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- name: "pretrain_cnn_lstm_softmax"
- layer {
- name: "data"
- type: "Python"
- top: "data"
- top: "label"
- top: "clip_markers"
- python_param {
- module: "obj_input_layer"
- layer: "videoReadTrain"
- }
- include: { phase: TRAIN }
- }
- layer {
- name: "data"
- type: "Python"
- top: "data"
- top: "label"
- top: "clip_markers"
- python_param {
- module: "obj_input_layer"
- layer: "videoReadTest"
- }
- 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: 7
- stride: 2
- weight_filler {
- type: "gaussian"
- std: 0.01
- }
- bias_filler {
- type: "constant"
- value: 0.1
- }
- }
- }
- layer {
- name: "relu1"
- type: "ReLU"
- bottom: "conv1"
- top: "conv1"
- }
- layer {
- name: "pool1"
- type: "Pooling"
- bottom: "conv1"
- top: "pool1"
- pooling_param {
- pool: MAX
- kernel_size: 3
- stride: 2
- }
- }
- layer {
- name: "norm1"
- type: "LRN"
- bottom: "pool1"
- top: "norm1"
- lrn_param {
- local_size: 5
- alpha: 0.0001
- beta: 0.75
- }
- }
- layer {
- name: "conv2"
- type: "Convolution"
- bottom: "norm1"
- top: "conv2"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 384
- kernel_size: 5
- group: 2
- stride: 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: "pool2"
- type: "Pooling"
- bottom: "conv2"
- top: "pool2"
- pooling_param {
- pool: MAX
- kernel_size: 3
- stride: 2
- }
- }
- layer {
- name: "norm2"
- type: "LRN"
- bottom: "pool2"
- top: "norm2"
- lrn_param {
- local_size: 5
- alpha: 0.0001
- beta: 0.75
- }
- }
- layer {
- name: "conv3"
- type: "Convolution"
- bottom: "norm2"
- top: "conv3"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 512
- pad: 1
- kernel_size: 3
- weight_filler {
- type: "gaussian"
- std: 0.01
- }
- bias_filler {
- type: "constant"
- value: 0.1
- }
- }
- }
- 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: 512
- 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: 384
- 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: 0.01
- }
- 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: 0.9
- }
- }
- layer{
- name: "reshape-data"
- type: "Reshape"
- bottom: "fc6"
- top: "fc6-reshape"
- reshape_param{
- shape{
- dim: 32 ################ parameter
- dim: 5 ################
- dim: 4096
- }
- }
- }
- layer{
- name: "reshape-cm"
- type: "Reshape"
- bottom: "clip_markers"
- top: "reshape-cm"
- reshape_param{
- shape{
- dim: 30 ################# Parameter
- dim: 5 #################
- }
- }
- }
- layer {
- name: "lstm1"
- type: "LSTM"
- bottom: "fc6-reshape"
- 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-drop"
- type: "Dropout"
- bottom: "lstm1"
- top: "lstm1-drop"
- dropout_param {
- dropout_ratio: 0.5
- }
- }
- layer {
- name: "fc8-final"
- type: "InnerProduct"
- bottom: "lstm1-drop"
- top: "fc8-final"
- param {
- lr_mult: 10
- decay_mult: 1
- }
- param {
- lr_mult: 20
- decay_mult: 0
- }
- inner_product_param {
- num_output: 10 ######################
- weight_filler {
- type: "gaussian"
- std: 0.001
- }
- bias_filler {
- type: "constant"
- value: 0.1
- }
- }
- }
- layer{
- name: "loss"
- type: "SoftmaxWithLoss"
- bottom: "fc8-final"
- bottom: "label"
- top: "loss"
- }
- layer{
- name: "accuracy"
- type: "Accuracy"
- bottom: "fc8-final"
- bottom: "label"
- top: "accuracy"
- }
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