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name: "cnn_lstm_softmax"
layer {
name: "data"
type: "Python"
top: "data"
top: "label"
top: "clip_markers"
python_param {
module: "my_obj_input_layer"
layer: "ReadTrain"
}
include: { phase: TRAIN }
}
layer {
name: "data"
type: "Python"
top: "data"
top: "label"
top: "clip_markers"
python_param {
module: "my_obj_input_layer"
layer: "ReadTest"
}
include: { phase: TEST stage: "test-on-test" }
}
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: "norm1"
type: "LRN"
bottom: "conv1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "norm1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
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: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "norm2"
type: "LRN"
bottom: "conv2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "norm2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
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"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
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: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
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: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
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: 0.1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
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: 0.1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer{
name: "reshape-data"
type: "Reshape"
bottom: "fc7"
top: "reshape-data"
reshape_param{
shape{
dim: 16
dim: 3
dim: 4096
}
}
}
layer {
name: "reshape-cm"
type: "Reshape"
bottom: "clip_markers"
top: "reshape-cm"
reshape_param {
shape{
dim: 16
dim: 3
}
}
}
layer {
name: "lstm1"
type: "LSTM"
bottom: "reshape-data"
bottom: "reshape-cm"
top: "lstm1"
recurrent_param {
num_output: 4096
weight_filler {
type: "uniform"
min: -0.01
max: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "lstm1_slice"
type: "Slice"
bottom: "lstm1"
top: "lstm1_0"
top: "lstm1_1"
top: "lstm1_2"
top: "lstm1_3"
top: "lstm1_4"
top: "lstm1_5"
top: "lstm1_6"
top: "lstm1_7"
top: "lstm1_8"
top: "lstm1_9"
top: "lstm1_10"
top: "lstm1_11"
top: "lstm1_12"
top: "lstm1_13"
top: "lstm1_14"
top: "lstm1_15"
slice_param {
axis: 0
}
}
layer {
name: "maxpool"
type: "Eltwise"
bottom: "lstm1_0"
bottom: "lstm1_1"
bottom: "lstm1_2"
bottom: "lstm1_3"
bottom: "lstm1_4"
bottom: "lstm1_5"
bottom: "lstm1_6"
bottom: "lstm1_7"
bottom: "lstm1_8"
bottom: "lstm1_9"
bottom: "lstm1_10"
bottom: "lstm1_11"
bottom: "lstm1_12"
bottom: "lstm1_13"
bottom: "lstm1_14"
bottom: "lstm1_15"
top: "maxpool"
eltwise_param {
operation: MAX
}
}
layer{
name: "reshape-lstm"
type: "Reshape"
bottom: "maxpool"
top: "reshape-lstm"
reshape_param {
shape {
dim: 3
dim: 4096
}
}
}
layer {
name: "lstm1-drop"
type: "Dropout"
bottom: "reshape-lstm"
top: "lstm1-drop"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "lstm1-drop"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 10
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fc8"
bottom: "label"
top: "accuracy"
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8"
bottom: "label"
top: "loss"
}
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