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mobilenet_v3_large_1.0.prototxt
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mobilenet_v3_large_1.0.prototxt
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name: "mobilenet v3"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224
#################### stage 1 ####################
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 16
pad: 1
bias_term: false
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv1-bn"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv1-bn-scale"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
bias_term: true
}
}
# H-swish
layer {
name: "conv1/shift"
type: "Power"
bottom: "conv1"
top: "conv1/shift"
power_param {
power: 1
scale: 1
shift: 3
}
}
layer {
name: "conv1/shift-relu"
type: "ReLU6"
bottom: "conv1/shift"
top: "conv1/shift"
}
layer {
name: "conv1/shift-div"
type: "Power"
bottom: "conv1/shift"
top: "conv1/shift-div"
power_param {
power: 1
scale: 0.1666666667
shift: 0
}
}
layer {
name: "conv1/hswish"
type: "Eltwise"
bottom: "conv1"
bottom: "conv1/shift-div"
top: "conv1/hswish"
eltwise_param {
operation: PROD
}
}
#################### stage 2-1 ####################
layer {
name: "conv2-1/expand"
type: "Convolution"
bottom: "conv1/hswish"
top: "conv2-1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 16
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2-1/expand-bn"
type: "BatchNorm"
bottom: "conv2-1/expand"
top: "conv2-1/expand"
}
layer {
name: "conv2-1/expand-bn-scale"
type: "Scale"
bottom: "conv2-1/expand"
top: "conv2-1/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv2-1/expand-relu"
type: "ReLU6"
bottom: "conv2-1/expand"
top: "conv2-1/expand"
}
layer {
name: "conv2-1/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv2-1/expand"
top: "conv2-1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 16
group: 16
pad: 1
bias_term: false
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv2-1/dwise-bn"
type: "BatchNorm"
bottom: "conv2-1/dwise"
top: "conv2-1/dwise"
}
layer {
name: "conv2-1/dwise-bn-scale"
type: "Scale"
bottom: "conv2-1/dwise"
top: "conv2-1/dwise"
scale_param {
bias_term: true
}
}
layer {
name: "conv2-1/dwise-relu"
type: "ReLU6"
bottom: "conv2-1/dwise"
top: "conv2-1/dwise"
}
layer {
name: "conv2-1/linear"
type: "Convolution"
bottom: "conv2-1/dwise"
top: "conv2-1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 16
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2-1/linear-bn"
type: "BatchNorm"
bottom: "conv2-1/linear"
top: "conv2-1/linear"
}
layer {
name: "conv2-1/linear-bn-scale"
type: "Scale"
bottom: "conv2-1/linear"
top: "conv2-1/linear"
scale_param {
bias_term: true
}
}
layer {
name: "block2-1"
type: "Eltwise"
bottom: "conv1/hswish"
bottom: "conv2-1/linear"
top: "block2-1"
}
#################### stage 2-2 ####################
layer {
name: "conv2-2/expand"
type: "Convolution"
bottom: "block2-1"
top: "conv2-2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2-2/expand-bn"
type: "BatchNorm"
bottom: "conv2-2/expand"
top: "conv2-2/expand"
}
layer {
name: "conv2-2/expand-bn-scale"
type: "Scale"
bottom: "conv2-2/expand"
top: "conv2-2/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv2-2/expand-relu"
type: "ReLU6"
bottom: "conv2-2/expand"
top: "conv2-2/expand"
}
layer {
name: "conv2-2/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv2-2/expand"
top: "conv2-2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
group: 64
pad: 1
bias_term: false
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv2-2/dwise-bn"
type: "BatchNorm"
bottom: "conv2-2/dwise"
top: "conv2-2/dwise"
}
layer {
name: "conv2-2/dwise-bn-scale"
type: "Scale"
bottom: "conv2-2/dwise"
top: "conv2-2/dwise"
scale_param {
bias_term: true
}
}
layer {
name: "conv2-2/dwise-relu"
type: "ReLU6"
bottom: "conv2-2/dwise"
top: "conv2-2/dwise"
}
layer {
name: "conv2-2/linear"
type: "Convolution"
bottom: "conv2-2/dwise"
top: "conv2-2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 24
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2-2/linear-bn"
type: "BatchNorm"
bottom: "conv2-2/linear"
top: "conv2-2/linear"
}
layer {
name: "conv2-2/linear-bn-scale"
type: "Scale"
bottom: "conv2-2/linear"
top: "conv2-2/linear"
scale_param {
bias_term: true
}
}
#################### stage 3-1 ####################
layer {
name: "conv3-1/expand"
type: "Convolution"
bottom: "conv2-2/linear"
top: "conv3-1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 72
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3-1/expand-bn"
type: "BatchNorm"
bottom: "conv3-1/expand"
top: "conv3-1/expand"
}
layer {
name: "conv3-1/expand-bn-scale"
type: "Scale"
bottom: "conv3-1/expand"
top: "conv3-1/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv3-1/expand-relu"
type: "ReLU6"
bottom: "conv3-1/expand"
top: "conv3-1/expand"
}
layer {
name: "conv3-1/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv3-1/expand"
top: "conv3-1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 72
group: 72
pad: 1
bias_term: false
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv3-1/dwise-bn"
type: "BatchNorm"
bottom: "conv3-1/dwise"
top: "conv3-1/dwise"
}
layer {
name: "conv3-1/dwise-bn-scale"
type: "Scale"
bottom: "conv3-1/dwise"
top: "conv3-1/dwise"
scale_param {
bias_term: true
}
}
layer {
name: "conv3-1/dwise-relu"
type: "ReLU6"
bottom: "conv3-1/dwise"
top: "conv3-1/dwise"
}
layer {
name: "conv3-1/linear"
type: "Convolution"
bottom: "conv3-1/dwise"
top: "conv3-1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 24
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3-1/linear-bn"
type: "BatchNorm"
bottom: "conv3-1/linear"
top: "conv3-1/linear"
}
layer {
name: "conv3-1/linear-bn-scale"
type: "Scale"
bottom: "conv3-1/linear"
top: "conv3-1/linear"
scale_param {
bias_term: true
}
}
layer {
name: "block3-1"
type: "Eltwise"
bottom: "conv2-2/linear"
bottom: "conv3-1/linear"
top: "block3-1"
}
#################### stage 3-2 ####################
layer {
name: "conv3-2/expand"
type: "Convolution"
bottom: "block3-1"
top: "conv3-2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 72
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3-2/expand-bn"
type: "BatchNorm"
bottom: "conv3-2/expand"
top: "conv3-2/expand"
}
layer {
name: "conv3-2/expand-bn-scale"
type: "Scale"
bottom: "conv3-2/expand"
top: "conv3-2/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv3-2/expand-relu"
type: "ReLU6"
bottom: "conv3-2/expand"
top: "conv3-2/expand"
}
layer {
name: "conv3-2/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv3-2/expand"
top: "conv3-2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 72
group: 72
pad: 2
bias_term: false
kernel_size: 5
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv3-2/dwise-bn"
type: "BatchNorm"
bottom: "conv3-2/dwise"
top: "conv3-2/dwise"
}
layer {
name: "conv3-2/dwise-bn-scale"
type: "Scale"
bottom: "conv3-2/dwise"
top: "conv3-2/dwise"
scale_param {
bias_term: true
}
}
# se
layer {
name: "conv3-2/dwise-se-pool"
type: "Pooling"
bottom: "conv3-2/dwise"
top: "conv3-2/dwise-se-pool"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "conv3-2/dwise-se-fc1"
type: "InnerProduct"
bottom: "conv3-2/dwise-se-pool"
top:"conv3-2/dwise-se-fc1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 18
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv3-2/dwise-se-fc1-relu"
type: "ReLU6"
bottom: "conv3-2/dwise-se-fc1"
top: "conv3-2/dwise-se-fc1"
}
layer {
name: "conv3-2/dwise-se-fc2"
type: "InnerProduct"
bottom: "conv3-2/dwise-se-fc1"
top:"conv3-2/dwise-se-fc2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 72
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
# H-sigmoid
layer {
name: "conv3-2/dwise-se-fc2/shift"
type: "Power"
bottom: "conv3-2/dwise-se-fc2"
top: "conv3-2/dwise-se-fc2/shift"
power_param {
power: 1
scale: 1
shift: 3
}
}
layer {
name: "conv3-2/dwise-se-fc2/shift-relu"
type: "ReLU6"
bottom: "conv3-2/dwise-se-fc2/shift"
top: "conv3-2/dwise-se-fc2/shift"
}
layer {
name: "conv3-2/dwise-se-fc2/shift-div"
type: "Power"
bottom: "conv3-2/dwise-se-fc2/shift"
top: "conv3-2/dwise-se-fc2/shift-div"
power_param {
power: 1
scale: 0.1666666667
shift: 0
}
}
layer {
name: "conv3-2/dwise/scale"
type: "Scale"
bottom: "conv3-2/dwise"
bottom: "conv3-2/dwise-se-fc2/shift-div"
top: "conv3-2/dwise/scale"
scale_param{
axis: 0
}
}
layer {
name: "conv3-2/dwise/scale-relu"
type: "ReLU6"
bottom: "conv3-2/dwise/scale"
top: "conv3-2/dwise/scale"
}
layer {
name: "conv3-2/linear"
type: "Convolution"
bottom: "conv3-2/dwise/scale"
top: "conv3-2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 40
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3-2/linear-bn"
type: "BatchNorm"
bottom: "conv3-2/linear"
top: "conv3-2/linear"
}
layer {
name: "conv3-2/linear-bn-scale"
type: "Scale"
bottom: "conv3-2/linear"
top: "conv3-2/linear"
scale_param {
bias_term: true
}
}
#################### stage 4-1 ####################
layer {
name: "conv4-1/expand"
type: "Convolution"
bottom: "conv3-2/linear"
top: "conv4-1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 120
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4-1/expand-bn"
type: "BatchNorm"
bottom: "conv4-1/expand"
top: "conv4-1/expand"
}
layer {
name: "conv4-1/expand-bn-scale"
type: "Scale"
bottom: "conv4-1/expand"
top: "conv4-1/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv4-1/expand-relu"
type: "ReLU6"
bottom: "conv4-1/expand"
top: "conv4-1/expand"
}
layer {
name: "conv4-1/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv4-1/expand"
top: "conv4-1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 120
group: 120
pad: 2
bias_term: false
kernel_size: 5
stride: 1
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4-1/dwise-bn"
type: "BatchNorm"
bottom: "conv4-1/dwise"
top: "conv4-1/dwise"
}
layer {
name: "conv4-1/dwise-bn-scale"
type: "Scale"
bottom: "conv4-1/dwise"
top: "conv4-1/dwise"
scale_param {
bias_term: true
}
}
# se
layer {
name: "conv4-1/dwise-se-pool"
type: "Pooling"
bottom: "conv4-1/dwise"
top: "conv4-1/dwise-se-pool"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "conv4-1/dwise-se-fc1"
type: "InnerProduct"
bottom: "conv4-1/dwise-se-pool"
top:"conv4-1/dwise-se-fc1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 30
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv4-1/dwise-se-fc1-relu"
type: "ReLU6"
bottom: "conv4-1/dwise-se-fc1"
top: "conv4-1/dwise-se-fc1"
}
layer {
name: "conv4-1/dwise-se-fc2"
type: "InnerProduct"
bottom: "conv4-1/dwise-se-fc1"
top:"conv4-1/dwise-se-fc2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 120
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
# H-sigmoid
layer {
name: "conv4-1/dwise-se-fc2/shift"
type: "Power"
bottom: "conv4-1/dwise-se-fc2"
top: "conv4-1/dwise-se-fc2/shift"
power_param {
power: 1
scale: 1
shift: 3
}
}
layer {
name: "conv4-1/dwise-se-fc2/shift-relu"
type: "ReLU6"
bottom: "conv4-1/dwise-se-fc2/shift"
top: "conv4-1/dwise-se-fc2/shift"
}
layer {
name: "conv4-1/dwise-se-fc2/shift-div"
type: "Power"
bottom: "conv4-1/dwise-se-fc2/shift"
top: "conv4-1/dwise-se-fc2/shift-div"
power_param {
power: 1
scale: 0.1666666667
shift: 0
}
}
layer {
name: "conv4-1/dwise/scale"
type: "Scale"
bottom: "conv4-1/dwise"
bottom: "conv4-1/dwise-se-fc2/shift-div"
top: "conv4-1/dwise/scale"
scale_param{
axis: 0
}
}
layer {
name: "conv4-1/dwise/scale-relu"
type: "ReLU6"
bottom: "conv4-1/dwise/scale"
top: "conv4-1/dwise/scale"
}
layer {
name: "conv4-1/linear"
type: "Convolution"
bottom: "conv4-1/dwise/scale"
top: "conv4-1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 40
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4-1/linear-bn"
type: "BatchNorm"
bottom: "conv4-1/linear"
top: "conv4-1/linear"
}
layer {
name: "conv4-1/linear-bn-scale"
type: "Scale"
bottom: "conv4-1/linear"
top: "conv4-1/linear"
scale_param {
bias_term: true
}
}
layer {
name: "block4-1"
type: "Eltwise"
bottom: "conv3-2/linear"
bottom: "conv4-1/linear"
top: "block4-1"
}
#################### stage 4-2 ####################
layer {
name: "conv4-2/expand"
type: "Convolution"
bottom: "block4-1"
top: "conv4-2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 120
pad: 0
bias_term: false
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4-2/expand-bn"
type: "BatchNorm"
bottom: "conv4-2/expand"
top: "conv4-2/expand"
}
layer {
name: "conv4-2/expand-bn-scale"
type: "Scale"
bottom: "conv4-2/expand"
top: "conv4-2/expand"
scale_param {
bias_term: true
}
}
layer {
name: "conv4-2/expand-relu"
type: "ReLU6"
bottom: "conv4-2/expand"
top: "conv4-2/expand"
}
layer {
name: "conv4-2/dwise"
#type: "Convolution"
type: "DepthwiseConvolution"
bottom: "conv4-2/expand"
top: "conv4-2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 120
group: 120
pad: 2
bias_term: false
kernel_size: 5
stride: 1
weight_filler {
type: "msra"
}
engine: CAFFE