stride: 2
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3b"
name: "inception_4e/double3x3b/bn"
top: "inception_4e/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_4e/double3x3b/bn"
top: "inception_4e/double3x3b/bn"
name: "inception_4e/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_4d/output"
top: "inception_4e/pool/3x3_s2"
name: "inception_4e/pool/3x3_s2"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
bottom: "inception_4e/3x3/bn"
bottom: "inception_4e/double3x3b/bn"
bottom: "inception_4e/pool/3x3_s2"
top: "inception_4e/output"
name: "inception_4e/output"
type: "Concat"
}
layer {
bottom: "inception_4e/output"
top: "inception_5a/1x1"
name: "inception_5a/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 352
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/1x1"
name: "inception_5a/1x1/bn"
top: "inception_5a/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/1x1/bn"
top: "inception_5a/1x1/bn"
name: "inception_5a/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_4e/output"
top: "inception_5a/3x3_reduce"
name: "inception_5a/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/3x3_reduce"
name: "inception_5a/3x3_reduce/bn"
top: "inception_5a/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/3x3_reduce/bn"
top: "inception_5a/3x3_reduce/bn"
name: "inception_5a/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_5a/3x3_reduce/bn"
top: "inception_5a/3x3"
name: "inception_5a/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/3x3"
name: "inception_5a/3x3/bn"
top: "inception_5a/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/3x3/bn"
top: "inception_5a/3x3/bn"
name: "inception_5a/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_4e/output"
top: "inception_5a/double3x3_reduce"
name: "inception_5a/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3_reduce"
name: "inception_5a/double3x3_reduce/bn"
top: "inception_5a/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3_reduce/bn"
top: "inception_5a/double3x3_reduce/bn"
name: "inception_5a/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_5a/double3x3_reduce/bn"
top: "inception_5a/double3x3a"
name: "inception_5a/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3a"
name: "inception_5a/double3x3a/bn"
top: "inception_5a/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3a/bn"
top: "inception_5a/double3x3a/bn"
name: "inception_5a/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_5a/double3x3a/bn"
top: "inception_5a/double3x3b"
name: "inception_5a/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3b"
name: "inception_5a/double3x3b/bn"
top: "inception_5a/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/double3x3b/bn"
top: "inception_5a/double3x3b/bn"
name: "inception_5a/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_4e/output"
top: "inception_5a/pool"
name: "inception_5a/pool"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_5a/pool"
top: "inception_5a/pool_proj"
name: "inception_5a/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
## BatchNorm
layer {
bottom: "inception_5a/pool_proj"
name: "inception_5a/pool_proj/bn"
top: "inception_5a/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5a/pool_proj/bn"
top: "inception_5a/pool_proj/bn"
name: "inception_5a/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_5a/1x1/bn"
bottom: "inception_5a/3x3/bn"
bottom: "inception_5a/double3x3b/bn"
bottom: "inception_5a/pool_proj/bn"
top: "inception_5a/output"
name: "inception_5a/output"
type: "Concat"
}
layer {
bottom: "inception_5a/output"
top: "inception_5b/1x1"
name: "inception_5b/1x1"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 352
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/1x1"
name: "inception_5b/1x1/bn"
top: "inception_5b/1x1/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/1x1/bn"
top: "inception_5b/1x1/bn"
name: "inception_5b/relu_1x1"
type: "ReLU"
}
layer {
bottom: "inception_5a/output"
top: "inception_5b/3x3_reduce"
name: "inception_5b/3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/3x3_reduce"
name: "inception_5b/3x3_reduce/bn"
top: "inception_5b/3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/3x3_reduce/bn"
top: "inception_5b/3x3_reduce/bn"
name: "inception_5b/relu_3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_5b/3x3_reduce/bn"
top: "inception_5b/3x3"
name: "inception_5b/3x3"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/3x3"
name: "inception_5b/3x3/bn"
top: "inception_5b/3x3/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/3x3/bn"
top: "inception_5b/3x3/bn"
name: "inception_5b/relu_3x3"
type: "ReLU"
}
layer {
bottom: "inception_5a/output"
top: "inception_5b/double3x3_reduce"
name: "inception_5b/double3x3_reduce"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3_reduce"
name: "inception_5b/double3x3_reduce/bn"
top: "inception_5b/double3x3_reduce/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3_reduce/bn"
top: "inception_5b/double3x3_reduce/bn"
name: "inception_5b/relu_double3x3_reduce"
type: "ReLU"
}
layer {
bottom: "inception_5b/double3x3_reduce/bn"
top: "inception_5b/double3x3a"
name: "inception_5b/double3x3a"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3a"
name: "inception_5b/double3x3a/bn"
top: "inception_5b/double3x3a/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3a/bn"
top: "inception_5b/double3x3a/bn"
name: "inception_5b/relu_double3x3a"
type: "ReLU"
}
layer {
bottom: "inception_5b/double3x3a/bn"
top: "inception_5b/double3x3b"
name: "inception_5b/double3x3b"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3b"
name: "inception_5b/double3x3b/bn"
top: "inception_5b/double3x3b/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/double3x3b/bn"
top: "inception_5b/double3x3b/bn"
name: "inception_5b/relu_double3x3b"
type: "ReLU"
}
layer {
bottom: "inception_5a/output"
top: "inception_5b/pool"
name: "inception_5b/pool"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
bottom: "inception_5b/pool"
top: "inception_5b/pool_proj"
name: "inception_5b/pool_proj"
type: "Convolution"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/pool_proj"
name: "inception_5b/pool_proj/bn"
top: "inception_5b/pool_proj/bn"
type: "BatchNorm"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
batch_norm_param {
scale_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
bottom: "inception_5b/pool_proj/bn"
top: "inception_5b/pool_proj/bn"
name: "inception_5b/relu_pool_proj"
type: "ReLU"
}
layer {
bottom: "inception_5b/1x1/bn"
bottom: "inception_5b/3x3/bn"
bottom: "inception_5b/double3x3b/bn"
bottom: "inception_5b/pool_proj/bn"
top: "inception_5b/output"
name: "inception_5b/output"
type: "Concat"
}
layer {
bottom: "inception_5b/output"
top: "pool5/7x7_s1"
name: "pool5/7x7_s1"
type: "Pooling"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
}
}
layer {
bottom: "pool5/7x7_s1"
top: "loss3/classifier"
name: "loss3/classifier"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
weight_filler {
type: "msra"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "loss3/loss"
type: "SoftmaxWithLoss"
bottom: "loss3/classifier"
bottom: "label"
top: "loss"
loss_weight: 1
exclude { stage: "deploy" }
}
layer {
name: "loss3/top-1"
type: "Accuracy"
bottom: "loss3/classifier"
bottom: "label"
top: "accuracy"
include { stage: "val" }
}
layer {
name: "loss3/top-5"
type: "Accuracy"
bottom: "loss3/classifier"
bottom: "label"
top: "accuracy-top5"
include { stage: "val" }
accuracy_param {
top_k: 5
}
}
layer {
name: "softmax"
type: "Softmax"
bottom: "loss3/classifier"
top: "softmax"
include { stage: "deploy" }
}
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