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人脸属性分析多任务训练 multi cnn for face attribution_多任务人脸属性分类

作者：我家小花儿 | 2024-06-01 04:03:29

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多任务人脸属性分类

face_attribute.prototxt 

shuffle_net   10-20ms

  1. name: "FaceAttribution"
  2. layer {
  3.   name: "data"
  4.   type: "Data"
  5.   top: "data"
  6.   include {
  7.     phase: TRAIN
  8.   }
  9.   transform_param {
  10. 		mean_value: 104
  11. 		mean_value: 117
  12. 		mean_value: 124
  13. 		scale: 0.0078125
  14.   }
  15.   data_param {
  16.     source: "../lmdb/train_data_npd"
  17.     batch_size: 128
  18.     backend: LMDB
  19.   }
  20. }
  21. layer {
  22.   name: "data"
  23.   type: "Data"
  24.   top: "label"
  25.   include {
  26.     phase: TRAIN
  27.   }
  28.   data_param {
  29.     source: "../lmdb/train_label_npd"
  30.     batch_size: 128
  31.     backend: LMDB
  32.   }
  33. }
  34.  
  35. layer {
  36.   name: "data"
  37.   type: "Data"
  38.   top: "data"
  39.   include {
  40.     phase: TEST
  41.   }
  42.   transform_param {
  43. 		mean_value: 104
  44. 		mean_value: 117
  45. 		mean_value: 124
  46. 		scale: 0.0078125
  47.   }
  48.   data_param {
  49.     source: "../lmdb/test_data_npd"
  50.     batch_size: 128
  51.     backend: LMDB
  52.   }
  53. }
  54. layer {
  55.   name: "data"
  56.   type: "Data"
  57.   top: "label"
  58.   include {
  59.     phase: TEST
  60.   }
  61.   data_param {
  62.     source: "../lmdb/test_label_npd"
  63.     batch_size: 128
  64.     backend: LMDB
  65.   }
  66. }
  67.  
  68.  
  69. layer {
  70.   name: "conv1"
  71.   type: "Convolution"
  72.   bottom: "data"
  73.   top: "conv1"
  74.   convolution_param {
  75.     num_output: 24
  76.     pad: 1
  77.     kernel_size: 3
  78.     stride: 2
  79.     bias_term: false
  80.     weight_filler {
  81.       type: "msra"
  82.     }
  83.   }
  84. }
  85. layer {
  86.   name: "conv1_bn"
  87.   type: "BatchNorm"
  88.   bottom: "conv1"
  89.   top: "conv1"
  90.   param {
  91.     lr_mult: 0
  92.     decay_mult: 0
  93.   }
  94.   param {
  95.     lr_mult: 0
  96.     decay_mult: 0
  97.   }
  98.   param {
  99.     lr_mult: 0
  100.     decay_mult: 0
  101.   }
  102. }
  103. layer {
  104.   name: "conv1_scale"
  105.   bottom: "conv1"
  106.   top: "conv1"
  107.   type: "Scale"
  108.   scale_param {
  109.     filler {
  110.       value: 1
  111.     }
  112.     bias_term: true
  113.     bias_filler {
  114.       value: 0
  115.     }
  116.   }
  117. }
  118. layer {
  119.   name: "conv1_relu"
  120.   type: "ReLU"
  121.   bottom: "conv1"
  122.   top: "conv1"
  123. }
  124.  
  125.  
  126. layer {
  127.   name: "conv2"
  128.   type: "Convolution"
  129.   bottom: "conv1"
  130.   top: "conv2"
  131.   convolution_param {
  132.     num_output: 48
  133.     pad: 1
  134.     kernel_size: 3
  135.     stride: 2
  136.     bias_term: false
  137.     weight_filler {
  138.       type: "msra"
  139.     }
  140.   }
  141. }
  142. layer {
  143.   name: "conv2_bn"
  144.   type: "BatchNorm"
  145.   bottom: "conv2"
  146.   top: "conv2"
  147.   param {
  148.     lr_mult: 0
  149.     decay_mult: 0
  150.   }
  151.   param {
  152.     lr_mult: 0
  153.     decay_mult: 0
  154.   }
  155.   param {
  156.     lr_mult: 0
  157.     decay_mult: 0
  158.   }
  159. }
  160. layer {
  161.   name: "conv2_scale"
  162.   bottom: "conv2"
  163.   top: "conv2"
  164.   type: "Scale"
  165.   scale_param {
  166.     filler {
  167.       value: 1
  168.     }
  169.     bias_term: true
  170.     bias_filler {
  171.       value: 0
  172.     }
  173.   }
  174. }
  175. layer {
  176.   name: "conv2_relu"
  177.   type: "ReLU"
  178.   bottom: "conv2"
  179.   top: "conv2"
  180. }
  181.  
  182. layer {
  183.   name: "branch1_1_conv1"
  184.   type: "ConvolutionDepthwise"
  185.   bottom: "conv2"
  186.   top: "branch1_1_conv1"
  187.   convolution_param {
  188.     num_output: 48
  189.     kernel_size: 3
  190.     stride: 2
  191.     pad: 1
  192.     bias_term: false
  193.     weight_filler {
  194.       type: "msra"
  195.     }
  196.   }
  197. }
  198. layer {
  199.   name: "branch1_1_conv1_bn"
  200.   type: "BatchNorm"
  201.   bottom: "branch1_1_conv1"
  202.   top: "branch1_1_conv1"
  203.   param {
  204.     lr_mult: 0
  205.     decay_mult: 0
  206.   }
  207.   param {
  208.     lr_mult: 0
  209.     decay_mult: 0
  210.   }
  211.   param {
  212.     lr_mult: 0
  213.     decay_mult: 0
  214.   }
  215. }
  216. layer {
  217.   name: "branch1_1_conv1_scale"
  218.   bottom: "branch1_1_conv1"
  219.   top: "branch1_1_conv1"
  220.   type: "Scale"
  221.   scale_param {
  222.     filler {
  223.       value: 1
  224.     }
  225.     bias_term: true
  226.     bias_filler {
  227.       value: 0
  228.     }
  229.   }
  230. }
  231. layer {
  232.   name: "branch1_1_conv2"
  233.   type: "Convolution"
  234.   bottom: "branch1_1_conv1"
  235.   top: "branch1_1_conv2"
  236.   convolution_param {
  237.     num_output: 64
  238.     kernel_size: 1
  239.     stride: 1
  240.     pad: 0
  241.     bias_term: false
  242.     weight_filler {
  243.       type: "msra"
  244.     }
  245.   }
  246. }
  247. layer {
  248.   name: "branch1_1_conv2_bn"
  249.   type: "BatchNorm"
  250.   bottom: "branch1_1_conv2"
  251.   top: "branch1_1_conv2"
  252.   param {
  253.     lr_mult: 0
  254.     decay_mult: 0
  255.   }
  256.   param {
  257.     lr_mult: 0
  258.     decay_mult: 0
  259.   }
  260.   param {
  261.     lr_mult: 0
  262.     decay_mult: 0
  263.   }
  264. }
  265. layer {
  266.   name: "branch1_1_conv2_scale"
  267.   bottom: "branch1_1_conv2"
  268.   top: "branch1_1_conv2"
  269.   type: "Scale"
  270.   scale_param {
  271.     filler {
  272.       value: 1
  273.     }
  274.     bias_term: true
  275.     bias_filler {
  276.       value: 0
  277.     }
  278.   }
  279. }
  280. layer {
  281.   name: "branch1_1_conv2_relu"
  282.   type: "ReLU"
  283.   bottom: "branch1_1_conv2"
  284.   top: "branch1_1_conv2"
  285. }
  286. layer {
  287.   name: "branch1_2_conv1"
  288.   type: "Convolution"
  289.   bottom: "conv2"
  290.   top: "branch1_2_conv1"
  291.   convolution_param {
  292.     num_output: 64
  293.     kernel_size: 1
  294.     stride: 1
  295.     pad: 0
  296.     bias_term: false
  297.     weight_filler {
  298.       type: "msra"
  299.     }
  300.   }
  301. }
  302. layer {
  303.   name: "branch1_2_conv1_bn"
  304.   type: "BatchNorm"
  305.   bottom: "branch1_2_conv1"
  306.   top: "branch1_2_conv1"
  307.   param {
  308.     lr_mult: 0
  309.     decay_mult: 0
  310.   }
  311.   param {
  312.     lr_mult: 0
  313.     decay_mult: 0
  314.   }
  315.   param {
  316.     lr_mult: 0
  317.     decay_mult: 0
  318.   }
  319. }
  320. layer {
  321.   name: "branch1_2_conv1_scale"
  322.   bottom: "branch1_2_conv1"
  323.   top: "branch1_2_conv1"
  324.   type: "Scale"
  325.   scale_param {
  326.     filler {
  327.       value: 1
  328.     }
  329.     bias_term: true
  330.     bias_filler {
  331.       value: 0
  332.     }
  333.   }
  334. }
  335. layer {
  336.   name: "branch1_2_conv1_relu"
  337.   type: "ReLU"
  338.   bottom: "branch1_2_conv1"
  339.   top: "branch1_2_conv1"
  340. }
  341. layer {
  342.   name: "branch1_2_conv2"
  343.   type: "ConvolutionDepthwise"
  344.   bottom: "branch1_2_conv1"
  345.   top: "branch1_2_conv2"
  346.   convolution_param {
  347.     num_output: 64
  348.     kernel_size: 3
  349.     stride: 2
  350.     pad: 1
  351.     bias_term: false
  352.     weight_filler {
  353.       type: "msra"
  354.     }
  355.   }
  356. }
  357. layer {
  358.   name: "branch1_2_conv2_bn"
  359.   type: "BatchNorm"
  360.   bottom: "branch1_2_conv2"
  361.   top: "branch1_2_conv2"
  362.   param {
  363.     lr_mult: 0
  364.     decay_mult: 0
  365.   }
  366.   param {
  367.     lr_mult: 0
  368.     decay_mult: 0
  369.   }
  370.   param {
  371.     lr_mult: 0
  372.     decay_mult: 0
  373.   }
  374. }
  375. layer {
  376.   name: "branch1_2_conv2_scale"
  377.   bottom: "branch1_2_conv2"
  378.   top: "branch1_2_conv2"
  379.   type: "Scale"
  380.   scale_param {
  381.     filler {
  382.       value: 1
  383.     }
  384.     bias_term: true
  385.     bias_filler {
  386.       value: 0
  387.     }
  388.   }
  389. }
  390. layer {
  391.   name: "branch1_2_conv3"
  392.   type: "Convolution"
  393.   bottom: "branch1_2_conv2"
  394.   top: "branch1_2_conv3"
  395.   convolution_param {
  396.     num_output: 64
  397.     kernel_size: 1
  398.     stride: 1
  399.     pad: 0
  400.     bias_term: false
  401.     weight_filler {
  402.       type: "msra"
  403.     }
  404.   }
  405. }
  406. layer {
  407.   name: "branch1_2_conv3_bn"
  408.   type: "BatchNorm"
  409.   bottom: "branch1_2_conv3"
  410.   top: "branch1_2_conv3"
  411.   param {
  412.     lr_mult: 0
  413.     decay_mult: 0
  414.   }
  415.   param {
  416.     lr_mult: 0
  417.     decay_mult: 0
  418.   }
  419.   param {
  420.     lr_mult: 0
  421.     decay_mult: 0
  422.   }
  423. }
  424. layer {
  425.   name: "branch1_2_conv3_scale"
  426.   bottom: "branch1_2_conv3"
  427.   top: "branch1_2_conv3"
  428.   type: "Scale"
  429.   scale_param {
  430.     filler {
  431.       value: 1
  432.     }
  433.     bias_term: true
  434.     bias_filler {
  435.       value: 0
  436.     }
  437.   }
  438. }
  439. layer {
  440.   name: "branch1_2_conv3_relu"
  441.   type: "ReLU"
  442.   bottom: "branch1_2_conv3"
  443.   top: "branch1_2_conv3"
  444. }
  445. layer {
  446.   name: "concat1"
  447.   type: "Concat"
  448.   bottom: "branch1_1_conv2"
  449.   bottom: "branch1_2_conv3"
  450.   top: "concat1"
  451. }
  452. layer {
  453.   name: "shuffle1"
  454.   type: "ShuffleChannel"
  455.   bottom: "concat1"
  456.   top: "shuffle1"
  457.   shuffle_channel_param {
  458.     group: 2
  459.   }
  460. }
  461. layer {
  462.   name: "slice2"
  463.   type: "Slice"
  464.   bottom: "shuffle1"
  465.   top: "branch2_1"
  466.   top: "branch2_2"
  467.   slice_param {
  468.     slice_point: 64
  469.     axis: 1
  470.   }
  471. }
  472. layer {
  473.   name: "branch2_2_conv1"
  474.   type: "Convolution"
  475.   bottom: "branch2_2"
  476.   top: "branch2_2_conv1"
  477.   convolution_param {
  478.     num_output: 64
  479.     kernel_size: 1
  480.     stride: 1
  481.     pad: 0
  482.     bias_term: false
  483.     weight_filler {
  484.       type: "msra"
  485.     }
  486.   }
  487. }
  488. layer {
  489.   name: "branch2_2_conv1_bn"
  490.   type: "BatchNorm"
  491.   bottom: "branch2_2_conv1"
  492.   top: "branch2_2_conv1"
  493.   param {
  494.     lr_mult: 0
  495.     decay_mult: 0
  496.   }
  497.   param {
  498.     lr_mult: 0
  499.     decay_mult: 0
  500.   }
  501.   param {
  502.     lr_mult: 0
  503.     decay_mult: 0
  504.   }
  505. }
  506. layer {
  507.   name: "branch2_2_conv1_scale"
  508.   bottom: "branch2_2_conv1"
  509.   top: "branch2_2_conv1"
  510.   type: "Scale"
  511.   scale_param {
  512.     filler {
  513.       value: 1
  514.     }
  515.     bias_term: true
  516.     bias_filler {
  517.       value: 0
  518.     }
  519.   }
  520. }
  521. layer {
  522.   name: "branch2_2_conv1_relu"
  523.   type: "ReLU"
  524.   bottom: "branch2_2_conv1"
  525.   top: "branch2_2_conv1"
  526. }
  527. layer {
  528.   name: "branch2_2_conv2"
  529.   type: "ConvolutionDepthwise"
  530.   bottom: "branch2_2_conv1"
  531.   top: "branch2_2_conv2"
  532.   convolution_param {
  533.     num_output: 64
  534.     kernel_size: 3
  535.     stride: 1
  536.     pad: 1
  537.     bias_term: false
  538.     weight_filler {
  539.       type: "msra"
  540.     }
  541.   }
  542. }
  543. layer {
  544.   name: "branch2_2_conv2_bn"
  545.   type: "BatchNorm"
  546.   bottom: "branch2_2_conv2"
  547.   top: "branch2_2_conv2"
  548.   param {
  549.     lr_mult: 0
  550.     decay_mult: 0
  551.   }
  552.   param {
  553.     lr_mult: 0
  554.     decay_mult: 0
  555.   }
  556.   param {
  557.     lr_mult: 0
  558.     decay_mult: 0
  559.   }
  560. }
  561. layer {
  562.   name: "branch2_2_conv2_scale"
  563.   bottom: "branch2_2_conv2"
  564.   top: "branch2_2_conv2"
  565.   type: "Scale"
  566.   scale_param {
  567.     filler {
  568.       value: 1
  569.     }
  570.     bias_term: true
  571.     bias_filler {
  572.       value: 0
  573.     }
  574.   }
  575. }
  576. layer {
  577.   name: "branch2_2_conv3"
  578.   type: "Convolution"
  579.   bottom: "branch2_2_conv2"
  580.   top: "branch2_2_conv3"
  581.   convolution_param {
  582.     num_output: 64
  583.     kernel_size: 1
  584.     stride: 1
  585.     pad: 0
  586.     bias_term: false
  587.     weight_filler {
  588.       type: "msra"
  589.     }
  590.   }
  591. }
  592. layer {
  593.   name: "branch2_2_conv3_bn"
  594.   type: "BatchNorm"
  595.   bottom: "branch2_2_conv3"
  596.   top: "branch2_2_conv3"
  597.   param {
  598.     lr_mult: 0
  599.     decay_mult: 0
  600.   }
  601.   param {
  602.     lr_mult: 0
  603.     decay_mult: 0
  604.   }
  605.   param {
  606.     lr_mult: 0
  607.     decay_mult: 0
  608.   }
  609. }
  610. layer {
  611.   name: "branch2_2_conv3_scale"
  612.   bottom: "branch2_2_conv3"
  613.   top: "branch2_2_conv3"
  614.   type: "Scale"
  615.   scale_param {
  616.     filler {
  617.       value: 1
  618.     }
  619.     bias_term: true
  620.     bias_filler {
  621.       value: 0
  622.     }
  623.   }
  624. }
  625. layer {
  626.   name: "branch2_2_conv3_relu"
  627.   type: "ReLU"
  628.   bottom: "branch2_2_conv3"
  629.   top: "branch2_2_conv3"
  630. }
  631. layer {
  632.   name: "concat2"
  633.   type: "Concat"
  634.   bottom: "branch2_1"
  635.   bottom: "branch2_2_conv3"
  636.   top: "concat2"
  637. }
  638. layer {
  639.   name: "shuffle2"
  640.   type: "ShuffleChannel"
  641.   bottom: "concat2"
  642.   top: "shuffle2"
  643.   shuffle_channel_param {
  644.     group: 2
  645.   }
  646. }
  647. layer {
  648.   name: "slice3"
  649.   type: "Slice"
  650.   bottom: "shuffle2"
  651.   top: "branch3_1"
  652.   top: "branch3_2"
  653.   slice_param {
  654.     slice_point: 64
  655.     axis: 1
  656.   }
  657. }
  658. layer {
  659.   name: "branch3_2_conv1"
  660.   type: "Convolution"
  661.   bottom: "branch3_2"
  662.   top: "branch3_2_conv1"
  663.   convolution_param {
  664.     num_output: 64
  665.     kernel_size: 1
  666.     stride: 1
  667.     pad: 0
  668.     bias_term: false
  669.     weight_filler {
  670.       type: "msra"
  671.     }
  672.   }
  673. }
  674. layer {
  675.   name: "branch3_2_conv1_bn"
  676.   type: "BatchNorm"
  677.   bottom: "branch3_2_conv1"
  678.   top: "branch3_2_conv1"
  679.   param {
  680.     lr_mult: 0
  681.     decay_mult: 0
  682.   }
  683.   param {
  684.     lr_mult: 0
  685.     decay_mult: 0
  686.   }
  687.   param {
  688.     lr_mult: 0
  689.     decay_mult: 0
  690.   }
  691. }
  692. layer {
  693.   name: "branch3_2_conv1_scale"
  694.   bottom: "branch3_2_conv1"
  695.   top: "branch3_2_conv1"
  696.   type: "Scale"
  697.   scale_param {
  698.     filler {
  699.       value: 1
  700.     }
  701.     bias_term: true
  702.     bias_filler {
  703.       value: 0
  704.     }
  705.   }
  706. }
  707. layer {
  708.   name: "branch3_2_conv1_relu"
  709.   type: "ReLU"
  710.   bottom: "branch3_2_conv1"
  711.   top: "branch3_2_conv1"
  712. }
  713. layer {
  714.   name: "branch3_2_conv2"
  715.   type: "ConvolutionDepthwise"
  716.   bottom: "branch3_2_conv1"
  717.   top: "branch3_2_conv2"
  718.   convolution_param {
  719.     num_output: 64
  720.     kernel_size: 3
  721.     stride: 1
  722.     pad: 1
  723.     bias_term: false
  724.     weight_filler {
  725.       type: "msra"
  726.     }
  727.   }
  728. }
  729. layer {
  730.   name: "branch3_2_conv2_bn"
  731.   type: "BatchNorm"
  732.   bottom: "branch3_2_conv2"
  733.   top: "branch3_2_conv2"
  734.   param {
  735.     lr_mult: 0
  736.     decay_mult: 0
  737.   }
  738.   param {
  739.     lr_mult: 0
  740.     decay_mult: 0
  741.   }
  742.   param {
  743.     lr_mult: 0
  744.     decay_mult: 0
  745.   }
  746. }
  747. layer {
  748.   name: "branch3_2_conv2_scale"
  749.   bottom: "branch3_2_conv2"
  750.   top: "branch3_2_conv2"
  751.   type: "Scale"
  752.   scale_param {
  753.     filler {
  754.       value: 1
  755.     }
  756.     bias_term: true
  757.     bias_filler {
  758.       value: 0
  759.     }
  760.   }
  761. }
  762. layer {
  763.   name: "branch3_2_conv3"
  764.   type: "Convolution"
  765.   bottom: "branch3_2_conv2"
  766.   top: "branch3_2_conv3"
  767.   convolution_param {
  768.     num_output: 64
  769.     kernel_size: 1
  770.     stride: 1
  771.     pad: 0
  772.     bias_term: false
  773.     weight_filler {
  774.       type: "msra"
  775.     }
  776.   }
  777. }
  778. layer {
  779.   name: "branch3_2_conv3_bn"
  780.   type: "BatchNorm"
  781.   bottom: "branch3_2_conv3"
  782.   top: "branch3_2_conv3"
  783.   param {
  784.     lr_mult: 0
  785.     decay_mult: 0
  786.   }
  787.   param {
  788.     lr_mult: 0
  789.     decay_mult: 0
  790.   }
  791.   param {
  792.     lr_mult: 0
  793.     decay_mult: 0
  794.   }
  795. }
  796. layer {
  797.   name: "branch3_2_conv3_scale"
  798.   bottom: "branch3_2_conv3"
  799.   top: "branch3_2_conv3"
  800.   type: "Scale"
  801.   scale_param {
  802.     filler {
  803.       value: 1
  804.     }
  805.     bias_term: true
  806.     bias_filler {
  807.       value: 0
  808.     }
  809.   }
  810. }
  811. layer {
  812.   name: "branch3_2_conv3_relu"
  813.   type: "ReLU"
  814.   bottom: "branch3_2_conv3"
  815.   top: "branch3_2_conv3"
  816. }
  817. layer {
  818.   name: "concat3"
  819.   type: "Concat"
  820.   bottom: "branch3_1"
  821.   bottom: "branch3_2_conv3"
  822.   top: "concat3"
  823. }
  824.  
  825. layer {
  826.   name: "shuffle3"
  827.   type: "ShuffleChannel"
  828.   bottom: "concat3"
  829.   top: "shuffle3"
  830.   shuffle_channel_param {
  831.     group: 2
  832.   }
  833. }
  834. layer {
  835.   name: "slice4"
  836.   type: "Slice"
  837.   bottom: "shuffle3"
  838.   top: "branch4_1"
  839.   top: "branch4_2"
  840.   slice_param {
  841.     slice_point: 64
  842.     axis: 1
  843.   }
  844. }
  845. layer {
  846.   name: "branch4_2_conv1"
  847.   type: "Convolution"
  848.   bottom: "branch4_2"
  849.   top: "branch4_2_conv1"
  850.   convolution_param {
  851.     num_output: 64
  852.     kernel_size: 1
  853.     stride: 1
  854.     pad: 0
  855.     bias_term: false
  856.     weight_filler {
  857.       type: "msra"
  858.     }
  859.   }
  860. }
  861. layer {
  862.   name: "branch4_2_conv1_bn"
  863.   type: "BatchNorm"
  864.   bottom: "branch4_2_conv1"
  865.   top: "branch4_2_conv1"
  866.   param {
  867.     lr_mult: 0
  868.     decay_mult: 0
  869.   }
  870.   param {
  871.     lr_mult: 0
  872.     decay_mult: 0
  873.   }
  874.   param {
  875.     lr_mult: 0
  876.     decay_mult: 0
  877.   }
  878. }
  879. layer {
  880.   name: "branch4_2_conv1_scale"
  881.   bottom: "branch4_2_conv1"
  882.   top: "branch4_2_conv1"
  883.   type: "Scale"
  884.   scale_param {
  885.     filler {
  886.       value: 1
  887.     }
  888.     bias_term: true
  889.     bias_filler {
  890.       value: 0
  891.     }
  892.   }
  893. }
  894. layer {
  895.   name: "branch4_2_conv1_relu"
  896.   type: "ReLU"
  897.   bottom: "branch4_2_conv1"
  898.   top: "branch4_2_conv1"
  899. }
  900. layer {
  901.   name: "branch4_2_conv2"
  902.   type: "ConvolutionDepthwise"
  903.   bottom: "branch4_2_conv1"
  904.   top: "branch4_2_conv2"
  905.   convolution_param {
  906.     num_output: 64
  907.     kernel_size: 3
  908.     stride: 1
  909.     pad: 1
  910.     bias_term: false
  911.     weight_filler {
  912.       type: "msra"
  913.     }
  914.   }
  915. }
  916. layer {
  917.   name: "branch4_2_conv2_bn"
  918.   type: "BatchNorm"
  919.   bottom: "branch4_2_conv2"
  920.   top: "branch4_2_conv2"
  921.   param {
  922.     lr_mult: 0
  923.     decay_mult: 0
  924.   }
  925.   param {
  926.     lr_mult: 0
  927.     decay_mult: 0
  928.   }
  929.   param {
  930.     lr_mult: 0
  931.     decay_mult: 0
  932.   }
  933. }
  934. layer {
  935.   name: "branch4_2_conv2_scale"
  936.   bottom: "branch4_2_conv2"
  937.   top: "branch4_2_conv2"
  938.   type: "Scale"
  939.   scale_param {
  940.     filler {
  941.       value: 1
  942.     }
  943.     bias_term: true
  944.     bias_filler {
  945.       value: 0
  946.     }
  947.   }
  948. }
  949. layer {
  950.   name: "branch4_2_conv3"
  951.   type: "Convolution"
  952.   bottom: "branch4_2_conv2"
  953.   top: "branch4_2_conv3"
  954.   convolution_param {
  955.     num_output: 64
  956.     kernel_size: 1
  957.     stride: 1
  958.     pad: 0
  959.     bias_term: false
  960.     weight_filler {
  961.       type: "msra"
  962.     }
  963.   }
  964. }
  965. layer {
  966.   name: "branch4_2_conv3_bn"
  967.   type: "BatchNorm"
  968.   bottom: "branch4_2_conv3"
  969.   top: "branch4_2_conv3"
  970.   param {
  971.     lr_mult: 0
  972.     decay_mult: 0
  973.   }
  974.   param {
  975.     lr_mult: 0
  976.     decay_mult: 0
  977.   }
  978.   param {
  979.     lr_mult: 0
  980.     decay_mult: 0
  981.   }
  982. }
  983. layer {
  984.   name: "branch4_2_conv3_scale"
  985.   bottom: "branch4_2_conv3"
  986.   top: "branch4_2_conv3"
  987.   type: "Scale"
  988.   scale_param {
  989.     filler {
  990.       value: 1
  991.     }
  992.     bias_term: true
  993.     bias_filler {
  994.       value: 0
  995.     }
  996.   }
  997. }
  998. layer {
  999.   name: "branch4_2_conv3_relu"
  1000.   type: "ReLU"
  1001.   bottom: "branch4_2_conv3"
  1002.   top: "branch4_2_conv3"
  1003. }
  1004. layer {
  1005.   name: "concat4"
  1006.   type: "Concat"
  1007.   bottom: "branch4_1"
  1008.   bottom: "branch4_2_conv3"
  1009.   top: "concat4"
  1010. }
  1011. layer {
  1012.   name: "shuffle4"
  1013.   type: "ShuffleChannel"
  1014.   bottom: "concat4"
  1015.   top: "shuffle4"
  1016.   shuffle_channel_param {
  1017.     group: 2
  1018.   }
  1019. }
  1020.  
  1021. layer {
  1022.   name: "age/conv_4_1_pw"
  1023.   type: "Convolution"
  1024.   bottom: "shuffle4"
  1025.   top: "age/conv_4_1_pw"
  1026.   param {
  1027.     lr_mult: 1.0
  1028.     decay_mult: 1.0
  1029.   }
  1030.   convolution_param {
  1031.     num_output: 192
  1032.     bias_term: false
  1033.     pad: 0
  1034.     kernel_size: 1
  1035.     stride: 1
  1036.     weight_filler {
  1037.       type: "msra"
  1038.     }
  1039.     bias_filler {
  1040.       type: "constant"
  1041.       value: 0.0
  1042.     }
  1043.   }
  1044. }
  1045. layer {
  1046.   name: "age/bn_4_1_pw"
  1047.   type: "BatchNorm"
  1048.   bottom: "age/conv_4_1_pw"
  1049.   top: "age/conv_4_1_pw"
  1050.   param {
  1051.     lr_mult: 0.0
  1052.     decay_mult: 0.0
  1053.   }
  1054.   param {
  1055.     lr_mult: 0.0
  1056.     decay_mult: 0.0
  1057.   }
  1058.   param {
  1059.     lr_mult: 0.0
  1060.     decay_mult: 0.0
  1061.   }
  1062. }
  1063. layer {
  1064.   name: "age/scale_4_1_pw"
  1065.   type: "Scale"
  1066.   bottom: "age/conv_4_1_pw"
  1067.   top: "age/conv_4_1_pw"
  1068.   scale_param {
  1069.     bias_term: true
  1070.   }
  1071. }
  1072. layer {
  1073.   name: "age/relu_4_1_pw"
  1074.   type: "ReLU"
  1075.   bottom: "age/conv_4_1_pw"
  1076.   top: "age/conv_4_1_pw"
  1077. }
  1078. layer {
  1079.   name: "age/conv_4_1_dw"
  1080.   type: "ConvolutionDepthwise"
  1081.   bottom: "age/conv_4_1_pw"
  1082.   top: "age/conv_4_1_dw"
  1083.   param {
  1084.     lr_mult: 1.0
  1085.     decay_mult: 1.0
  1086.   }
  1087.   convolution_param {
  1088.     num_output: 192
  1089.     bias_term: false
  1090.     pad: 1
  1091.     kernel_size: 3
  1092.     stride: 2
  1093.     weight_filler {
  1094.       type: "msra"
  1095.     }
  1096.     bias_filler {
  1097.       type: "constant"
  1098.       value: 0.0
  1099.     }
  1100.   }
  1101. }
  1102. layer {
  1103.   name: "age/bn_4_1_dw"
  1104.   type: "BatchNorm"
  1105.   bottom: "age/conv_4_1_dw"
  1106.   top: "age/conv_4_1_dw"
  1107.   param {
  1108.     lr_mult: 0.0
  1109.     decay_mult: 0.0
  1110.   }
  1111.   param {
  1112.     lr_mult: 0.0
  1113.     decay_mult: 0.0
  1114.   }
  1115.   param {
  1116.     lr_mult: 0.0
  1117.     decay_mult: 0.0
  1118.   }
  1119. }
  1120. layer {
  1121.   name: "age/scale_4_1_dw"
  1122.   type: "Scale"
  1123.   bottom: "age/conv_4_1_dw"
  1124.   top: "age/conv_4_1_dw"
  1125.   scale_param {
  1126.     bias_term: true
  1127.   }
  1128. }
  1129. layer {
  1130.   name: "age/relu_4_1_dw"
  1131.   type: "ReLU"
  1132.   bottom: "age/conv_4_1_dw"
  1133.   top: "age/conv_4_1_dw"
  1134. }
  1135. layer {
  1136.   name: "age/conv_4_1_linear"
  1137.   type: "Convolution"
  1138.   bottom: "age/conv_4_1_dw"
  1139.   top: "age/conv_4_1_linear"
  1140.   param {
  1141.     lr_mult: 1.0
  1142.     decay_mult: 1.0
  1143.   }
  1144.   convolution_param {
  1145.     num_output: 96
  1146.     bias_term: false
  1147.     pad: 0
  1148.     kernel_size: 1
  1149.     stride: 1
  1150.     weight_filler {
  1151.       type: "msra"
  1152.     }
  1153.     bias_filler {
  1154.       type: "constant"
  1155.       value: 0.0
  1156.     }
  1157.   }
  1158. }
  1159. layer {
  1160.   name: "age/bn_4_1_linear"
  1161.   type: "BatchNorm"
  1162.   bottom: "age/conv_4_1_linear"
  1163.   top: "age/conv_4_1_linear"
  1164.   param {
  1165.     lr_mult: 0.0
  1166.     decay_mult: 0.0
  1167.   }
  1168.   param {
  1169.     lr_mult: 0.0
  1170.     decay_mult: 0.0
  1171.   }
  1172.   param {
  1173.     lr_mult: 0.0
  1174.     decay_mult: 0.0
  1175.   }
  1176. }
  1177. layer {
  1178.   name: "age/scale_4_1_linear"
  1179.   type: "Scale"
  1180.   bottom: "age/conv_4_1_linear"
  1181.   top: "age/conv_4_1_linear"
  1182.   scale_param {
  1183.     bias_term: true
  1184.   }
  1185. }
  1186. layer {
  1187.   name: "age/conv_4_2_pw"
  1188.   type: "Convolution"
  1189.   bottom: "age/conv_4_1_linear"
  1190.   top: "age/conv_4_2_pw"
  1191.   param {
  1192.     lr_mult: 1.0
  1193.     decay_mult: 1.0
  1194.   }
  1195.   convolution_param {
  1196.     num_output: 192
  1197.     bias_term: false
  1198.     pad: 0
  1199.     kernel_size: 1
  1200.     stride: 1
  1201.     weight_filler {
  1202.       type: "msra"
  1203.     }
  1204.     bias_filler {
  1205.       type: "constant"
  1206.       value: 0.0
  1207.     }
  1208.   }
  1209. }
  1210. layer {
  1211.   name: "age/bn_4_2_pw"
  1212.   type: "BatchNorm"
  1213.   bottom: "age/conv_4_2_pw"
  1214.   top: "age/conv_4_2_pw"
  1215.   param {
  1216.     lr_mult: 0.0
  1217.     decay_mult: 0.0
  1218.   }
  1219.   param {
  1220.     lr_mult: 0.0
  1221.     decay_mult: 0.0
  1222.   }
  1223.   param {
  1224.     lr_mult: 0.0
  1225.     decay_mult: 0.0
  1226.   }
  1227. }
  1228. layer {
  1229.   name: "age/scale_4_2_pw"
  1230.   type: "Scale"
  1231.   bottom: "age/conv_4_2_pw"
  1232.   top: "age/conv_4_2_pw"
  1233.   scale_param {
  1234.     bias_term: true
  1235.   }
  1236. }
  1237. layer {
  1238.   name: "age/relu_4_2_pw"
  1239.   type: "ReLU"
  1240.   bottom: "age/conv_4_2_pw"
  1241.   top: "age/conv_4_2_pw"
  1242. }
  1243. layer {
  1244.   name: "age/conv_4_2_dw"
  1245.   type: "ConvolutionDepthwise"
  1246.   bottom: "age/conv_4_2_pw"
  1247.   top: "age/conv_4_2_dw"
  1248.   param {
  1249.     lr_mult: 1.0
  1250.     decay_mult: 1.0
  1251.   }
  1252.   convolution_param {
  1253.     num_output: 192
  1254.     bias_term: false
  1255.     pad: 1
  1256.     kernel_size: 3
  1257.     stride: 1
  1258.     weight_filler {
  1259.       type: "msra"
  1260.     }
  1261.     bias_filler {
  1262.       type: "constant"
  1263.       value: 0.0
  1264.     }
  1265.   }
  1266. }
  1267. layer {
  1268.   name: "age/bn_4_2_dw"
  1269.   type: "BatchNorm"
  1270.   bottom: "age/conv_4_2_dw"
  1271.   top: "age/conv_4_2_dw"
  1272.   param {
  1273.     lr_mult: 0.0
  1274.     decay_mult: 0.0
  1275.   }
  1276.   param {
  1277.     lr_mult: 0.0
  1278.     decay_mult: 0.0
  1279.   }
  1280.   param {
  1281.     lr_mult: 0.0
  1282.     decay_mult: 0.0
  1283.   }
  1284. }
  1285. layer {
  1286.   name: "age/scale_4_2_dw"
  1287.   type: "Scale"
  1288.   bottom: "age/conv_4_2_dw"
  1289.   top: "age/conv_4_2_dw"
  1290.   scale_param {
  1291.     bias_term: true
  1292.   }
  1293. }
  1294. layer {
  1295.   name: "age/relu_4_2_dw"
  1296.   type: "ReLU"
  1297.   bottom: "age/conv_4_2_dw"
  1298.   top: "age/conv_4_2_dw"
  1299. }
  1300. layer {
  1301.   name: "age/conv_4_2_linear"
  1302.   type: "Convolution"
  1303.   bottom: "age/conv_4_2_dw"
  1304.   top: "age/conv_4_2_linear"
  1305.   param {
  1306.     lr_mult: 1.0
  1307.     decay_mult: 1.0
  1308.   }
  1309.   convolution_param {
  1310.     num_output: 96
  1311.     bias_term: false
  1312.     pad: 0
  1313.     kernel_size: 1
  1314.     stride: 1
  1315.     weight_filler {
  1316.       type: "msra"
  1317.     }
  1318.     bias_filler {
  1319.       type: "constant"
  1320.       value: 0.0
  1321.     }
  1322.   }
  1323. }
  1324. layer {
  1325.   name: "age/bn_4_2_linear"
  1326.   type: "BatchNorm"
  1327.   bottom: "age/conv_4_2_linear"
  1328.   top: "age/conv_4_2_linear"
  1329.   param {
  1330.     lr_mult: 0.0
  1331.     decay_mult: 0.0
  1332.   }
  1333.   param {
  1334.     lr_mult: 0.0
  1335.     decay_mult: 0.0
  1336.   }
  1337.   param {
  1338.     lr_mult: 0.0
  1339.     decay_mult: 0.0
  1340.   }
  1341. }
  1342. layer {
  1343.   name: "age/scale_4_2_linear"
  1344.   type: "Scale"
  1345.   bottom: "age/conv_4_2_linear"
  1346.   top: "age/conv_4_2_linear"
  1347.   scale_param {
  1348.     bias_term: true
  1349.   }
  1350. }
  1351. layer {
  1352.   name: "age/add_4_2"
  1353.   type: "Eltwise"
  1354.   bottom: "age/conv_4_1_linear"
  1355.   bottom: "age/conv_4_2_linear"
  1356.   top: "age/add_4_2"
  1357. }
  1358.  
  1359. layer {
  1360.   name: "age/ip1"
  1361.   type: "InnerProduct"
  1362.   bottom: "age/add_4_2"
  1363.   top: "age/ip1"
  1364.   param {
  1365.     lr_mult: 1
  1366.   }
  1367.   param {
  1368.     lr_mult: 2
  1369.   }
  1370.   inner_product_param {
  1371.     num_output: 96
  1372.     weight_filler {
  1373.       type: "xavier"
  1374.     }
  1375.     bias_filler {
  1376.       type: "constant"
  1377.     }
  1378.   }
  1379. }
  1380. layer {
  1381.   name: "age/ip2"
  1382.   type: "InnerProduct"
  1383.   bottom: "age/ip1"
  1384.   top: "age/ip2"
  1385.   param {
  1386.     lr_mult: 1
  1387.   }
  1388.   param {
  1389.     lr_mult: 2
  1390.   }
  1391.   inner_product_param {
  1392.     num_output: 1
  1393.     weight_filler {
  1394.       type: "xavier"
  1395.     }
  1396.     bias_filler {
  1397.       type: "constant"
  1398.     }
  1399.   }
  1400. }
  1401.  
  1402.  
  1403. layer {
  1404.   name: "emotion/conv_4_1_pw"
  1405.   type: "Convolution"
  1406.   bottom: "shuffle4"
  1407.   top: "emotion/conv_4_1_pw"
  1408.   param {
  1409.     lr_mult: 1.0
  1410.     decay_mult: 1.0
  1411.   }
  1412.   convolution_param {
  1413.     num_output: 192
  1414.     bias_term: false
  1415.     pad: 0
  1416.     kernel_size: 1
  1417.     stride: 1
  1418.     weight_filler {
  1419.       type: "msra"
  1420.     }
  1421.     bias_filler {
  1422.       type: "constant"
  1423.       value: 0.0
  1424.     }
  1425.   }
  1426. }
  1427. layer {
  1428.   name: "emotion/bn_4_1_pw"
  1429.   type: "BatchNorm"
  1430.   bottom: "emotion/conv_4_1_pw"
  1431.   top: "emotion/conv_4_1_pw"
  1432.   param {
  1433.     lr_mult: 0.0
  1434.     decay_mult: 0.0
  1435.   }
  1436.   param {
  1437.     lr_mult: 0.0
  1438.     decay_mult: 0.0
  1439.   }
  1440.   param {
  1441.     lr_mult: 0.0
  1442.     decay_mult: 0.0
  1443.   }
  1444. }
  1445. layer {
  1446.   name: "emotion/scale_4_1_pw"
  1447.   type: "Scale"
  1448.   bottom: "emotion/conv_4_1_pw"
  1449.   top: "emotion/conv_4_1_pw"
  1450.   scale_param {
  1451.     bias_term: true
  1452.   }
  1453. }
  1454. layer {
  1455.   name: "emotion/relu_4_1_pw"
  1456.   type: "ReLU"
  1457.   bottom: "emotion/conv_4_1_pw"
  1458.   top: "emotion/conv_4_1_pw"
  1459. }
  1460. layer {
  1461.   name: "emotion/conv_4_1_dw"
  1462.   type: "ConvolutionDepthwise"
  1463.   bottom: "emotion/conv_4_1_pw"
  1464.   top: "emotion/conv_4_1_dw"
  1465.   param {
  1466.     lr_mult: 1.0
  1467.     decay_mult: 1.0
  1468.   }
  1469.   convolution_param {
  1470.     num_output: 192
  1471.     bias_term: false
  1472.     pad: 1
  1473.     kernel_size: 3
  1474.     stride: 2
  1475.     weight_filler {
  1476.       type: "msra"
  1477.     }
  1478.     bias_filler {
  1479.       type: "constant"
  1480.       value: 0.0
  1481.     }
  1482.   }
  1483. }
  1484. layer {
  1485.   name: "emotion/bn_4_1_dw"
  1486.   type: "BatchNorm"
  1487.   bottom: "emotion/conv_4_1_dw"
  1488.   top: "emotion/conv_4_1_dw"
  1489.   param {
  1490.     lr_mult: 0.0
  1491.     decay_mult: 0.0
  1492.   }
  1493.   param {
  1494.     lr_mult: 0.0
  1495.     decay_mult: 0.0
  1496.   }
  1497.   param {
  1498.     lr_mult: 0.0
  1499.     decay_mult: 0.0
  1500.   }
  1501. }
  1502. layer {
  1503.   name: "emotion/scale_4_1_dw"
  1504.   type: "Scale"
  1505.   bottom: "emotion/conv_4_1_dw"
  1506.   top: "emotion/conv_4_1_dw"
  1507.   scale_param {
  1508.     bias_term: true
  1509.   }
  1510. }
  1511. layer {
  1512.   name: "emotion/relu_4_1_dw"
  1513.   type: "ReLU"
  1514.   bottom: "emotion/conv_4_1_dw"
  1515.   top: "emotion/conv_4_1_dw"
  1516. }
  1517. layer {
  1518.   name: "emotion/conv_4_1_linear"
  1519.   type: "Convolution"
  1520.   bottom: "emotion/conv_4_1_dw"
  1521.   top: "emotion/conv_4_1_linear"
  1522.   param {
  1523.     lr_mult: 1.0
  1524.     decay_mult: 1.0
  1525.   }
  1526.   convolution_param {
  1527.     num_output: 96
  1528.     bias_term: false
  1529.     pad: 0
  1530.     kernel_size: 1
  1531.     stride: 1
  1532.     weight_filler {
  1533.       type: "msra"
  1534.     }
  1535.     bias_filler {
  1536.       type: "constant"
  1537.       value: 0.0
  1538.     }
  1539.   }
  1540. }
  1541. layer {
  1542.   name: "emotion/bn_4_1_linear"
  1543.   type: "BatchNorm"
  1544.   bottom: "emotion/conv_4_1_linear"
  1545.   top: "emotion/conv_4_1_linear"
  1546.   param {
  1547.     lr_mult: 0.0
  1548.     decay_mult: 0.0
  1549.   }
  1550.   param {
  1551.     lr_mult: 0.0
  1552.     decay_mult: 0.0
  1553.   }
  1554.   param {
  1555.     lr_mult: 0.0
  1556.     decay_mult: 0.0
  1557.   }
  1558. }
  1559. layer {
  1560.   name: "emotion/scale_4_1_linear"
  1561.   type: "Scale"
  1562.   bottom: "emotion/conv_4_1_linear"
  1563.   top: "emotion/conv_4_1_linear"
  1564.   scale_param {
  1565.     bias_term: true
  1566.   }
  1567. }
  1568. layer {
  1569.   name: "emotion/conv_4_2_pw"
  1570.   type: "Convolution"
  1571.   bottom: "emotion/conv_4_1_linear"
  1572.   top: "emotion/conv_4_2_pw"
  1573.   param {
  1574.     lr_mult: 1.0
  1575.     decay_mult: 1.0
  1576.   }
  1577.   convolution_param {
  1578.     num_output: 192
  1579.     bias_term: false
  1580.     pad: 0
  1581.     kernel_size: 1
  1582.     stride: 1
  1583.     weight_filler {
  1584.       type: "msra"
  1585.     }
  1586.     bias_filler {
  1587.       type: "constant"
  1588.       value: 0.0
  1589.     }
  1590.   }
  1591. }
  1592. layer {
  1593.   name: "emotion/bn_4_2_pw"
  1594.   type: "BatchNorm"
  1595.   bottom: "emotion/conv_4_2_pw"
  1596.   top: "emotion/conv_4_2_pw"
  1597.   param {
  1598.     lr_mult: 0.0
  1599.     decay_mult: 0.0
  1600.   }
  1601.   param {
  1602.     lr_mult: 0.0
  1603.     decay_mult: 0.0
  1604.   }
  1605.   param {
  1606.     lr_mult: 0.0
  1607.     decay_mult: 0.0
  1608.   }
  1609. }
  1610. layer {
  1611.   name: "emotion/scale_4_2_pw"
  1612.   type: "Scale"
  1613.   bottom: "emotion/conv_4_2_pw"
  1614.   top: "emotion/conv_4_2_pw"
  1615.   scale_param {
  1616.     bias_term: true
  1617.   }
  1618. }
  1619. layer {
  1620.   name: "emotion/relu_4_2_pw"
  1621.   type: "ReLU"
  1622.   bottom: "emotion/conv_4_2_pw"
  1623.   top: "emotion/conv_4_2_pw"
  1624. }
  1625. layer {
  1626.   name: "emotion/conv_4_2_dw"
  1627.   type: "ConvolutionDepthwise"
  1628.   bottom: "emotion/conv_4_2_pw"
  1629.   top: "emotion/conv_4_2_dw"
  1630.   param {
  1631.     lr_mult: 1.0
  1632.     decay_mult: 1.0
  1633.   }
  1634.   convolution_param {
  1635.     num_output: 192
  1636.     bias_term: false
  1637.     pad: 1
  1638.     kernel_size: 3
  1639.     stride: 1
  1640.     weight_filler {
  1641.       type: "msra"
  1642.     }
  1643.     bias_filler {
  1644.       type: "constant"
  1645.       value: 0.0
  1646.     }
  1647.   }
  1648. }
  1649. layer {
  1650.   name: "emotion/bn_4_2_dw"
  1651.   type: "BatchNorm"
  1652.   bottom: "emotion/conv_4_2_dw"
  1653.   top: "emotion/conv_4_2_dw"
  1654.   param {
  1655.     lr_mult: 0.0
  1656.     decay_mult: 0.0
  1657.   }
  1658.   param {
  1659.     lr_mult: 0.0
  1660.     decay_mult: 0.0
  1661.   }
  1662.   param {
  1663.     lr_mult: 0.0
  1664.     decay_mult: 0.0
  1665.   }
  1666. }
  1667. layer {
  1668.   name: "emotion/scale_4_2_dw"
  1669.   type: "Scale"
  1670.   bottom: "emotion/conv_4_2_dw"
  1671.   top: "emotion/conv_4_2_dw"
  1672.   scale_param {
  1673.     bias_term: true
  1674.   }
  1675. }
  1676. layer {
  1677.   name: "emotion/relu_4_2_dw"
  1678.   type: "ReLU"
  1679.   bottom: "emotion/conv_4_2_dw"
  1680.   top: "emotion/conv_4_2_dw"
  1681. }
  1682. layer {
  1683.   name: "emotion/conv_4_2_linear"
  1684.   type: "Convolution"
  1685.   bottom: "emotion/conv_4_2_dw"
  1686.   top: "emotion/conv_4_2_linear"
  1687.   param {
  1688.     lr_mult: 1.0
  1689.     decay_mult: 1.0
  1690.   }
  1691.   convolution_param {
  1692.     num_output: 96
  1693.     bias_term: false
  1694.     pad: 0
  1695.     kernel_size: 1
  1696.     stride: 1
  1697.     weight_filler {
  1698.       type: "msra"
  1699.     }
  1700.     bias_filler {
  1701.       type: "constant"
  1702.       value: 0.0
  1703.     }
  1704.   }
  1705. }
  1706. layer {
  1707.   name: "emotion/bn_4_2_linear"
  1708.   type: "BatchNorm"
  1709.   bottom: "emotion/conv_4_2_linear"
  1710.   top: "emotion/conv_4_2_linear"
  1711.   param {
  1712.     lr_mult: 0.0
  1713.     decay_mult: 0.0
  1714.   }
  1715.   param {
  1716.     lr_mult: 0.0
  1717.     decay_mult: 0.0
  1718.   }
  1719.   param {
  1720.     lr_mult: 0.0
  1721.     decay_mult: 0.0
  1722.   }
  1723. }
  1724. layer {
  1725.   name: "emotion/scale_4_2_linear"
  1726.   type: "Scale"
  1727.   bottom: "emotion/conv_4_2_linear"
  1728.   top: "emotion/conv_4_2_linear"
  1729.   scale_param {
  1730.     bias_term: true
  1731.   }
  1732. }
  1733. layer {
  1734.   name: "emotion/add_4_2"
  1735.   type: "Eltwise"
  1736.   bottom: "emotion/conv_4_1_linear"
  1737.   bottom: "emotion/conv_4_2_linear"
  1738.   top: "emotion/add_4_2"
  1739. }
  1740.  
  1741. layer {
  1742.   name: "emotion/conv1_"
  1743.   type: "Convolution"
  1744.   bottom: "emotion/add_4_2"
  1745.   top: "emotion/conv1_"
  1746.   param {
  1747.     lr_mult: 1
  1748.     decay_mult: 1
  1749.   }
  1750.   param {
  1751.     lr_mult: 2
  1752.     decay_mult: 0
  1753.   }
  1754.   convolution_param {
  1755.     num_output: 128
  1756.     kernel_size: 3
  1757.     stride: 1
  1758.     weight_filler {
  1759.       type: "xavier"
  1760.     }
  1761.     bias_filler {
  1762.       type: "constant"
  1763.       value: 0
  1764.     }
  1765.   }
  1766. }
  1767. layer {
  1768.   name: "emotion/relu1_"
  1769.   type: "ReLU"
  1770.   bottom: "emotion/conv1_"
  1771.   top: "emotion/conv1_"
  1772. }
  1773. layer {
  1774.   name: "emotion/pool1_"
  1775.   type: "Pooling"
  1776.   bottom: "emotion/conv1_"
  1777.   top: "emotion/pool1_"
  1778.   pooling_param {
  1779.     pool: AVE
  1780.     kernel_size: 4
  1781.     stride: 4
  1782.   }
  1783. }
  1784. layer {
  1785.   name: "emotion/ip1"
  1786.   type: "InnerProduct"
  1787.   bottom: "emotion/pool1_"
  1788.   top: "emotion/ip1"
  1789.   param {
  1790.     lr_mult: 1
  1791.   }
  1792.   param {
  1793.     lr_mult: 2
  1794.   }
  1795.   inner_product_param {
  1796.     num_output: 3
  1797.     weight_filler {
  1798.       type: "xavier"
  1799.     }
  1800.     bias_filler {
  1801.       type: "constant"
  1802.     }
  1803.   }
  1804. }
  1805.  
  1806. layer {
  1807.   name: "sex/conv_4_1_pw"
  1808.   type: "Convolution"
  1809.   bottom: "shuffle4"
  1810.   top: "sex/conv_4_1_pw"
  1811.   param {
  1812.     lr_mult: 1.0
  1813.     decay_mult: 1.0
  1814.   }
  1815.   convolution_param {
  1816.     num_output: 192
  1817.     bias_term: false
  1818.     pad: 0
  1819.     kernel_size: 1
  1820.     stride: 1
  1821.     weight_filler {
  1822.       type: "msra"
  1823.     }
  1824.     bias_filler {
  1825.       type: "constant"
  1826.       value: 0.0
  1827.     }
  1828.   }
  1829. }
  1830. layer {
  1831.   name: "sex/bn_4_1_pw"
  1832.   type: "BatchNorm"
  1833.   bottom: "sex/conv_4_1_pw"
  1834.   top: "sex/conv_4_1_pw"
  1835.   param {
  1836.     lr_mult: 0.0
  1837.     decay_mult: 0.0
  1838.   }
  1839.   param {
  1840.     lr_mult: 0.0
  1841.     decay_mult: 0.0
  1842.   }
  1843.   param {
  1844.     lr_mult: 0.0
  1845.     decay_mult: 0.0
  1846.   }
  1847. }
  1848. layer {
  1849.   name: "sex/scale_4_1_pw"
  1850.   type: "Scale"
  1851.   bottom: "sex/conv_4_1_pw"
  1852.   top: "sex/conv_4_1_pw"
  1853.   scale_param {
  1854.     bias_term: true
  1855.   }
  1856. }
  1857. layer {
  1858.   name: "sex/relu_4_1_pw"
  1859.   type: "ReLU"
  1860.   bottom: "sex/conv_4_1_pw"
  1861.   top: "sex/conv_4_1_pw"
  1862. }
  1863. layer {
  1864.   name: "sex/conv_4_1_dw"
  1865.   type: "ConvolutionDepthwise"
  1866.   bottom: "sex/conv_4_1_pw"
  1867.   top: "sex/conv_4_1_dw"
  1868.   param {
  1869.     lr_mult: 1.0
  1870.     decay_mult: 1.0
  1871.   }
  1872.   convolution_param {
  1873.     num_output: 192
  1874.     bias_term: false
  1875.     pad: 1
  1876.     kernel_size: 3
  1877.     stride: 2
  1878.     weight_filler {
  1879.       type: "msra"
  1880.     }
  1881.     bias_filler {
  1882.       type: "constant"
  1883.       value: 0.0
  1884.     }
  1885.   }
  1886. }
  1887. layer {
  1888.   name: "sex/bn_4_1_dw"
  1889.   type: "BatchNorm"
  1890.   bottom: "sex/conv_4_1_dw"
  1891.   top: "sex/conv_4_1_dw"
  1892.   param {
  1893.     lr_mult: 0.0
  1894.     decay_mult: 0.0
  1895.   }
  1896.   param {
  1897.     lr_mult: 0.0
  1898.     decay_mult: 0.0
  1899.   }
  1900.   param {
  1901.     lr_mult: 0.0
  1902.     decay_mult: 0.0
  1903.   }
  1904. }
  1905. layer {
  1906.   name: "sex/scale_4_1_dw"
  1907.   type: "Scale"
  1908.   bottom: "sex/conv_4_1_dw"
  1909.   top: "sex/conv_4_1_dw"
  1910.   scale_param {
  1911.     bias_term: true
  1912.   }
  1913. }
  1914. layer {
  1915.   name: "sex/relu_4_1_dw"
  1916.   type: "ReLU"
  1917.   bottom: "sex/conv_4_1_dw"
  1918.   top: "sex/conv_4_1_dw"
  1919. }
  1920. layer {
  1921.   name: "sex/conv_4_1_linear"
  1922.   type: "Convolution"
  1923.   bottom: "sex/conv_4_1_dw"
  1924.   top: "sex/conv_4_1_linear"
  1925.   param {
  1926.     lr_mult: 1.0
  1927.     decay_mult: 1.0
  1928.   }
  1929.   convolution_param {
  1930.     num_output: 96
  1931.     bias_term: false
  1932.     pad: 0
  1933.     kernel_size: 1
  1934.     stride: 1
  1935.     weight_filler {
  1936.       type: "msra"
  1937.     }
  1938.     bias_filler {
  1939.       type: "constant"
  1940.       value: 0.0
  1941.     }
  1942.   }
  1943. }
  1944. layer {
  1945.   name: "sex/bn_4_1_linear"
  1946.   type: "BatchNorm"
  1947.   bottom: "sex/conv_4_1_linear"
  1948.   top: "sex/conv_4_1_linear"
  1949.   param {
  1950.     lr_mult: 0.0
  1951.     decay_mult: 0.0
  1952.   }
  1953.   param {
  1954.     lr_mult: 0.0
  1955.     decay_mult: 0.0
  1956.   }
  1957.   param {
  1958.     lr_mult: 0.0
  1959.     decay_mult: 0.0
  1960.   }
  1961. }
  1962. layer {
  1963.   name: "sex/scale_4_1_linear"
  1964.   type: "Scale"
  1965.   bottom: "sex/conv_4_1_linear"
  1966.   top: "sex/conv_4_1_linear"
  1967.   scale_param {
  1968.     bias_term: true
  1969.   }
  1970. }
  1971. layer {
  1972.   name: "sex/conv_4_2_pw"
  1973.   type: "Convolution"
  1974.   bottom: "sex/conv_4_1_linear"
  1975.   top: "sex/conv_4_2_pw"
  1976.   param {
  1977.     lr_mult: 1.0
  1978.     decay_mult: 1.0
  1979.   }
  1980.   convolution_param {
  1981.     num_output: 192
  1982.     bias_term: false
  1983.     pad: 0
  1984.     kernel_size: 1
  1985.     stride: 1
  1986.     weight_filler {
  1987.       type: "msra"
  1988.     }
  1989.     bias_filler {
  1990.       type: "constant"
  1991.       value: 0.0
  1992.     }
  1993.   }
  1994. }
  1995. layer {
  1996.   name: "sex/bn_4_2_pw"
  1997.   type: "BatchNorm"
  1998.   bottom: "sex/conv_4_2_pw"
  1999.   top: "sex/conv_4_2_pw"
  2000.   param {
  2001.     lr_mult: 0.0
  2002.     decay_mult: 0.0
  2003.   }
  2004.   param {
  2005.     lr_mult: 0.0
  2006.     decay_mult: 0.0
  2007.   }
  2008.   param {
  2009.     lr_mult: 0.0
  2010.     decay_mult: 0.0
  2011.   }
  2012. }
  2013. layer {
  2014.   name: "sex/scale_4_2_pw"
  2015.   type: "Scale"
  2016.   bottom: "sex/conv_4_2_pw"
  2017.   top: "sex/conv_4_2_pw"
  2018.   scale_param {
  2019.     bias_term: true
  2020.   }
  2021. }
  2022. layer {
  2023.   name: "sex/relu_4_2_pw"
  2024.   type: "ReLU"
  2025.   bottom: "sex/conv_4_2_pw"
  2026.   top: "sex/conv_4_2_pw"
  2027. }
  2028. layer {
  2029.   name: "sex/conv_4_2_dw"
  2030.   type: "ConvolutionDepthwise"
  2031.   bottom: "sex/conv_4_2_pw"
  2032.   top: "sex/conv_4_2_dw"
  2033.   param {
  2034.     lr_mult: 1.0
  2035.     decay_mult: 1.0
  2036.   }
  2037.   convolution_param {
  2038.     num_output: 192
  2039.     bias_term: false
  2040.     pad: 1
  2041.     kernel_size: 3
  2042.     stride: 1
  2043.     weight_filler {
  2044.       type: "msra"
  2045.     }
  2046.     bias_filler {
  2047.       type: "constant"
  2048.       value: 0.0
  2049.     }
  2050.   }
  2051. }
  2052. layer {
  2053.   name: "sex/bn_4_2_dw"
  2054.   type: "BatchNorm"
  2055.   bottom: "sex/conv_4_2_dw"
  2056.   top: "sex/conv_4_2_dw"
  2057.   param {
  2058.     lr_mult: 0.0
  2059.     decay_mult: 0.0
  2060.   }
  2061.   param {
  2062.     lr_mult: 0.0
  2063.     decay_mult: 0.0
  2064.   }
  2065.   param {
  2066.     lr_mult: 0.0
  2067.     decay_mult: 0.0
  2068.   }
  2069. }
  2070. layer {
  2071.   name: "sex/scale_4_2_dw"
  2072.   type: "Scale"
  2073.   bottom: "sex/conv_4_2_dw"
  2074.   top: "sex/conv_4_2_dw"
  2075.   scale_param {
  2076.     bias_term: true
  2077.   }
  2078. }
  2079. layer {
  2080.   name: "sex/relu_4_2_dw"
  2081.   type: "ReLU"
  2082.   bottom: "sex/conv_4_2_dw"
  2083.   top: "sex/conv_4_2_dw"
  2084. }
  2085. layer {
  2086.   name: "sex/conv_4_2_linear"
  2087.   type: "Convolution"
  2088.   bottom: "sex/conv_4_2_dw"
  2089.   top: "sex/conv_4_2_linear"
  2090.   param {
  2091.     lr_mult: 1.0
  2092.     decay_mult: 1.0
  2093.   }
  2094.   convolution_param {
  2095.     num_output: 96
  2096.     bias_term: false
  2097.     pad: 0
  2098.     kernel_size: 1
  2099.     stride: 1
  2100.     weight_filler {
  2101.       type: "msra"
  2102.     }
  2103.     bias_filler {
  2104.       type: "constant"
  2105.       value: 0.0
  2106.     }
  2107.   }
  2108. }
  2109. layer {
  2110.   name: "sex/bn_4_2_linear"
  2111.   type: "BatchNorm"
  2112.   bottom: "sex/conv_4_2_linear"
  2113.   top: "sex/conv_4_2_linear"
  2114.   param {
  2115.     lr_mult: 0.0
  2116.     decay_mult: 0.0
  2117.   }
  2118.   param {
  2119.     lr_mult: 0.0
  2120.     decay_mult: 0.0
  2121.   }
  2122.   param {
  2123.     lr_mult: 0.0
  2124.     decay_mult: 0.0
  2125.   }
  2126. }
  2127. layer {
  2128.   name: "sex/scale_4_2_linear"
  2129.   type: "Scale"
  2130.   bottom: "sex/conv_4_2_linear"
  2131.   top: "sex/conv_4_2_linear"
  2132.   scale_param {
  2133.     bias_term: true
  2134.   }
  2135. }
  2136. layer {
  2137.   name: "sex/add_4_2"
  2138.   type: "Eltwise"
  2139.   bottom: "sex/conv_4_1_linear"
  2140.   bottom: "sex/conv_4_2_linear"
  2141.   top: "sex/add_4_2"
  2142. }
  2143.  
  2144. layer {
  2145.   name: "sex/conv1_"
  2146.   type: "Convolution"
  2147.   bottom: "sex/add_4_2"
  2148.   top: "sex/conv1_"
  2149.   param {
  2150.     lr_mult: 1
  2151.     decay_mult: 1
  2152.   }
  2153.   param {
  2154.     lr_mult: 2
  2155.     decay_mult: 0
  2156.   }
  2157.   convolution_param {
  2158.     num_output: 128
  2159.     kernel_size: 3
  2160.     stride: 1
  2161.     weight_filler {
  2162.       type: "xavier"
  2163.     }
  2164.     bias_filler {
  2165.       type: "constant"
  2166.       value: 0
  2167.     }
  2168.   }
  2169. }
  2170. layer {
  2171.   name: "sex/relu1_"
  2172.   type: "ReLU"
  2173.   bottom: "sex/conv1_"
  2174.   top: "sex/conv1_"
  2175. }
  2176. layer {
  2177.   name: "sex/pool1_"
  2178.   type: "Pooling"
  2179.   bottom: "sex/conv1_"
  2180.   top: "sex/pool1_"
  2181.   pooling_param {
  2182.     pool: AVE
  2183.     kernel_size: 4
  2184.     stride: 4
  2185.   }
  2186. }
  2187. layer {
  2188.   name: "sex/ip1"
  2189.   type: "InnerProduct"
  2190.   bottom: "sex/pool1_"
  2191.   top: "sex/ip1"
  2192.   param {
  2193.     lr_mult: 1
  2194.   }
  2195.   param {
  2196.     lr_mult: 2
  2197.   }
  2198.   inner_product_param {
  2199.     num_output: 2
  2200.     weight_filler {
  2201.       type: "xavier"
  2202.     }
  2203.     bias_filler {
  2204.       type: "constant"
  2205.     }
  2206.   }
  2207. }
  2208.  
  2209.  
  2210. layer {
  2211.   name: "glass/conv_4_1_pw"
  2212.   type: "Convolution"
  2213.   bottom: "shuffle4"
  2214.   top: "glass/conv_4_1_pw"
  2215.   param {
  2216.     lr_mult: 1.0
  2217.     decay_mult: 1.0
  2218.   }
  2219.   convolution_param {
  2220.     num_output: 192
  2221.     bias_term: false
  2222.     pad: 0
  2223.     kernel_size: 1
  2224.     stride: 1
  2225.     weight_filler {
  2226.       type: "msra"
  2227.     }
  2228.     bias_filler {
  2229.       type: "constant"
  2230.       value: 0.0
  2231.     }
  2232.   }
  2233. }
  2234. layer {
  2235.   name: "glass/bn_4_1_pw"
  2236.   type: "BatchNorm"
  2237.   bottom: "glass/conv_4_1_pw"
  2238.   top: "glass/conv_4_1_pw"
  2239.   param {
  2240.     lr_mult: 0.0
  2241.     decay_mult: 0.0
  2242.   }
  2243.   param {
  2244.     lr_mult: 0.0
  2245.     decay_mult: 0.0
  2246.   }
  2247.   param {
  2248.     lr_mult: 0.0
  2249.     decay_mult: 0.0
  2250.   }
  2251. }
  2252. layer {
  2253.   name: "glass/scale_4_1_pw"
  2254.   type: "Scale"
  2255.   bottom: "glass/conv_4_1_pw"
  2256.   top: "glass/conv_4_1_pw"
  2257.   scale_param {
  2258.     bias_term: true
  2259.   }
  2260. }
  2261. layer {
  2262.   name: "glass/relu_4_1_pw"
  2263.   type: "ReLU"
  2264.   bottom: "glass/conv_4_1_pw"
  2265.   top: "glass/conv_4_1_pw"
  2266. }
  2267. layer {
  2268.   name: "glass/conv_4_1_dw"
  2269.   type: "ConvolutionDepthwise"
  2270.   bottom: "glass/conv_4_1_pw"
  2271.   top: "glass/conv_4_1_dw"
  2272.   param {
  2273.     lr_mult: 1.0
  2274.     decay_mult: 1.0
  2275.   }
  2276.   convolution_param {
  2277.     num_output: 192
  2278.     bias_term: false
  2279.     pad: 1
  2280.     kernel_size: 3
  2281.     stride: 2
  2282.     weight_filler {
  2283.       type: "msra"
  2284.     }
  2285.     bias_filler {
  2286.       type: "constant"
  2287.       value: 0.0
  2288.     }
  2289.   }
  2290. }
  2291. layer {
  2292.   name: "glass/bn_4_1_dw"
  2293.   type: "BatchNorm"
  2294.   bottom: "glass/conv_4_1_dw"
  2295.   top: "glass/conv_4_1_dw"
  2296.   param {
  2297.     lr_mult: 0.0
  2298.     decay_mult: 0.0
  2299.   }
  2300.   param {
  2301.     lr_mult: 0.0
  2302.     decay_mult: 0.0
  2303.   }
  2304.   param {
  2305.     lr_mult: 0.0
  2306.     decay_mult: 0.0
  2307.   }
  2308. }
  2309. layer {
  2310.   name: "glass/scale_4_1_dw"
  2311.   type: "Scale"
  2312.   bottom: "glass/conv_4_1_dw"
  2313.   top: "glass/conv_4_1_dw"
  2314.   scale_param {
  2315.     bias_term: true
  2316.   }
  2317. }
  2318. layer {
  2319.   name: "glass/relu_4_1_dw"
  2320.   type: "ReLU"
  2321.   bottom: "glass/conv_4_1_dw"
  2322.   top: "glass/conv_4_1_dw"
  2323. }
  2324. layer {
  2325.   name: "glass/conv_4_1_linear"
  2326.   type: "Convolution"
  2327.   bottom: "glass/conv_4_1_dw"
  2328.   top: "glass/conv_4_1_linear"
  2329.   param {
  2330.     lr_mult: 1.0
  2331.     decay_mult: 1.0
  2332.   }
  2333.   convolution_param {
  2334.     num_output: 96
  2335.     bias_term: false
  2336.     pad: 0
  2337.     kernel_size: 1
  2338.     stride: 1
  2339.     weight_filler {
  2340.       type: "msra"
  2341.     }
  2342.     bias_filler {
  2343.       type: "constant"
  2344.       value: 0.0
  2345.     }
  2346.   }
  2347. }
  2348. layer {
  2349.   name: "glass/bn_4_1_linear"
  2350.   type: "BatchNorm"
  2351.   bottom: "glass/conv_4_1_linear"
  2352.   top: "glass/conv_4_1_linear"
  2353.   param {
  2354.     lr_mult: 0.0
  2355.     decay_mult: 0.0
  2356.   }
  2357.   param {
  2358.     lr_mult: 0.0
  2359.     decay_mult: 0.0
  2360.   }
  2361.   param {
  2362.     lr_mult: 0.0
  2363.     decay_mult: 0.0
  2364.   }
  2365. }
  2366. layer {
  2367.   name: "glass/scale_4_1_linear"
  2368.   type: "Scale"
  2369.   bottom: "glass/conv_4_1_linear"
  2370.   top: "glass/conv_4_1_linear"
  2371.   scale_param {
  2372.     bias_term: true
  2373.   }
  2374. }
  2375. layer {
  2376.   name: "glass/conv_4_2_pw"
  2377.   type: "Convolution"
  2378.   bottom: "glass/conv_4_1_linear"
  2379.   top: "glass/conv_4_2_pw"
  2380.   param {
  2381.     lr_mult: 1.0
  2382.     decay_mult: 1.0
  2383.   }
  2384.   convolution_param {
  2385.     num_output: 192
  2386.     bias_term: false
  2387.     pad: 0
  2388.     kernel_size: 1
  2389.     stride: 1
  2390.     weight_filler {
  2391.       type: "msra"
  2392.     }
  2393.     bias_filler {
  2394.       type: "constant"
  2395.       value: 0.0
  2396.     }
  2397.   }
  2398. }
  2399. layer {
  2400.   name: "glass/bn_4_2_pw"
  2401.   type: "BatchNorm"
  2402.   bottom: "glass/conv_4_2_pw"
  2403.   top: "glass/conv_4_2_pw"
  2404.   param {
  2405.     lr_mult: 0.0
  2406.     decay_mult: 0.0
  2407.   }
  2408.   param {
  2409.     lr_mult: 0.0
  2410.     decay_mult: 0.0
  2411.   }
  2412.   param {
  2413.     lr_mult: 0.0
  2414.     decay_mult: 0.0
  2415.   }
  2416. }
  2417. layer {
  2418.   name: "glass/scale_4_2_pw"
  2419.   type: "Scale"
  2420.   bottom: "glass/conv_4_2_pw"
  2421.   top: "glass/conv_4_2_pw"
  2422.   scale_param {
  2423.     bias_term: true
  2424.   }
  2425. }
  2426. layer {
  2427.   name: "glass/relu_4_2_pw"
  2428.   type: "ReLU"
  2429.   bottom: "glass/conv_4_2_pw"
  2430.   top: "glass/conv_4_2_pw"
  2431. }
  2432. layer {
  2433.   name: "glass/conv_4_2_dw"
  2434.   type: "ConvolutionDepthwise"
  2435.   bottom: "glass/conv_4_2_pw"
  2436.   top: "glass/conv_4_2_dw"
  2437.   param {
  2438.     lr_mult: 1.0
  2439.     decay_mult: 1.0
  2440.   }
  2441.   convolution_param {
  2442.     num_output: 192
  2443.     bias_term: false
  2444.     pad: 1
  2445.     kernel_size: 3
  2446.     stride: 1
  2447.     weight_filler {
  2448.       type: "msra"
  2449.     }
  2450.     bias_filler {
  2451.       type: "constant"
  2452.       value: 0.0
  2453.     }
  2454.   }
  2455. }
  2456. layer {
  2457.   name: "glass/bn_4_2_dw"
  2458.   type: "BatchNorm"
  2459.   bottom: "glass/conv_4_2_dw"
  2460.   top: "glass/conv_4_2_dw"
  2461.   param {
  2462.     lr_mult: 0.0
  2463.     decay_mult: 0.0
  2464.   }
  2465.   param {
  2466.     lr_mult: 0.0
  2467.     decay_mult: 0.0
  2468.   }
  2469.   param {
  2470.     lr_mult: 0.0
  2471.     decay_mult: 0.0
  2472.   }
  2473. }
  2474. layer {
  2475.   name: "glass/scale_4_2_dw"
  2476.   type: "Scale"
  2477.   bottom: "glass/conv_4_2_dw"
  2478.   top: "glass/conv_4_2_dw"
  2479.   scale_param {
  2480.     bias_term: true
  2481.   }
  2482. }
  2483. layer {
  2484.   name: "glass/relu_4_2_dw"
  2485.   type: "ReLU"
  2486.   bottom: "glass/conv_4_2_dw"
  2487.   top: "glass/conv_4_2_dw"
  2488. }
  2489. layer {
  2490.   name: "glass/conv_4_2_linear"
  2491.   type: "Convolution"
  2492.   bottom: "glass/conv_4_2_dw"
  2493.   top: "glass/conv_4_2_linear"
  2494.   param {
  2495.     lr_mult: 1.0
  2496.     decay_mult: 1.0
  2497.   }
  2498.   convolution_param {
  2499.     num_output: 96
  2500.     bias_term: false
  2501.     pad: 0
  2502.     kernel_size: 1
  2503.     stride: 1
  2504.     weight_filler {
  2505.       type: "msra"
  2506.     }
  2507.     bias_filler {
  2508.       type: "constant"
  2509.       value: 0.0
  2510.     }
  2511.   }
  2512. }
  2513. layer {
  2514.   name: "glass/bn_4_2_linear"
  2515.   type: "BatchNorm"
  2516.   bottom: "glass/conv_4_2_linear"
  2517.   top: "glass/conv_4_2_linear"
  2518.   param {
  2519.     lr_mult: 0.0
  2520.     decay_mult: 0.0
  2521.   }
  2522.   param {
  2523.     lr_mult: 0.0
  2524.     decay_mult: 0.0
  2525.   }
  2526.   param {
  2527.     lr_mult: 0.0
  2528.     decay_mult: 0.0
  2529.   }
  2530. }
  2531. layer {
  2532.   name: "glass/scale_4_2_linear"
  2533.   type: "Scale"
  2534.   bottom: "glass/conv_4_2_linear"
  2535.   top: "glass/conv_4_2_linear"
  2536.   scale_param {
  2537.     bias_term: true
  2538.   }
  2539. }
  2540. layer {
  2541.   name: "glass/add_4_2"
  2542.   type: "Eltwise"
  2543.   bottom: "glass/conv_4_1_linear"
  2544.   bottom: "glass/conv_4_2_linear"
  2545.   top: "glass/add_4_2"
  2546. }
  2547.  
  2548. layer {
  2549.   name: "glass/conv1_"
  2550.   type: "Convolution"
  2551.   bottom: "glass/add_4_2"
  2552.   top: "glass/conv1_"
  2553.   param {
  2554.     lr_mult: 1
  2555.     decay_mult: 1
  2556.   }
  2557.   param {
  2558.     lr_mult: 2
  2559.     decay_mult: 0
  2560.   }
  2561.   convolution_param {
  2562.     num_output: 128
  2563.     kernel_size: 3
  2564.     stride: 1
  2565.     weight_filler {
  2566.       type: "xavier"
  2567.     }
  2568.     bias_filler {
  2569.       type: "constant"
  2570.       value: 0
  2571.     }
  2572.   }
  2573. }
  2574. layer {
  2575.   name: "glass/relu1_"
  2576.   type: "ReLU"
  2577.   bottom: "glass/conv1_"
  2578.   top: "glass/conv1_"
  2579. }
  2580. layer {
  2581.   name: "glass/pool1_"
  2582.   type: "Pooling"
  2583.   bottom: "glass/conv1_"
  2584.   top: "glass/pool1_"
  2585.   pooling_param {
  2586.     pool: AVE
  2587.     kernel_size: 4
  2588.     stride: 4
  2589.   }
  2590. }
  2591. layer {
  2592.   name: "glass/ip1"
  2593.   type: "InnerProduct"
  2594.   bottom: "glass/pool1_"
  2595.   top: "glass/ip1"
  2596.   param {
  2597.     lr_mult: 1
  2598.   }
  2599.   param {
  2600.     lr_mult: 2
  2601.   }
  2602.   inner_product_param {
  2603.     num_output: 3
  2604.     weight_filler {
  2605.       type: "xavier"
  2606.     }
  2607.     bias_filler {
  2608.       type: "constant"
  2609.     }
  2610.   }
  2611. }
  2612.  
  2613. layer {
  2614.   name: "race/conv_4_1_pw"
  2615.   type: "Convolution"
  2616.   bottom: "shuffle4"
  2617.   top: "race/conv_4_1_pw"
  2618.   param {
  2619.     lr_mult: 1.0
  2620.     decay_mult: 1.0
  2621.   }
  2622.   convolution_param {
  2623.     num_output: 192
  2624.     bias_term: false
  2625.     pad: 0
  2626.     kernel_size: 1
  2627.     stride: 1
  2628.     weight_filler {
  2629.       type: "msra"
  2630.     }
  2631.     bias_filler {
  2632.       type: "constant"
  2633.       value: 0.0
  2634.     }
  2635.   }
  2636. }
  2637. layer {
  2638.   name: "race/bn_4_1_pw"
  2639.   type: "BatchNorm"
  2640.   bottom: "race/conv_4_1_pw"
  2641.   top: "race/conv_4_1_pw"
  2642.   param {
  2643.     lr_mult: 0.0
  2644.     decay_mult: 0.0
  2645.   }
  2646.   param {
  2647.     lr_mult: 0.0
  2648.     decay_mult: 0.0
  2649.   }
  2650.   param {
  2651.     lr_mult: 0.0
  2652.     decay_mult: 0.0
  2653.   }
  2654. }
  2655. layer {
  2656.   name: "race/scale_4_1_pw"
  2657.   type: "Scale"
  2658.   bottom: "race/conv_4_1_pw"
  2659.   top: "race/conv_4_1_pw"
  2660.   scale_param {
  2661.     bias_term: true
  2662.   }
  2663. }
  2664. layer {
  2665.   name: "race/relu_4_1_pw"
  2666.   type: "ReLU"
  2667.   bottom: "race/conv_4_1_pw"
  2668.   top: "race/conv_4_1_pw"
  2669. }
  2670. layer {
  2671.   name: "race/conv_4_1_dw"
  2672.   type: "ConvolutionDepthwise"
  2673.   bottom: "race/conv_4_1_pw"
  2674.   top: "race/conv_4_1_dw"
  2675.   param {
  2676.     lr_mult: 1.0
  2677.     decay_mult: 1.0
  2678.   }
  2679.   convolution_param {
  2680.     num_output: 192
  2681.     bias_term: false
  2682.     pad: 1
  2683.     kernel_size: 3
  2684.     stride: 2
  2685.     weight_filler {
  2686.       type: "msra"
  2687.     }
  2688.     bias_filler {
  2689.       type: "constant"
  2690.       value: 0.0
  2691.     }
  2692.   }
  2693. }
  2694. layer {
  2695.   name: "race/bn_4_1_dw"
  2696.   type: "BatchNorm"
  2697.   bottom: "race/conv_4_1_dw"
  2698.   top: "race/conv_4_1_dw"
  2699.   param {
  2700.     lr_mult: 0.0
  2701.     decay_mult: 0.0
  2702.   }
  2703.   param {
  2704.     lr_mult: 0.0
  2705.     decay_mult: 0.0
  2706.   }
  2707.   param {
  2708.     lr_mult: 0.0
  2709.     decay_mult: 0.0
  2710.   }
  2711. }
  2712. layer {
  2713.   name: "race/scale_4_1_dw"
  2714.   type: "Scale"
  2715.   bottom: "race/conv_4_1_dw"
  2716.   top: "race/conv_4_1_dw"
  2717.   scale_param {
  2718.     bias_term: true
  2719.   }
  2720. }
  2721. layer {
  2722.   name: "race/relu_4_1_dw"
  2723.   type: "ReLU"
  2724.   bottom: "race/conv_4_1_dw"
  2725.   top: "race/conv_4_1_dw"
  2726. }
  2727. layer {
  2728.   name: "race/conv_4_1_linear"
  2729.   type: "Convolution"
  2730.   bottom: "race/conv_4_1_dw"
  2731.   top: "race/conv_4_1_linear"
  2732.   param {
  2733.     lr_mult: 1.0
  2734.     decay_mult: 1.0
  2735.   }
  2736.   convolution_param {
  2737.     num_output: 96
  2738.     bias_term: false
  2739.     pad: 0
  2740.     kernel_size: 1
  2741.     stride: 1
  2742.     weight_filler {
  2743.       type: "msra"
  2744.     }
  2745.     bias_filler {
  2746.       type: "constant"
  2747.       value: 0.0
  2748.     }
  2749.   }
  2750. }
  2751. layer {
  2752.   name: "race/bn_4_1_linear"
  2753.   type: "BatchNorm"
  2754.   bottom: "race/conv_4_1_linear"
  2755.   top: "race/conv_4_1_linear"
  2756.   param {
  2757.     lr_mult: 0.0
  2758.     decay_mult: 0.0
  2759.   }
  2760.   param {
  2761.     lr_mult: 0.0
  2762.     decay_mult: 0.0
  2763.   }
  2764.   param {
  2765.     lr_mult: 0.0
  2766.     decay_mult: 0.0
  2767.   }
  2768. }
  2769. layer {
  2770.   name: "race/scale_4_1_linear"
  2771.   type: "Scale"
  2772.   bottom: "race/conv_4_1_linear"
  2773.   top: "race/conv_4_1_linear"
  2774.   scale_param {
  2775.     bias_term: true
  2776.   }
  2777. }
  2778. layer {
  2779.   name: "race/conv_4_2_pw"
  2780.   type: "Convolution"
  2781.   bottom: "race/conv_4_1_linear"
  2782.   top: "race/conv_4_2_pw"
  2783.   param {
  2784.     lr_mult: 1.0
  2785.     decay_mult: 1.0
  2786.   }
  2787.   convolution_param {
  2788.     num_output: 192
  2789.     bias_term: false
  2790.     pad: 0
  2791.     kernel_size: 1
  2792.     stride: 1
  2793.     weight_filler {
  2794.       type: "msra"
  2795.     }
  2796.     bias_filler {
  2797.       type: "constant"
  2798.       value: 0.0
  2799.     }
  2800.   }
  2801. }
  2802. layer {
  2803.   name: "race/bn_4_2_pw"
  2804.   type: "BatchNorm"
  2805.   bottom: "race/conv_4_2_pw"
  2806.   top: "race/conv_4_2_pw"
  2807.   param {
  2808.     lr_mult: 0.0
  2809.     decay_mult: 0.0
  2810.   }
  2811.   param {
  2812.     lr_mult: 0.0
  2813.     decay_mult: 0.0
  2814.   }
  2815.   param {
  2816.     lr_mult: 0.0
  2817.     decay_mult: 0.0
  2818.   }
  2819. }
  2820. layer {
  2821.   name: "race/scale_4_2_pw"
  2822.   type: "Scale"
  2823.   bottom: "race/conv_4_2_pw"
  2824.   top: "race/conv_4_2_pw"
  2825.   scale_param {
  2826.     bias_term: true
  2827.   }
  2828. }
  2829. layer {
  2830.   name: "race/relu_4_2_pw"
  2831.   type: "ReLU"
  2832.   bottom: "race/conv_4_2_pw"
  2833.   top: "race/conv_4_2_pw"
  2834. }
  2835. layer {
  2836.   name: "race/conv_4_2_dw"
  2837.   type: "ConvolutionDepthwise"
  2838.   bottom: "race/conv_4_2_pw"
  2839.   top: "race/conv_4_2_dw"
  2840.   param {
  2841.     lr_mult: 1.0
  2842.     decay_mult: 1.0
  2843.   }
  2844.   convolution_param {
  2845.     num_output: 192
  2846.     bias_term: false
  2847.     pad: 1
  2848.     kernel_size: 3
  2849.     stride: 1
  2850.     weight_filler {
  2851.       type: "msra"
  2852.     }
  2853.     bias_filler {
  2854.       type: "constant"
  2855.       value: 0.0
  2856.     }
  2857.   }
  2858. }
  2859. layer {
  2860.   name: "race/bn_4_2_dw"
  2861.   type: "BatchNorm"
  2862.   bottom: "race/conv_4_2_dw"
  2863.   top: "race/conv_4_2_dw"
  2864.   param {
  2865.     lr_mult: 0.0
  2866.     decay_mult: 0.0
  2867.   }
  2868.   param {
  2869.     lr_mult: 0.0
  2870.     decay_mult: 0.0
  2871.   }
  2872.   param {
  2873.     lr_mult: 0.0
  2874.     decay_mult: 0.0
  2875.   }
  2876. }
  2877. layer {
  2878.   name: "race/scale_4_2_dw"
  2879.   type: "Scale"
  2880.   bottom: "race/conv_4_2_dw"
  2881.   top: "race/conv_4_2_dw"
  2882.   scale_param {
  2883.     bias_term: true
  2884.   }
  2885. }
  2886. layer {
  2887.   name: "race/relu_4_2_dw"
  2888.   type: "ReLU"
  2889.   bottom: "race/conv_4_2_dw"
  2890.   top: "race/conv_4_2_dw"
  2891. }
  2892. layer {
  2893.   name: "race/conv_4_2_linear"
  2894.   type: "Convolution"
  2895.   bottom: "race/conv_4_2_dw"
  2896.   top: "race/conv_4_2_linear"
  2897.   param {
  2898.     lr_mult: 1.0
  2899.     decay_mult: 1.0
  2900.   }
  2901.   convolution_param {
  2902.     num_output: 96
  2903.     bias_term: false
  2904.     pad: 0
  2905.     kernel_size: 1
  2906.     stride: 1
  2907.     weight_filler {
  2908.       type: "msra"
  2909.     }
  2910.     bias_filler {
  2911.       type: "constant"
  2912.       value: 0.0
  2913.     }
  2914.   }
  2915. }
  2916. layer {
  2917.   name: "race/bn_4_2_linear"
  2918.   type: "BatchNorm"
  2919.   bottom: "race/conv_4_2_linear"
  2920.   top: "race/conv_4_2_linear"
  2921.   param {
  2922.     lr_mult: 0.0
  2923.     decay_mult: 0.0
  2924.   }
  2925.   param {
  2926.     lr_mult: 0.0
  2927.     decay_mult: 0.0
  2928.   }
  2929.   param {
  2930.     lr_mult: 0.0
  2931.     decay_mult: 0.0
  2932.   }
  2933. }
  2934. layer {
  2935.   name: "race/scale_4_2_linear"
  2936.   type: "Scale"
  2937.   bottom: "race/conv_4_2_linear"
  2938.   top: "race/conv_4_2_linear"
  2939.   scale_param {
  2940.     bias_term: true
  2941.   }
  2942. }
  2943. layer {
  2944.   name: "race/add_4_2"
  2945.   type: "Eltwise"
  2946.   bottom: "race/conv_4_1_linear"
  2947.   bottom: "race/conv_4_2_linear"
  2948.   top: "race/add_4_2"
  2949. }
  2950.  
  2951. layer {
  2952.   name: "race/conv1_"
  2953.   type: "Convolution"
  2954.   bottom: "race/add_4_2"
  2955.   top: "race/conv1_"
  2956.   param {
  2957.     lr_mult: 1
  2958.     decay_mult: 1
  2959.   }
  2960.   param {
  2961.     lr_mult: 2
  2962.     decay_mult: 0
  2963.   }
  2964.   convolution_param {
  2965.     num_output: 128
  2966.     kernel_size: 3
  2967.     stride: 1
  2968.     weight_filler {
  2969.       type: "xavier"
  2970.     }
  2971.     bias_filler {
  2972.       type: "constant"
  2973.       value: 0
  2974.     }
  2975.   }
  2976. }
  2977. layer {
  2978.   name: "race/relu1_"
  2979.   type: "ReLU"
  2980.   bottom: "race/conv1_"
  2981.   top: "race/conv1_"
  2982. }
  2983. layer {
  2984.   name: "race/pool1_"
  2985.   type: "Pooling"
  2986.   bottom: "race/conv1_"
  2987.   top: "race/pool1_"
  2988.   pooling_param {
  2989.     pool: AVE
  2990.     kernel_size: 4
  2991.     stride: 4
  2992.   }
  2993. }
  2994. layer {
  2995.   name: "race/ip1"
  2996.   type: "InnerProduct"
  2997.   bottom: "race/pool1_"
  2998.   top: "race/ip1"
  2999.   param {
  3000.     lr_mult: 1
  3001.   }
  3002.   param {
  3003.     lr_mult: 2
  3004.   }
  3005.   inner_product_param {
  3006.     num_output: 4
  3007.     weight_filler {
  3008.       type: "xavier"
  3009.     }
  3010.     bias_filler {
  3011.       type: "constant"
  3012.     }
  3013.   }
  3014. }
  3015.  
  3016.  
  3017. layer {
  3018.   name: "slice"
  3019.   type: "Slice"
  3020.   bottom: "label"
  3021.   top: "label_age"
  3022.   top: "label_emotion"
  3023.   top: "label_sex"
  3024.   top: "label_glass"
  3025.   top: "label_race"
  3026.   slice_param {
  3027.     axis: 1
  3028.   }
  3029. }
  3030.  
  3031. layer {
  3032.   name: "loss_age"
  3033.   type: "AbsoluteLoss"
  3034.   bottom: "age/ip2"
  3035.   bottom: "label_age"
  3036.   top: "loss_age"
  3037. }
  3038. #layer {
  3039. #  name: "loss_age"
  3040. #  type: "EuclideanLoss"
  3041. #  bottom: "age/ip2"
  3042. #  bottom: "label_age"
  3043. #  top: "loss_age"
  3044. #}
  3045.  
  3046.  
  3047. layer {
  3048.   name: "accuracy_age"
  3049.   type: "AbsoluteLoss"
  3050.   bottom: "age/ip2"
  3051.   bottom: "label_age"
  3052.   top: "accuracy_age"
  3053.   include {
  3054.     phase: TEST
  3055.   }
  3056. }
  3057.  
  3058.  
  3059.  
  3060. layer {
  3061.   name: "loss_emotion"
  3062.   type: "SoftmaxWithLoss"
  3063.   bottom: "emotion/ip1"
  3064.   bottom: "label_emotion"
  3065.   top: "loss_emotion"
  3066. }
  3067.  
  3068. layer {
  3069.   name: "accuracy_emotion"
  3070.   type: "Accuracy"
  3071.   bottom: "emotion/ip1"
  3072.   bottom: "label_emotion"
  3073.   top: "accuracy_emotion"
  3074.   include {
  3075.     phase: TEST
  3076.   }
  3077. }
  3078.  
  3079. layer {
  3080.   name: "loss_sex"
  3081.   type: "SoftmaxWithLoss"
  3082.   bottom: "sex/ip1"
  3083.   bottom: "label_sex"
  3084.   top: "loss_sex"
  3085. }
  3086.  
  3087. layer {
  3088.   name: "accuracy_sex"
  3089.   type: "Accuracy"
  3090.   bottom: "sex/ip1"
  3091.   bottom: "label_sex"
  3092.   top: "accuracy_sex"
  3093.   include {
  3094.     phase: TEST
  3095.   }
  3096. }
  3097.  
  3098.  
  3099.  
  3100. layer {
  3101.   name: "loss_glass"
  3102.   type: "SoftmaxWithLoss"
  3103.   bottom: "glass/ip1"
  3104.   bottom: "label_glass"
  3105.   top: "loss_glass"
  3106. }
  3107.  
  3108. layer {
  3109.   name: "accuracy_glass"
  3110.   type: "Accuracy"
  3111.   bottom: "glass/ip1"
  3112.   bottom: "label_glass"
  3113.   top: "accuracy_glass"
  3114.   include {
  3115.     phase: TEST
  3116.   }
  3117. }
  3118.  
  3119. layer {
  3120.   name: "loss_race"
  3121.   type: "SoftmaxWithLoss"
  3122.   bottom: "race/ip1"
  3123.   bottom: "label_race"
  3124.   top: "loss_race"
  3125. }
  3126.  
  3127. layer {
  3128.   name: "accuracy_race"
  3129.   type: "Accuracy"
  3130.   bottom: "race/ip1"
  3131.   bottom: "label_race"
  3132.   top: "accuracy_race"
  3133.   include {
  3134.     phase: TEST
  3135.   }
  3136. }
  3137.  
  3138.  
  3139.  
  3140.  
  3141.  
  3142.  
  3143.  
  3144.  
  3145.  
  3146.  
  3147.  
  3148.  
  3149.  
  3150.

 

mobile_net.prototxt

  1. name: "FaceAttribution"
  2. layer {
  3.   name: "data"
  4.   type: "Data"
  5.   top: "data"
  6.   include {
  7.     phase: TRAIN
  8.   }
  9.   transform_param {
  10. 		mean_value: 127.5
  11. 		mean_value: 127.5
  12. 		mean_value: 127.5
  13. 		scale: 0.0078125
  14.   }
  15.   data_param {
  16.     source: "D:/face_attribute/lmdb/train_data_npd"
  17.     batch_size: 64
  18.     backend: LMDB
  19.   }
  20. }
  21. layer {
  22.   name: "data"
  23.   type: "Data"
  24.   top: "label"
  25.   include {
  26.     phase: TRAIN
  27.   }
  28.   data_param {
  29.     source: "D:/face_attribute/lmdb/train_label_npd"
  30.     batch_size: 64
  31.     backend: LMDB
  32.   }
  33. }
  34.  
  35. layer {
  36.   name: "data"
  37.   type: "Data"
  38.   top: "data"
  39.   include {
  40.     phase: TEST
  41.   }
  42.   transform_param {
  43. 		mean_value: 127.5
  44. 		mean_value: 127.5
  45. 		mean_value: 127.5
  46. 		scale: 0.0078125
  47.   }
  48.   data_param {
  49.     source: "D:/face_attribute/lmdb/test_data_npd"
  50.     batch_size: 64
  51.     backend: LMDB
  52.   }
  53. }
  54. layer {
  55.   name: "data"
  56.   type: "Data"
  57.   top: "label"
  58.   include {
  59.     phase: TEST
  60.   }
  61.   data_param {
  62.     source: "D:/face_attribute/lmdb/test_label_npd"
  63.     batch_size: 64
  64.     backend: LMDB
  65.   }
  66. }
  67.  
  68.  
  69. layer {
  70.   name: "conv1"
  71.   type: "Convolution"
  72.   bottom: "data"
  73.   top: "conv1"
  74.   convolution_param {
  75.     num_output: 24
  76.     pad: 1
  77.     kernel_size: 3
  78.     stride: 2
  79.     bias_term: false
  80.     weight_filler {
  81.       type: "msra"
  82.     }
  83.   }
  84. }
  85. layer {
  86.   name: "conv1_bn"
  87.   type: "BatchNorm"
  88.   bottom: "conv1"
  89.   top: "conv1"
  90.   param {
  91.     lr_mult: 0
  92.     decay_mult: 0
  93.   }
  94.   param {
  95.     lr_mult: 0
  96.     decay_mult: 0
  97.   }
  98.   param {
  99.     lr_mult: 0
  100.     decay_mult: 0
  101.   }
  102. }
  103. layer {
  104.   name: "conv1_scale"
  105.   bottom: "conv1"
  106.   top: "conv1"
  107.   type: "Scale"
  108.   scale_param {
  109.     filler {
  110.       value: 1
  111.     }
  112.     bias_term: true
  113.     bias_filler {
  114.       value: 0
  115.     }
  116.   }
  117. }
  118. layer {
  119.   name: "conv1_relu"
  120.   type: "PReLU"
  121.   bottom: "conv1"
  122.   top: "conv1"
  123. }
  124.  
  125.  
  126. layer {
  127.   name: "conv2"
  128.   type: "Convolution"
  129.   bottom: "conv1"
  130.   top: "conv2"
  131.   convolution_param {
  132.     num_output: 48
  133.     pad: 1
  134.     kernel_size: 3
  135.     stride: 2
  136.     bias_term: false
  137.     weight_filler {
  138.       type: "msra"
  139.     }
  140.   }
  141. }
  142. layer {
  143.   name: "conv2_bn"
  144.   type: "BatchNorm"
  145.   bottom: "conv2"
  146.   top: "conv2"
  147.   param {
  148.     lr_mult: 0
  149.     decay_mult: 0
  150.   }
  151.   param {
  152.     lr_mult: 0
  153.     decay_mult: 0
  154.   }
  155.   param {
  156.     lr_mult: 0
  157.     decay_mult: 0
  158.   }
  159. }
  160. layer {
  161.   name: "conv2_scale"
  162.   bottom: "conv2"
  163.   top: "conv2"
  164.   type: "Scale"
  165.   scale_param {
  166.     filler {
  167.       value: 1
  168.     }
  169.     bias_term: true
  170.     bias_filler {
  171.       value: 0
  172.     }
  173.   }
  174. }
  175. layer {
  176.   name: "conv2_relu"
  177.   type: "PReLU"
  178.   bottom: "conv2"
  179.   top: "conv2"
  180. }
  181.  
  182.  
  183.  
  184. layer {
  185.   name: "conv_3_1_pw"
  186.   type: "Convolution"
  187.   bottom: "conv2"
  188.   top: "conv_3_1_pw"
  189.   param {
  190.     lr_mult: 1.0
  191.     decay_mult: 1.0
  192.   }
  193.   convolution_param {
  194.     num_output: 96
  195.     bias_term: false
  196.     pad: 0
  197.     kernel_size: 1
  198.     stride: 1
  199.     weight_filler {
  200.       type: "msra"
  201.     }
  202.     bias_filler {
  203.       type: "constant"
  204.       value: 0.0
  205.     }
  206.   }
  207. }
  208. layer {
  209.   name: "bn_3_1_pw"
  210.   type: "BatchNorm"
  211.   bottom: "conv_3_1_pw"
  212.   top: "conv_3_1_pw"
  213.   param {
  214.     lr_mult: 0.0
  215.     decay_mult: 0.0
  216.   }
  217.   param {
  218.     lr_mult: 0.0
  219.     decay_mult: 0.0
  220.   }
  221.   param {
  222.     lr_mult: 0.0
  223.     decay_mult: 0.0
  224.   }
  225. }
  226. layer {
  227.   name: "scale_3_1_pw"
  228.   type: "Scale"
  229.   bottom: "conv_3_1_pw"
  230.   top: "conv_3_1_pw"
  231.   scale_param {
  232.     bias_term: true
  233.   }
  234. }
  235. layer {
  236.   name: "relu_3_1_pw"
  237.   type: "PReLU"
  238.   bottom: "conv_3_1_pw"
  239.   top: "conv_3_1_pw"
  240. }
  241. layer {
  242.   name: "conv_3_1_dw"
  243.   type: "ConvolutionDepthwise"
  244.   bottom: "conv_3_1_pw"
  245.   top: "conv_3_1_dw"
  246.   param {
  247.     lr_mult: 1.0
  248.     decay_mult: 1.0
  249.   }
  250.   convolution_param {
  251.     num_output: 96
  252.     bias_term: false
  253.     pad: 1
  254.     kernel_size: 3
  255.     stride: 2
  256.     weight_filler {
  257.       type: "msra"
  258.     }
  259.     bias_filler {
  260.       type: "constant"
  261.       value: 0.0
  262.     }
  263.   }
  264. }
  265. layer {
  266.   name: "bn_3_1_dw"
  267.   type: "BatchNorm"
  268.   bottom: "conv_3_1_dw"
  269.   top: "conv_3_1_dw"
  270.   param {
  271.     lr_mult: 0.0
  272.     decay_mult: 0.0
  273.   }
  274.   param {
  275.     lr_mult: 0.0
  276.     decay_mult: 0.0
  277.   }
  278.   param {
  279.     lr_mult: 0.0
  280.     decay_mult: 0.0
  281.   }
  282. }
  283. layer {
  284.   name: "scale_3_1_dw"
  285.   type: "Scale"
  286.   bottom: "conv_3_1_dw"
  287.   top: "conv_3_1_dw"
  288.   scale_param {
  289.     bias_term: true
  290.   }
  291. }
  292. layer {
  293.   name: "relu_3_1_dw"
  294.   type: "PReLU"
  295.   bottom: "conv_3_1_dw"
  296.   top: "conv_3_1_dw"
  297. }
  298. layer {
  299.   name: "conv_3_1_linear"
  300.   type: "Convolution"
  301.   bottom: "conv_3_1_dw"
  302.   top: "conv_3_1_linear"
  303.   param {
  304.     lr_mult: 1.0
  305.     decay_mult: 1.0
  306.   }
  307.   convolution_param {
  308.     num_output: 64
  309.     bias_term: false
  310.     pad: 0
  311.     kernel_size: 1
  312.     stride: 1
  313.     weight_filler {
  314.       type: "msra"
  315.     }
  316.     bias_filler {
  317.       type: "constant"
  318.       value: 0.0
  319.     }
  320.   }
  321. }
  322. layer {
  323.   name: "bn_3_1_linear"
  324.   type: "BatchNorm"
  325.   bottom: "conv_3_1_linear"
  326.   top: "conv_3_1_linear"
  327.   param {
  328.     lr_mult: 0.0
  329.     decay_mult: 0.0
  330.   }
  331.   param {
  332.     lr_mult: 0.0
  333.     decay_mult: 0.0
  334.   }
  335.   param {
  336.     lr_mult: 0.0
  337.     decay_mult: 0.0
  338.   }
  339. }
  340. layer {
  341.   name: "scale_3_1_linear"
  342.   type: "Scale"
  343.   bottom: "conv_3_1_linear"
  344.   top: "conv_3_1_linear"
  345.   scale_param {
  346.     bias_term: true
  347.   }
  348. }
  349.  
  350.  
  351. layer {
  352.   name: "conv_4_1_pw"
  353.   type: "Convolution"
  354.   bottom: "conv_3_1_linear"
  355.   top: "conv_4_1_pw"
  356.   param {
  357.     lr_mult: 1.0
  358.     decay_mult: 1.0
  359.   }
  360.   convolution_param {
  361.     num_output: 96
  362.     bias_term: false
  363.     pad: 0
  364.     kernel_size: 1
  365.     stride: 1
  366.     weight_filler {
  367.       type: "msra"
  368.     }
  369.     bias_filler {
  370.       type: "constant"
  371.       value: 0.0
  372.     }
  373.   }
  374. }
  375. layer {
  376.   name: "bn_4_1_pw"
  377.   type: "BatchNorm"
  378.   bottom: "conv_4_1_pw"
  379.   top: "conv_4_1_pw"
  380.   param {
  381.     lr_mult: 0.0
  382.     decay_mult: 0.0
  383.   }
  384.   param {
  385.     lr_mult: 0.0
  386.     decay_mult: 0.0
  387.   }
  388.   param {
  389.     lr_mult: 0.0
  390.     decay_mult: 0.0
  391.   }
  392. }
  393. layer {
  394.   name: "scale_4_1_pw"
  395.   type: "Scale"
  396.   bottom: "conv_4_1_pw"
  397.   top: "conv_4_1_pw"
  398.   scale_param {
  399.     bias_term: true
  400.   }
  401. }
  402. layer {
  403.   name: "relu_4_1_pw"
  404.   type: "PReLU"
  405.   bottom: "conv_4_1_pw"
  406.   top: "conv_4_1_pw"
  407. }
  408. layer {
  409.   name: "conv_4_1_dw"
  410.   type: "ConvolutionDepthwise"
  411.   bottom: "conv_4_1_pw"
  412.   top: "conv_4_1_dw"
  413.   param {
  414.     lr_mult: 1.0
  415.     decay_mult: 1.0
  416.   }
  417.   convolution_param {
  418.     num_output: 96
  419.     bias_term: false
  420.     pad: 1
  421.     kernel_size: 3
  422.     stride: 1
  423.     weight_filler {
  424.       type: "msra"
  425.     }
  426.     bias_filler {
  427.       type: "constant"
  428.       value: 0.0
  429.     }
  430.   }
  431. }
  432. layer {
  433.   name: "bn_4_1_dw"
  434.   type: "BatchNorm"
  435.   bottom: "conv_4_1_dw"
  436.   top: "conv_4_1_dw"
  437.   param {
  438.     lr_mult: 0.0
  439.     decay_mult: 0.0
  440.   }
  441.   param {
  442.     lr_mult: 0.0
  443.     decay_mult: 0.0
  444.   }
  445.   param {
  446.     lr_mult: 0.0
  447.     decay_mult: 0.0
  448.   }
  449. }
  450. layer {
  451.   name: "scale_4_1_dw"
  452.   type: "Scale"
  453.   bottom: "conv_4_1_dw"
  454.   top: "conv_4_1_dw"
  455.   scale_param {
  456.     bias_term: true
  457.   }
  458. }
  459. layer {
  460.   name: "relu_4_1_dw"
  461.   type: "PReLU"
  462.   bottom: "conv_4_1_dw"
  463.   top: "conv_4_1_dw"
  464. }
  465. layer {
  466.   name: "conv_4_1_linear"
  467.   type: "Convolution"
  468.   bottom: "conv_4_1_dw"
  469.   top: "conv_4_1_linear"
  470.   param {
  471.     lr_mult: 1.0
  472.     decay_mult: 1.0
  473.   }
  474.   convolution_param {
  475.     num_output: 64
  476.     bias_term: false
  477.     pad: 0
  478.     kernel_size: 1
  479.     stride: 1
  480.     weight_filler {
  481.       type: "msra"
  482.     }
  483.     bias_filler {
  484.       type: "constant"
  485.       value: 0.0
  486.     }
  487.   }
  488. }
  489. layer {
  490.   name: "bn_4_1_linear"
  491.   type: "BatchNorm"
  492.   bottom: "conv_4_1_linear"
  493.   top: "conv_4_1_linear"
  494.   param {
  495.     lr_mult: 0.0
  496.     decay_mult: 0.0
  497.   }
  498.   param {
  499.     lr_mult: 0.0
  500.     decay_mult: 0.0
  501.   }
  502.   param {
  503.     lr_mult: 0.0
  504.     decay_mult: 0.0
  505.   }
  506. }
  507. layer {
  508.   name: "scale_4_1_linear"
  509.   type: "Scale"
  510.   bottom: "conv_4_1_linear"
  511.   top: "conv_4_1_linear"
  512.   scale_param {
  513.     bias_term: true
  514.   }
  515. }
  516.  
  517. layer {
  518.   name: "add_4_1"
  519.   type: "Eltwise"
  520.   bottom: "conv_3_1_linear"
  521.   bottom: "conv_4_1_linear"
  522.   top: "add_4_2"
  523. }
  524.  
  525. layer {
  526.   name: "conv_5_1_pw"
  527.   type: "Convolution"
  528.   bottom: "add_4_2"
  529.   top: "conv_5_1_pw"
  530.   param {
  531.     lr_mult: 1.0
  532.     decay_mult: 1.0
  533.   }
  534.   convolution_param {
  535.     num_output: 96
  536.     bias_term: false
  537.     pad: 0
  538.     kernel_size: 1
  539.     stride: 1
  540.     weight_filler {
  541.       type: "msra"
  542.     }
  543.     bias_filler {
  544.       type: "constant"
  545.       value: 0.0
  546.     }
  547.   }
  548. }
  549. layer {
  550.   name: "bn_5_1_pw"
  551.   type: "BatchNorm"
  552.   bottom: "conv_5_1_pw"
  553.   top: "conv_5_1_pw"
  554.   param {
  555.     lr_mult: 0.0
  556.     decay_mult: 0.0
  557.   }
  558.   param {
  559.     lr_mult: 0.0
  560.     decay_mult: 0.0
  561.   }
  562.   param {
  563.     lr_mult: 0.0
  564.     decay_mult: 0.0
  565.   }
  566. }
  567. layer {
  568.   name: "scale_5_1_pw"
  569.   type: "Scale"
  570.   bottom: "conv_5_1_pw"
  571.   top: "conv_5_1_pw"
  572.   scale_param {
  573.     bias_term: true
  574.   }
  575. }
  576. layer {
  577.   name: "relu_5_1_pw"
  578.   type: "PReLU"
  579.   bottom: "conv_5_1_pw"
  580.   top: "conv_5_1_pw"
  581. }
  582. layer {
  583.   name: "conv_5_1_dw"
  584.   type: "ConvolutionDepthwise"
  585.   bottom: "conv_5_1_pw"
  586.   top: "conv_5_1_dw"
  587.   param {
  588.     lr_mult: 1.0
  589.     decay_mult: 1.0
  590.   }
  591.   convolution_param {
  592.     num_output: 96
  593.     bias_term: false
  594.     pad: 1
  595.     kernel_size: 3
  596.     stride: 1
  597.     weight_filler {
  598.       type: "msra"
  599.     }
  600.     bias_filler {
  601.       type: "constant"
  602.       value: 0.0
  603.     }
  604.   }
  605. }
  606. layer {
  607.   name: "bn_5_1_dw"
  608.   type: "BatchNorm"
  609.   bottom: "conv_5_1_dw"
  610.   top: "conv_5_1_dw"
  611.   param {
  612.     lr_mult: 0.0
  613.     decay_mult: 0.0
  614.   }
  615.   param {
  616.     lr_mult: 0.0
  617.     decay_mult: 0.0
  618.   }
  619.   param {
  620.     lr_mult: 0.0
  621.     decay_mult: 0.0
  622.   }
  623. }
  624. layer {
  625.   name: "scale_5_1_dw"
  626.   type: "Scale"
  627.   bottom: "conv_5_1_dw"
  628.   top: "conv_5_1_dw"
  629.   scale_param {
  630.     bias_term: true
  631.   }
  632. }
  633. layer {
  634.   name: "relu_5_1_dw"
  635.   type: "PReLU"
  636.   bottom: "conv_5_1_dw"
  637.   top: "conv_5_1_dw"
  638. }
  639. layer {
  640.   name: "conv_5_1_linear"
  641.   type: "Convolution"
  642.   bottom: "conv_5_1_dw"
  643.   top: "conv_5_1_linear"
  644.   param {
  645.     lr_mult: 1.0
  646.     decay_mult: 1.0
  647.   }
  648.   convolution_param {
  649.     num_output: 64
  650.     bias_term: false
  651.     pad: 0
  652.     kernel_size: 1
  653.     stride: 1
  654.     weight_filler {
  655.       type: "msra"
  656.     }
  657.     bias_filler {
  658.       type: "constant"
  659.       value: 0.0
  660.     }
  661.   }
  662. }
  663. layer {
  664.   name: "bn_5_1_linear"
  665.   type: "BatchNorm"
  666.   bottom: "conv_5_1_linear"
  667.   top: "conv_5_1_linear"
  668.   param {
  669.     lr_mult: 0.0
  670.     decay_mult: 0.0
  671.   }
  672.   param {
  673.     lr_mult: 0.0
  674.     decay_mult: 0.0
  675.   }
  676.   param {
  677.     lr_mult: 0.0
  678.     decay_mult: 0.0
  679.   }
  680. }
  681. layer {
  682.   name: "scale_5_1_linear"
  683.   type: "Scale"
  684.   bottom: "conv_5_1_linear"
  685.   top: "conv_5_1_linear"
  686.   scale_param {
  687.     bias_term: true
  688.   }
  689. }
  690.  
  691. layer {
  692.   name: "add_5_1"
  693.   type: "Eltwise"
  694.   bottom: "add_4_2"
  695.   bottom: "conv_5_1_linear"
  696.   top: "add_5_1"
  697. }
  698.  
  699.  
  700. layer {
  701.   name: "conv_6_1_pw"
  702.   type: "Convolution"
  703.   bottom: "add_5_1"
  704.   top: "conv_6_1_pw"
  705.   param {
  706.     lr_mult: 1.0
  707.     decay_mult: 1.0
  708.   }
  709.   convolution_param {
  710.     num_output: 96
  711.     bias_term: false
  712.     pad: 0
  713.     kernel_size: 1
  714.     stride: 1
  715.     weight_filler {
  716.       type: "msra"
  717.     }
  718.     bias_filler {
  719.       type: "constant"
  720.       value: 0.0
  721.     }
  722.   }
  723. }
  724. layer {
  725.   name: "bn_6_1_pw"
  726.   type: "BatchNorm"
  727.   bottom: "conv_6_1_pw"
  728.   top: "conv_6_1_pw"
  729.   param {
  730.     lr_mult: 0.0
  731.     decay_mult: 0.0
  732.   }
  733.   param {
  734.     lr_mult: 0.0
  735.     decay_mult: 0.0
  736.   }
  737.   param {
  738.     lr_mult: 0.0
  739.     decay_mult: 0.0
  740.   }
  741. }
  742. layer {
  743.   name: "scale_6_1_pw"
  744.   type: "Scale"
  745.   bottom: "conv_6_1_pw"
  746.   top: "conv_6_1_pw"
  747.   scale_param {
  748.     bias_term: true
  749.   }
  750. }
  751. layer {
  752.   name: "relu_6_1_pw"
  753.   type: "PReLU"
  754.   bottom: "conv_6_1_pw"
  755.   top: "conv_6_1_pw"
  756. }
  757. layer {
  758.   name: "conv_6_1_dw"
  759.   type: "ConvolutionDepthwise"
  760.   bottom: "conv_6_1_pw"
  761.   top: "conv_6_1_dw"
  762.   param {
  763.     lr_mult: 1.0
  764.     decay_mult: 1.0
  765.   }
  766.   convolution_param {
  767.     num_output: 96
  768.     bias_term: false
  769.     pad: 1
  770.     kernel_size: 3
  771.     stride: 1
  772.     weight_filler {
  773.       type: "msra"
  774.     }
  775.     bias_filler {
  776.       type: "constant"
  777.       value: 0.0
  778.     }
  779.   }
  780. }
  781. layer {
  782.   name: "bn_6_1_dw"
  783.   type: "BatchNorm"
  784.   bottom: "conv_6_1_dw"
  785.   top: "conv_6_1_dw"
  786.   param {
  787.     lr_mult: 0.0
  788.     decay_mult: 0.0
  789.   }
  790.   param {
  791.     lr_mult: 0.0
  792.     decay_mult: 0.0
  793.   }
  794.   param {
  795.     lr_mult: 0.0
  796.     decay_mult: 0.0
  797.   }
  798. }
  799. layer {
  800.   name: "scale_6_1_dw"
  801.   type: "Scale"
  802.   bottom: "conv_6_1_dw"
  803.   top: "conv_6_1_dw"
  804.   scale_param {
  805.     bias_term: true
  806.   }
  807. }
  808. layer {
  809.   name: "relu_6_1_dw"
  810.   type: "PReLU"
  811.   bottom: "conv_6_1_dw"
  812.   top: "conv_6_1_dw"
  813. }
  814. layer {
  815.   name: "conv_6_1_linear"
  816.   type: "Convolution"
  817.   bottom: "conv_6_1_dw"
  818.   top: "conv_6_1_linear"
  819.   param {
  820.     lr_mult: 1.0
  821.     decay_mult: 1.0
  822.   }
  823.   convolution_param {
  824.     num_output: 64
  825.     bias_term: false
  826.     pad: 0
  827.     kernel_size: 1
  828.     stride: 1
  829.     weight_filler {
  830.       type: "msra"
  831.     }
  832.     bias_filler {
  833.       type: "constant"
  834.       value: 0.0
  835.     }
  836.   }
  837. }
  838. layer {
  839.   name: "bn_6_1_linear"
  840.   type: "BatchNorm"
  841.   bottom: "conv_6_1_linear"
  842.   top: "conv_6_1_linear"
  843.   param {
  844.     lr_mult: 0.0
  845.     decay_mult: 0.0
  846.   }
  847.   param {
  848.     lr_mult: 0.0
  849.     decay_mult: 0.0
  850.   }
  851.   param {
  852.     lr_mult: 0.0
  853.     decay_mult: 0.0
  854.   }
  855. }
  856. layer {
  857.   name: "scale_6_1_linear"
  858.   type: "Scale"
  859.   bottom: "conv_6_1_linear"
  860.   top: "conv_6_1_linear"
  861.   scale_param {
  862.     bias_term: true
  863.   }
  864. }
  865.  
  866. layer {
  867.   name: "add_6_1"
  868.   type: "Eltwise"
  869.   bottom: "add_5_1"
  870.   bottom: "conv_6_1_linear"
  871.   top: "add_6_1"
  872. }
  873.  
  874.  
  875. layer {
  876.   name: "age/conv_4_1_pw"
  877.   type: "Convolution"
  878.   bottom: "add_6_1"
  879.   top: "age/conv_4_1_pw"
  880.   param {
  881.     lr_mult: 1.0
  882.     decay_mult: 1.0
  883.   }
  884.   convolution_param {
  885.     num_output: 192
  886.     bias_term: false
  887.     pad: 0
  888.     kernel_size: 1
  889.     stride: 1
  890.     weight_filler {
  891.       type: "msra"
  892.     }
  893.     bias_filler {
  894.       type: "constant"
  895.       value: 0.0
  896.     }
  897.   }
  898. }
  899. layer {
  900.   name: "age/bn_4_1_pw"
  901.   type: "BatchNorm"
  902.   bottom: "age/conv_4_1_pw"
  903.   top: "age/conv_4_1_pw"
  904.   param {
  905.     lr_mult: 0.0
  906.     decay_mult: 0.0
  907.   }
  908.   param {
  909.     lr_mult: 0.0
  910.     decay_mult: 0.0
  911.   }
  912.   param {
  913.     lr_mult: 0.0
  914.     decay_mult: 0.0
  915.   }
  916. }
  917. layer {
  918.   name: "age/scale_4_1_pw"
  919.   type: "Scale"
  920.   bottom: "age/conv_4_1_pw"
  921.   top: "age/conv_4_1_pw"
  922.   scale_param {
  923.     bias_term: true
  924.   }
  925. }
  926. layer {
  927.   name: "age/relu_4_1_pw"
  928.   type: "PReLU"
  929.   bottom: "age/conv_4_1_pw"
  930.   top: "age/conv_4_1_pw"
  931. }
  932. layer {
  933.   name: "age/conv_4_1_dw"
  934.   type: "ConvolutionDepthwise"
  935.   bottom: "age/conv_4_1_pw"
  936.   top: "age/conv_4_1_dw"
  937.   param {
  938.     lr_mult: 1.0
  939.     decay_mult: 1.0
  940.   }
  941.   convolution_param {
  942.     num_output: 192
  943.     bias_term: false
  944.     pad: 1
  945.     kernel_size: 3
  946.     stride: 2
  947.     weight_filler {
  948.       type: "msra"
  949.     }
  950.     bias_filler {
  951.       type: "constant"
  952.       value: 0.0
  953.     }
  954.   }
  955. }
  956. layer {
  957.   name: "age/bn_4_1_dw"
  958.   type: "BatchNorm"
  959.   bottom: "age/conv_4_1_dw"
  960.   top: "age/conv_4_1_dw"
  961.   param {
  962.     lr_mult: 0.0
  963.     decay_mult: 0.0
  964.   }
  965.   param {
  966.     lr_mult: 0.0
  967.     decay_mult: 0.0
  968.   }
  969.   param {
  970.     lr_mult: 0.0
  971.     decay_mult: 0.0
  972.   }
  973. }
  974. layer {
  975.   name: "age/scale_4_1_dw"
  976.   type: "Scale"
  977.   bottom: "age/conv_4_1_dw"
  978.   top: "age/conv_4_1_dw"
  979.   scale_param {
  980.     bias_term: true
  981.   }
  982. }
  983. layer {
  984.   name: "age/relu_4_1_dw"
  985.   type: "PReLU"
  986.   bottom: "age/conv_4_1_dw"
  987.   top: "age/conv_4_1_dw"
  988. }
  989. layer {
  990.   name: "age/conv_4_1_linear"
  991.   type: "Convolution"
  992.   bottom: "age/conv_4_1_dw"
  993.   top: "age/conv_4_1_linear"
  994.   param {
  995.     lr_mult: 1.0
  996.     decay_mult: 1.0
  997.   }
  998.   convolution_param {
  999.     num_output: 96
  1000.     bias_term: false
  1001.     pad: 0
  1002.     kernel_size: 1
  1003.     stride: 1
  1004.     weight_filler {
  1005.       type: "msra"
  1006.     }
  1007.     bias_filler {
  1008.       type: "constant"
  1009.       value: 0.0
  1010.     }
  1011.   }
  1012. }
  1013. layer {
  1014.   name: "age/bn_4_1_linear"
  1015.   type: "BatchNorm"
  1016.   bottom: "age/conv_4_1_linear"
  1017.   top: "age/conv_4_1_linear"
  1018.   param {
  1019.     lr_mult: 0.0
  1020.     decay_mult: 0.0
  1021.   }
  1022.   param {
  1023.     lr_mult: 0.0
  1024.     decay_mult: 0.0
  1025.   }
  1026.   param {
  1027.     lr_mult: 0.0
  1028.     decay_mult: 0.0
  1029.   }
  1030. }
  1031. layer {
  1032.   name: "age/scale_4_1_linear"
  1033.   type: "Scale"
  1034.   bottom: "age/conv_4_1_linear"
  1035.   top: "age/conv_4_1_linear"
  1036.   scale_param {
  1037.     bias_term: true
  1038.   }
  1039. }
  1040. layer {
  1041.   name: "age/conv_4_2_pw"
  1042.   type: "Convolution"
  1043.   bottom: "age/conv_4_1_linear"
  1044.   top: "age/conv_4_2_pw"
  1045.   param {
  1046.     lr_mult: 1.0
  1047.     decay_mult: 1.0
  1048.   }
  1049.   convolution_param {
  1050.     num_output: 192
  1051.     bias_term: false
  1052.     pad: 0
  1053.     kernel_size: 1
  1054.     stride: 1
  1055.     weight_filler {
  1056.       type: "msra"
  1057.     }
  1058.     bias_filler {
  1059.       type: "constant"
  1060.       value: 0.0
  1061.     }
  1062.   }
  1063. }
  1064. layer {
  1065.   name: "age/bn_4_2_pw"
  1066.   type: "BatchNorm"
  1067.   bottom: "age/conv_4_2_pw"
  1068.   top: "age/conv_4_2_pw"
  1069.   param {
  1070.     lr_mult: 0.0
  1071.     decay_mult: 0.0
  1072.   }
  1073.   param {
  1074.     lr_mult: 0.0
  1075.     decay_mult: 0.0
  1076.   }
  1077.   param {
  1078.     lr_mult: 0.0
  1079.     decay_mult: 0.0
  1080.   }
  1081. }
  1082. layer {
  1083.   name: "age/scale_4_2_pw"
  1084.   type: "Scale"
  1085.   bottom: "age/conv_4_2_pw"
  1086.   top: "age/conv_4_2_pw"
  1087.   scale_param {
  1088.     bias_term: true
  1089.   }
  1090. }
  1091. layer {
  1092.   name: "age/relu_4_2_pw"
  1093.   type: "PReLU"
  1094.   bottom: "age/conv_4_2_pw"
  1095.   top: "age/conv_4_2_pw"
  1096. }
  1097. layer {
  1098.   name: "age/conv_4_2_dw"
  1099.   type: "ConvolutionDepthwise"
  1100.   bottom: "age/conv_4_2_pw"
  1101.   top: "age/conv_4_2_dw"
  1102.   param {
  1103.     lr_mult: 1.0
  1104.     decay_mult: 1.0
  1105.   }
  1106.   convolution_param {
  1107.     num_output: 192
  1108.     bias_term: false
  1109.     pad: 1
  1110.     kernel_size: 3
  1111.     stride: 1
  1112.     weight_filler {
  1113.       type: "msra"
  1114.     }
  1115.     bias_filler {
  1116.       type: "constant"
  1117.       value: 0.0
  1118.     }
  1119.   }
  1120. }
  1121. layer {
  1122.   name: "age/bn_4_2_dw"
  1123.   type: "BatchNorm"
  1124.   bottom: "age/conv_4_2_dw"
  1125.   top: "age/conv_4_2_dw"
  1126.   param {
  1127.     lr_mult: 0.0
  1128.     decay_mult: 0.0
  1129.   }
  1130.   param {
  1131.     lr_mult: 0.0
  1132.     decay_mult: 0.0
  1133.   }
  1134.   param {
  1135.     lr_mult: 0.0
  1136.     decay_mult: 0.0
  1137.   }
  1138. }
  1139. layer {
  1140.   name: "age/scale_4_2_dw"
  1141.   type: "Scale"
  1142.   bottom: "age/conv_4_2_dw"
  1143.   top: "age/conv_4_2_dw"
  1144.   scale_param {
  1145.     bias_term: true
  1146.   }
  1147. }
  1148. layer {
  1149.   name: "age/relu_4_2_dw"
  1150.   type: "PReLU"
  1151.   bottom: "age/conv_4_2_dw"
  1152.   top: "age/conv_4_2_dw"
  1153. }
  1154. layer {
  1155.   name: "age/conv_4_2_linear"
  1156.   type: "Convolution"
  1157.   bottom: "age/conv_4_2_dw"
  1158.   top: "age/conv_4_2_linear"
  1159.   param {
  1160.     lr_mult: 1.0
  1161.     decay_mult: 1.0
  1162.   }
  1163.   convolution_param {
  1164.     num_output: 96
  1165.     bias_term: false
  1166.     pad: 0
  1167.     kernel_size: 1
  1168.     stride: 1
  1169.     weight_filler {
  1170.       type: "msra"
  1171.     }
  1172.     bias_filler {
  1173.       type: "constant"
  1174.       value: 0.0
  1175.     }
  1176.   }
  1177. }
  1178. layer {
  1179.   name: "age/bn_4_2_linear"
  1180.   type: "BatchNorm"
  1181.   bottom: "age/conv_4_2_linear"
  1182.   top: "age/conv_4_2_linear"
  1183.   param {
  1184.     lr_mult: 0.0
  1185.     decay_mult: 0.0
  1186.   }
  1187.   param {
  1188.     lr_mult: 0.0
  1189.     decay_mult: 0.0
  1190.   }
  1191.   param {
  1192.     lr_mult: 0.0
  1193.     decay_mult: 0.0
  1194.   }
  1195. }
  1196. layer {
  1197.   name: "age/scale_4_2_linear"
  1198.   type: "Scale"
  1199.   bottom: "age/conv_4_2_linear"
  1200.   top: "age/conv_4_2_linear"
  1201.   scale_param {
  1202.     bias_term: true
  1203.   }
  1204. }
  1205. layer {
  1206.   name: "age/add_4_2"
  1207.   type: "Eltwise"
  1208.   bottom: "age/conv_4_1_linear"
  1209.   bottom: "age/conv_4_2_linear"
  1210.   top: "age/add_4_2"
  1211. }
  1212.  
  1213. layer {
  1214.   name: "age/ip1"
  1215.   type: "InnerProduct"
  1216.   bottom: "age/add_4_2"
  1217.   top: "age/ip1"
  1218.   param {
  1219.     lr_mult: 1
  1220.   }
  1221.   param {
  1222.     lr_mult: 2
  1223.   }
  1224.   inner_product_param {
  1225.     num_output: 96
  1226.     weight_filler {
  1227.       type: "xavier"
  1228.     }
  1229.     bias_filler {
  1230.       type: "constant"
  1231.     }
  1232.   }
  1233. }
  1234. layer {
  1235.   name: "age/ip2"
  1236.   type: "InnerProduct"
  1237.   bottom: "age/ip1"
  1238.   top: "age/ip2"
  1239.   param {
  1240.     lr_mult: 1
  1241.   }
  1242.   param {
  1243.     lr_mult: 2
  1244.   }
  1245.   inner_product_param {
  1246.     num_output: 1
  1247.     weight_filler {
  1248.       type: "xavier"
  1249.     }
  1250.     bias_filler {
  1251.       type: "constant"
  1252.     }
  1253.   }
  1254. }
  1255.  
  1256.  
  1257. layer {
  1258.   name: "emotion/conv_4_1_pw"
  1259.   type: "Convolution"
  1260.   bottom: "add_6_1"
  1261.   top: "emotion/conv_4_1_pw"
  1262.   param {
  1263.     lr_mult: 1.0
  1264.     decay_mult: 1.0
  1265.   }
  1266.   convolution_param {
  1267.     num_output: 192
  1268.     bias_term: false
  1269.     pad: 0
  1270.     kernel_size: 1
  1271.     stride: 1
  1272.     weight_filler {
  1273.       type: "msra"
  1274.     }
  1275.     bias_filler {
  1276.       type: "constant"
  1277.       value: 0.0
  1278.     }
  1279.   }
  1280. }
  1281. layer {
  1282.   name: "emotion/bn_4_1_pw"
  1283.   type: "BatchNorm"
  1284.   bottom: "emotion/conv_4_1_pw"
  1285.   top: "emotion/conv_4_1_pw"
  1286.   param {
  1287.     lr_mult: 0.0
  1288.     decay_mult: 0.0
  1289.   }
  1290.   param {
  1291.     lr_mult: 0.0
  1292.     decay_mult: 0.0
  1293.   }
  1294.   param {
  1295.     lr_mult: 0.0
  1296.     decay_mult: 0.0
  1297.   }
  1298. }
  1299. layer {
  1300.   name: "emotion/scale_4_1_pw"
  1301.   type: "Scale"
  1302.   bottom: "emotion/conv_4_1_pw"
  1303.   top: "emotion/conv_4_1_pw"
  1304.   scale_param {
  1305.     bias_term: true
  1306.   }
  1307. }
  1308. layer {
  1309.   name: "emotion/relu_4_1_pw"
  1310.   type: "PReLU"
  1311.   bottom: "emotion/conv_4_1_pw"
  1312.   top: "emotion/conv_4_1_pw"
  1313. }
  1314. layer {
  1315.   name: "emotion/conv_4_1_dw"
  1316.   type: "ConvolutionDepthwise"
  1317.   bottom: "emotion/conv_4_1_pw"
  1318.   top: "emotion/conv_4_1_dw"
  1319.   param {
  1320.     lr_mult: 1.0
  1321.     decay_mult: 1.0
  1322.   }
  1323.   convolution_param {
  1324.     num_output: 192
  1325.     bias_term: false
  1326.     pad: 1
  1327.     kernel_size: 3
  1328.     stride: 2
  1329.     weight_filler {
  1330.       type: "msra"
  1331.     }
  1332.     bias_filler {
  1333.       type: "constant"
  1334.       value: 0.0
  1335.     }
  1336.   }
  1337. }
  1338. layer {
  1339.   name: "emotion/bn_4_1_dw"
  1340.   type: "BatchNorm"
  1341.   bottom: "emotion/conv_4_1_dw"
  1342.   top: "emotion/conv_4_1_dw"
  1343.   param {
  1344.     lr_mult: 0.0
  1345.     decay_mult: 0.0
  1346.   }
  1347.   param {
  1348.     lr_mult: 0.0
  1349.     decay_mult: 0.0
  1350.   }
  1351.   param {
  1352.     lr_mult: 0.0
  1353.     decay_mult: 0.0
  1354.   }
  1355. }
  1356. layer {
  1357.   name: "emotion/scale_4_1_dw"
  1358.   type: "Scale"
  1359.   bottom: "emotion/conv_4_1_dw"
  1360.   top: "emotion/conv_4_1_dw"
  1361.   scale_param {
  1362.     bias_term: true
  1363.   }
  1364. }
  1365. layer {
  1366.   name: "emotion/relu_4_1_dw"
  1367.   type: "PReLU"
  1368.   bottom: "emotion/conv_4_1_dw"
  1369.   top: "emotion/conv_4_1_dw"
  1370. }
  1371. layer {
  1372.   name: "emotion/conv_4_1_linear"
  1373.   type: "Convolution"
  1374.   bottom: "emotion/conv_4_1_dw"
  1375.   top: "emotion/conv_4_1_linear"
  1376.   param {
  1377.     lr_mult: 1.0
  1378.     decay_mult: 1.0
  1379.   }
  1380.   convolution_param {
  1381.     num_output: 96
  1382.     bias_term: false
  1383.     pad: 0
  1384.     kernel_size: 1
  1385.     stride: 1
  1386.     weight_filler {
  1387.       type: "msra"
  1388.     }
  1389.     bias_filler {
  1390.       type: "constant"
  1391.       value: 0.0
  1392.     }
  1393.   }
  1394. }
  1395. layer {
  1396.   name: "emotion/bn_4_1_linear"
  1397.   type: "BatchNorm"
  1398.   bottom: "emotion/conv_4_1_linear"
  1399.   top: "emotion/conv_4_1_linear"
  1400.   param {
  1401.     lr_mult: 0.0
  1402.     decay_mult: 0.0
  1403.   }
  1404.   param {
  1405.     lr_mult: 0.0
  1406.     decay_mult: 0.0
  1407.   }
  1408.   param {
  1409.     lr_mult: 0.0
  1410.     decay_mult: 0.0
  1411.   }
  1412. }
  1413. layer {
  1414.   name: "emotion/scale_4_1_linear"
  1415.   type: "Scale"
  1416.   bottom: "emotion/conv_4_1_linear"
  1417.   top: "emotion/conv_4_1_linear"
  1418.   scale_param {
  1419.     bias_term: true
  1420.   }
  1421. }
  1422. layer {
  1423.   name: "emotion/conv_4_2_pw"
  1424.   type: "Convolution"
  1425.   bottom: "emotion/conv_4_1_linear"
  1426.   top: "emotion/conv_4_2_pw"
  1427.   param {
  1428.     lr_mult: 1.0
  1429.     decay_mult: 1.0
  1430.   }
  1431.   convolution_param {
  1432.     num_output: 192
  1433.     bias_term: false
  1434.     pad: 0
  1435.     kernel_size: 1
  1436.     stride: 1
  1437.     weight_filler {
  1438.       type: "msra"
  1439.     }
  1440.     bias_filler {
  1441.       type: "constant"
  1442.       value: 0.0
  1443.     }
  1444.   }
  1445. }
  1446. layer {
  1447.   name: "emotion/bn_4_2_pw"
  1448.   type: "BatchNorm"
  1449.   bottom: "emotion/conv_4_2_pw"
  1450.   top: "emotion/conv_4_2_pw"
  1451.   param {
  1452.     lr_mult: 0.0
  1453.     decay_mult: 0.0
  1454.   }
  1455.   param {
  1456.     lr_mult: 0.0
  1457.     decay_mult: 0.0
  1458.   }
  1459.   param {
  1460.     lr_mult: 0.0
  1461.     decay_mult: 0.0
  1462.   }
  1463. }
  1464. layer {
  1465.   name: "emotion/scale_4_2_pw"
  1466.   type: "Scale"
  1467.   bottom: "emotion/conv_4_2_pw"
  1468.   top: "emotion/conv_4_2_pw"
  1469.   scale_param {
  1470.     bias_term: true
  1471.   }
  1472. }
  1473. layer {
  1474.   name: "emotion/relu_4_2_pw"
  1475.   type: "PReLU"
  1476.   bottom: "emotion/conv_4_2_pw"
  1477.   top: "emotion/conv_4_2_pw"
  1478. }
  1479. layer {
  1480.   name: "emotion/conv_4_2_dw"
  1481.   type: "ConvolutionDepthwise"
  1482.   bottom: "emotion/conv_4_2_pw"
  1483.   top: "emotion/conv_4_2_dw"
  1484.   param {
  1485.     lr_mult: 1.0
  1486.     decay_mult: 1.0
  1487.   }
  1488.   convolution_param {
  1489.     num_output: 192
  1490.     bias_term: false
  1491.     pad: 1
  1492.     kernel_size: 3
  1493.     stride: 1
  1494.     weight_filler {
  1495.       type: "msra"
  1496.     }
  1497.     bias_filler {
  1498.       type: "constant"
  1499.       value: 0.0
  1500.     }
  1501.   }
  1502. }
  1503. layer {
  1504.   name: "emotion/bn_4_2_dw"
  1505.   type: "BatchNorm"
  1506.   bottom: "emotion/conv_4_2_dw"
  1507.   top: "emotion/conv_4_2_dw"
  1508.   param {
  1509.     lr_mult: 0.0
  1510.     decay_mult: 0.0
  1511.   }
  1512.   param {
  1513.     lr_mult: 0.0
  1514.     decay_mult: 0.0
  1515.   }
  1516.   param {
  1517.     lr_mult: 0.0
  1518.     decay_mult: 0.0
  1519.   }
  1520. }
  1521. layer {
  1522.   name: "emotion/scale_4_2_dw"
  1523.   type: "Scale"
  1524.   bottom: "emotion/conv_4_2_dw"
  1525.   top: "emotion/conv_4_2_dw"
  1526.   scale_param {
  1527.     bias_term: true
  1528.   }
  1529. }
  1530. layer {
  1531.   name: "emotion/relu_4_2_dw"
  1532.   type: "PReLU"
  1533.   bottom: "emotion/conv_4_2_dw"
  1534.   top: "emotion/conv_4_2_dw"
  1535. }
  1536. layer {
  1537.   name: "emotion/conv_4_2_linear"
  1538.   type: "Convolution"
  1539.   bottom: "emotion/conv_4_2_dw"
  1540.   top: "emotion/conv_4_2_linear"
  1541.   param {
  1542.     lr_mult: 1.0
  1543.     decay_mult: 1.0
  1544.   }
  1545.   convolution_param {
  1546.     num_output: 96
  1547.     bias_term: false
  1548.     pad: 0
  1549.     kernel_size: 1
  1550.     stride: 1
  1551.     weight_filler {
  1552.       type: "msra"
  1553.     }
  1554.     bias_filler {
  1555.       type: "constant"
  1556.       value: 0.0
  1557.     }
  1558.   }
  1559. }
  1560. layer {
  1561.   name: "emotion/bn_4_2_linear"
  1562.   type: "BatchNorm"
  1563.   bottom: "emotion/conv_4_2_linear"
  1564.   top: "emotion/conv_4_2_linear"
  1565.   param {
  1566.     lr_mult: 0.0
  1567.     decay_mult: 0.0
  1568.   }
  1569.   param {
  1570.     lr_mult: 0.0
  1571.     decay_mult: 0.0
  1572.   }
  1573.   param {
  1574.     lr_mult: 0.0
  1575.     decay_mult: 0.0
  1576.   }
  1577. }
  1578. layer {
  1579.   name: "emotion/scale_4_2_linear"
  1580.   type: "Scale"
  1581.   bottom: "emotion/conv_4_2_linear"
  1582.   top: "emotion/conv_4_2_linear"
  1583.   scale_param {
  1584.     bias_term: true
  1585.   }
  1586. }
  1587. layer {
  1588.   name: "emotion/add_4_2"
  1589.   type: "Eltwise"
  1590.   bottom: "emotion/conv_4_1_linear"
  1591.   bottom: "emotion/conv_4_2_linear"
  1592.   top: "emotion/add_4_2"
  1593. }
  1594.  
  1595. layer {
  1596.   name: "emotion/conv1_"
  1597.   type: "Convolution"
  1598.   bottom: "emotion/add_4_2"
  1599.   top: "emotion/conv1_"
  1600.   param {
  1601.     lr_mult: 1
  1602.     decay_mult: 1
  1603.   }
  1604.   param {
  1605.     lr_mult: 2
  1606.     decay_mult: 0
  1607.   }
  1608.   convolution_param {
  1609.     num_output: 128
  1610.     kernel_size: 3
  1611.     stride: 1
  1612.     weight_filler {
  1613.       type: "xavier"
  1614.     }
  1615.     bias_filler {
  1616.       type: "constant"
  1617.       value: 0
  1618.     }
  1619.   }
  1620. }
  1621. layer {
  1622.   name: "emotion/relu1_"
  1623.   type: "PReLU"
  1624.   bottom: "emotion/conv1_"
  1625.   top: "emotion/conv1_"
  1626. }
  1627. layer {
  1628.   name: "emotion/pool1_"
  1629.   type: "Pooling"
  1630.   bottom: "emotion/conv1_"
  1631.   top: "emotion/pool1_"
  1632.   pooling_param {
  1633.     pool: AVE
  1634.     kernel_size: 4
  1635.     stride: 4
  1636.   }
  1637. }
  1638. layer {
  1639.   name: "emotion/ip1"
  1640.   type: "InnerProduct"
  1641.   bottom: "emotion/pool1_"
  1642.   top: "emotion/ip1"
  1643.   param {
  1644.     lr_mult: 1
  1645.   }
  1646.   param {
  1647.     lr_mult: 2
  1648.   }
  1649.   inner_product_param {
  1650.     num_output: 3
  1651.     weight_filler {
  1652.       type: "xavier"
  1653.     }
  1654.     bias_filler {
  1655.       type: "constant"
  1656.     }
  1657.   }
  1658. }
  1659.  
  1660. layer {
  1661.   name: "sex/conv_4_1_pw"
  1662.   type: "Convolution"
  1663.   bottom: "add_6_1"
  1664.   top: "sex/conv_4_1_pw"
  1665.   param {
  1666.     lr_mult: 1.0
  1667.     decay_mult: 1.0
  1668.   }
  1669.   convolution_param {
  1670.     num_output: 192
  1671.     bias_term: false
  1672.     pad: 0
  1673.     kernel_size: 1
  1674.     stride: 1
  1675.     weight_filler {
  1676.       type: "msra"
  1677.     }
  1678.     bias_filler {
  1679.       type: "constant"
  1680.       value: 0.0
  1681.     }
  1682.   }
  1683. }
  1684. layer {
  1685.   name: "sex/bn_4_1_pw"
  1686.   type: "BatchNorm"
  1687.   bottom: "sex/conv_4_1_pw"
  1688.   top: "sex/conv_4_1_pw"
  1689.   param {
  1690.     lr_mult: 0.0
  1691.     decay_mult: 0.0
  1692.   }
  1693.   param {
  1694.     lr_mult: 0.0
  1695.     decay_mult: 0.0
  1696.   }
  1697.   param {
  1698.     lr_mult: 0.0
  1699.     decay_mult: 0.0
  1700.   }
  1701. }
  1702. layer {
  1703.   name: "sex/scale_4_1_pw"
  1704.   type: "Scale"
  1705.   bottom: "sex/conv_4_1_pw"
  1706.   top: "sex/conv_4_1_pw"
  1707.   scale_param {
  1708.     bias_term: true
  1709.   }
  1710. }
  1711. layer {
  1712.   name: "sex/relu_4_1_pw"
  1713.   type: "PReLU"
  1714.   bottom: "sex/conv_4_1_pw"
  1715.   top: "sex/conv_4_1_pw"
  1716. }
  1717. layer {
  1718.   name: "sex/conv_4_1_dw"
  1719.   type: "ConvolutionDepthwise"
  1720.   bottom: "sex/conv_4_1_pw"
  1721.   top: "sex/conv_4_1_dw"
  1722.   param {
  1723.     lr_mult: 1.0
  1724.     decay_mult: 1.0
  1725.   }
  1726.   convolution_param {
  1727.     num_output: 192
  1728.     bias_term: false
  1729.     pad: 1
  1730.     kernel_size: 3
  1731.     stride: 2
  1732.     weight_filler {
  1733.       type: "msra"
  1734.     }
  1735.     bias_filler {
  1736.       type: "constant"
  1737.       value: 0.0
  1738.     }
  1739.   }
  1740. }
  1741. layer {
  1742.   name: "sex/bn_4_1_dw"
  1743.   type: "BatchNorm"
  1744.   bottom: "sex/conv_4_1_dw"
  1745.   top: "sex/conv_4_1_dw"
  1746.   param {
  1747.     lr_mult: 0.0
  1748.     decay_mult: 0.0
  1749.   }
  1750.   param {
  1751.     lr_mult: 0.0
  1752.     decay_mult: 0.0
  1753.   }
  1754.   param {
  1755.     lr_mult: 0.0
  1756.     decay_mult: 0.0
  1757.   }
  1758. }
  1759. layer {
  1760.   name: "sex/scale_4_1_dw"
  1761.   type: "Scale"
  1762.   bottom: "sex/conv_4_1_dw"
  1763.   top: "sex/conv_4_1_dw"
  1764.   scale_param {
  1765.     bias_term: true
  1766.   }
  1767. }
  1768. layer {
  1769.   name: "sex/relu_4_1_dw"
  1770.   type: "PReLU"
  1771.   bottom: "sex/conv_4_1_dw"
  1772.   top: "sex/conv_4_1_dw"
  1773. }
  1774. layer {
  1775.   name: "sex/conv_4_1_linear"
  1776.   type: "Convolution"
  1777.   bottom: "sex/conv_4_1_dw"
  1778.   top: "sex/conv_4_1_linear"
  1779.   param {
  1780.     lr_mult: 1.0
  1781.     decay_mult: 1.0
  1782.   }
  1783.   convolution_param {
  1784.     num_output: 96
  1785.     bias_term: false
  1786.     pad: 0
  1787.     kernel_size: 1
  1788.     stride: 1
  1789.     weight_filler {
  1790.       type: "msra"
  1791.     }
  1792.     bias_filler {
  1793.       type: "constant"
  1794.       value: 0.0
  1795.     }
  1796.   }
  1797. }
  1798. layer {
  1799.   name: "sex/bn_4_1_linear"
  1800.   type: "BatchNorm"
  1801.   bottom: "sex/conv_4_1_linear"
  1802.   top: "sex/conv_4_1_linear"
  1803.   param {
  1804.     lr_mult: 0.0
  1805.     decay_mult: 0.0
  1806.   }
  1807.   param {
  1808.     lr_mult: 0.0
  1809.     decay_mult: 0.0
  1810.   }
  1811.   param {
  1812.     lr_mult: 0.0
  1813.     decay_mult: 0.0
  1814.   }
  1815. }
  1816. layer {
  1817.   name: "sex/scale_4_1_linear"
  1818.   type: "Scale"
  1819.   bottom: "sex/conv_4_1_linear"
  1820.   top: "sex/conv_4_1_linear"
  1821.   scale_param {
  1822.     bias_term: true
  1823.   }
  1824. }
  1825. layer {
  1826.   name: "sex/conv_4_2_pw"
  1827.   type: "Convolution"
  1828.   bottom: "sex/conv_4_1_linear"
  1829.   top: "sex/conv_4_2_pw"
  1830.   param {
  1831.     lr_mult: 1.0
  1832.     decay_mult: 1.0
  1833.   }
  1834.   convolution_param {
  1835.     num_output: 192
  1836.     bias_term: false
  1837.     pad: 0
  1838.     kernel_size: 1
  1839.     stride: 1
  1840.     weight_filler {
  1841.       type: "msra"
  1842.     }
  1843.     bias_filler {
  1844.       type: "constant"
  1845.       value: 0.0
  1846.     }
  1847.   }
  1848. }
  1849. layer {
  1850.   name: "sex/bn_4_2_pw"
  1851.   type: "BatchNorm"
  1852.   bottom: "sex/conv_4_2_pw"
  1853.   top: "sex/conv_4_2_pw"
  1854.   param {
  1855.     lr_mult: 0.0
  1856.     decay_mult: 0.0
  1857.   }
  1858.   param {
  1859.     lr_mult: 0.0
  1860.     decay_mult: 0.0
  1861.   }
  1862.   param {
  1863.     lr_mult: 0.0
  1864.     decay_mult: 0.0
  1865.   }
  1866. }
  1867. layer {
  1868.   name: "sex/scale_4_2_pw"
  1869.   type: "Scale"
  1870.   bottom: "sex/conv_4_2_pw"
  1871.   top: "sex/conv_4_2_pw"
  1872.   scale_param {
  1873.     bias_term: true
  1874.   }
  1875. }
  1876. layer {
  1877.   name: "sex/relu_4_2_pw"
  1878.   type: "PReLU"
  1879.   bottom: "sex/conv_4_2_pw"
  1880.   top: "sex/conv_4_2_pw"
  1881. }
  1882. layer {
  1883.   name: "sex/conv_4_2_dw"
  1884.   type: "ConvolutionDepthwise"
  1885.   bottom: "sex/conv_4_2_pw"
  1886.   top: "sex/conv_4_2_dw"
  1887.   param {
  1888.     lr_mult: 1.0
  1889.     decay_mult: 1.0
  1890.   }
  1891.   convolution_param {
  1892.     num_output: 192
  1893.     bias_term: false
  1894.     pad: 1
  1895.     kernel_size: 3
  1896.     stride: 1
  1897.     weight_filler {
  1898.       type: "msra"
  1899.     }
  1900.     bias_filler {
  1901.       type: "constant"
  1902.       value: 0.0
  1903.     }
  1904.   }
  1905. }
  1906. layer {
  1907.   name: "sex/bn_4_2_dw"
  1908.   type: "BatchNorm"
  1909.   bottom: "sex/conv_4_2_dw"
  1910.   top: "sex/conv_4_2_dw"
  1911.   param {
  1912.     lr_mult: 0.0
  1913.     decay_mult: 0.0
  1914.   }
  1915.   param {
  1916.     lr_mult: 0.0
  1917.     decay_mult: 0.0
  1918.   }
  1919.   param {
  1920.     lr_mult: 0.0
  1921.     decay_mult: 0.0
  1922.   }
  1923. }
  1924. layer {
  1925.   name: "sex/scale_4_2_dw"
  1926.   type: "Scale"
  1927.   bottom: "sex/conv_4_2_dw"
  1928.   top: "sex/conv_4_2_dw"
  1929.   scale_param {
  1930.     bias_term: true
  1931.   }
  1932. }
  1933. layer {
  1934.   name: "sex/relu_4_2_dw"
  1935.   type: "PReLU"
  1936.   bottom: "sex/conv_4_2_dw"
  1937.   top: "sex/conv_4_2_dw"
  1938. }
  1939. layer {
  1940.   name: "sex/conv_4_2_linear"
  1941.   type: "Convolution"
  1942.   bottom: "sex/conv_4_2_dw"
  1943.   top: "sex/conv_4_2_linear"
  1944.   param {
  1945.     lr_mult: 1.0
  1946.     decay_mult: 1.0
  1947.   }
  1948.   convolution_param {
  1949.     num_output: 96
  1950.     bias_term: false
  1951.     pad: 0
  1952.     kernel_size: 1
  1953.     stride: 1
  1954.     weight_filler {
  1955.       type: "msra"
  1956.     }
  1957.     bias_filler {
  1958.       type: "constant"
  1959.       value: 0.0
  1960.     }
  1961.   }
  1962. }
  1963. layer {
  1964.   name: "sex/bn_4_2_linear"
  1965.   type: "BatchNorm"
  1966.   bottom: "sex/conv_4_2_linear"
  1967.   top: "sex/conv_4_2_linear"
  1968.   param {
  1969.     lr_mult: 0.0
  1970.     decay_mult: 0.0
  1971.   }
  1972.   param {
  1973.     lr_mult: 0.0
  1974.     decay_mult: 0.0
  1975.   }
  1976.   param {
  1977.     lr_mult: 0.0
  1978.     decay_mult: 0.0
  1979.   }
  1980. }
  1981. layer {
  1982.   name: "sex/scale_4_2_linear"
  1983.   type: "Scale"
  1984.   bottom: "sex/conv_4_2_linear"
  1985.   top: "sex/conv_4_2_linear"
  1986.   scale_param {
  1987.     bias_term: true
  1988.   }
  1989. }
  1990. layer {
  1991.   name: "sex/add_4_2"
  1992.   type: "Eltwise"
  1993.   bottom: "sex/conv_4_1_linear"
  1994.   bottom: "sex/conv_4_2_linear"
  1995.   top: "sex/add_4_2"
  1996. }
  1997.  
  1998. layer {
  1999.   name: "sex/conv1_"
  2000.   type: "Convolution"
  2001.   bottom: "sex/add_4_2"
  2002.   top: "sex/conv1_"
  2003.   param {
  2004.     lr_mult: 1
  2005.     decay_mult: 1
  2006.   }
  2007.   param {
  2008.     lr_mult: 2
  2009.     decay_mult: 0
  2010.   }
  2011.   convolution_param {
  2012.     num_output: 128
  2013.     kernel_size: 3
  2014.     stride: 1
  2015.     weight_filler {
  2016.       type: "xavier"
  2017.     }
  2018.     bias_filler {
  2019.       type: "constant"
  2020.       value: 0
  2021.     }
  2022.   }
  2023. }
  2024. layer {
  2025.   name: "sex/relu1_"
  2026.   type: "PReLU"
  2027.   bottom: "sex/conv1_"
  2028.   top: "sex/conv1_"
  2029. }
  2030. layer {
  2031.   name: "sex/pool1_"
  2032.   type: "Pooling"
  2033.   bottom: "sex/conv1_"
  2034.   top: "sex/pool1_"
  2035.   pooling_param {
  2036.     pool: AVE
  2037.     kernel_size: 4
  2038.     stride: 4
  2039.   }
  2040. }
  2041. layer {
  2042.   name: "sex/ip1"
  2043.   type: "InnerProduct"
  2044.   bottom: "sex/pool1_"
  2045.   top: "sex/ip1"
  2046.   param {
  2047.     lr_mult: 1
  2048.   }
  2049.   param {
  2050.     lr_mult: 2
  2051.   }
  2052.   inner_product_param {
  2053.     num_output: 2
  2054.     weight_filler {
  2055.       type: "xavier"
  2056.     }
  2057.     bias_filler {
  2058.       type: "constant"
  2059.     }
  2060.   }
  2061. }
  2062.  
  2063.  
  2064. layer {
  2065.   name: "glass/conv_4_1_pw"
  2066.   type: "Convolution"
  2067.   bottom: "add_6_1"
  2068.   top: "glass/conv_4_1_pw"
  2069.   param {
  2070.     lr_mult: 1.0
  2071.     decay_mult: 1.0
  2072.   }
  2073.   convolution_param {
  2074.     num_output: 192
  2075.     bias_term: false
  2076.     pad: 0
  2077.     kernel_size: 1
  2078.     stride: 1
  2079.     weight_filler {
  2080.       type: "msra"
  2081.     }
  2082.     bias_filler {
  2083.       type: "constant"
  2084.       value: 0.0
  2085.     }
  2086.   }
  2087. }
  2088. layer {
  2089.   name: "glass/bn_4_1_pw"
  2090.   type: "BatchNorm"
  2091.   bottom: "glass/conv_4_1_pw"
  2092.   top: "glass/conv_4_1_pw"
  2093.   param {
  2094.     lr_mult: 0.0
  2095.     decay_mult: 0.0
  2096.   }
  2097.   param {
  2098.     lr_mult: 0.0
  2099.     decay_mult: 0.0
  2100.   }
  2101.   param {
  2102.     lr_mult: 0.0
  2103.     decay_mult: 0.0
  2104.   }
  2105. }
  2106. layer {
  2107.   name: "glass/scale_4_1_pw"
  2108.   type: "Scale"
  2109.   bottom: "glass/conv_4_1_pw"
  2110.   top: "glass/conv_4_1_pw"
  2111.   scale_param {
  2112.     bias_term: true
  2113.   }
  2114. }
  2115. layer {
  2116.   name: "glass/relu_4_1_pw"
  2117.   type: "PReLU"
  2118.   bottom: "glass/conv_4_1_pw"
  2119.   top: "glass/conv_4_1_pw"
  2120. }
  2121. layer {
  2122.   name: "glass/conv_4_1_dw"
  2123.   type: "ConvolutionDepthwise"
  2124.   bottom: "glass/conv_4_1_pw"
  2125.   top: "glass/conv_4_1_dw"
  2126.   param {
  2127.     lr_mult: 1.0
  2128.     decay_mult: 1.0
  2129.   }
  2130.   convolution_param {
  2131.     num_output: 192
  2132.     bias_term: false
  2133.     pad: 1
  2134.     kernel_size: 3
  2135.     stride: 2
  2136.     weight_filler {
  2137.       type: "msra"
  2138.     }
  2139.     bias_filler {
  2140.       type: "constant"
  2141.       value: 0.0
  2142.     }
  2143.   }
  2144. }
  2145. layer {
  2146.   name: "glass/bn_4_1_dw"
  2147.   type: "BatchNorm"
  2148.   bottom: "glass/conv_4_1_dw"
  2149.   top: "glass/conv_4_1_dw"
  2150.   param {
  2151.     lr_mult: 0.0
  2152.     decay_mult: 0.0
  2153.   }
  2154.   param {
  2155.     lr_mult: 0.0
  2156.     decay_mult: 0.0
  2157.   }
  2158.   param {
  2159.     lr_mult: 0.0
  2160.     decay_mult: 0.0
  2161.   }
  2162. }
  2163. layer {
  2164.   name: "glass/scale_4_1_dw"
  2165.   type: "Scale"
  2166.   bottom: "glass/conv_4_1_dw"
  2167.   top: "glass/conv_4_1_dw"
  2168.   scale_param {
  2169.     bias_term: true
  2170.   }
  2171. }
  2172. layer {
  2173.   name: "glass/relu_4_1_dw"
  2174.   type: "PReLU"
  2175.   bottom: "glass/conv_4_1_dw"
  2176.   top: "glass/conv_4_1_dw"
  2177. }
  2178. layer {
  2179.   name: "glass/conv_4_1_linear"
  2180.   type: "Convolution"
  2181.   bottom: "glass/conv_4_1_dw"
  2182.   top: "glass/conv_4_1_linear"
  2183.   param {
  2184.     lr_mult: 1.0
  2185.     decay_mult: 1.0
  2186.   }
  2187.   convolution_param {
  2188.     num_output: 96
  2189.     bias_term: false
  2190.     pad: 0
  2191.     kernel_size: 1
  2192.     stride: 1
  2193.     weight_filler {
  2194.       type: "msra"
  2195.     }
  2196.     bias_filler {
  2197.       type: "constant"
  2198.       value: 0.0
  2199.     }
  2200.   }
  2201. }
  2202. layer {
  2203.   name: "glass/bn_4_1_linear"
  2204.   type: "BatchNorm"
  2205.   bottom: "glass/conv_4_1_linear"
  2206.   top: "glass/conv_4_1_linear"
  2207.   param {
  2208.     lr_mult: 0.0
  2209.     decay_mult: 0.0
  2210.   }
  2211.   param {
  2212.     lr_mult: 0.0
  2213.     decay_mult: 0.0
  2214.   }
  2215.   param {
  2216.     lr_mult: 0.0
  2217.     decay_mult: 0.0
  2218.   }
  2219. }
  2220. layer {
  2221.   name: "glass/scale_4_1_linear"
  2222.   type: "Scale"
  2223.   bottom: "glass/conv_4_1_linear"
  2224.   top: "glass/conv_4_1_linear"
  2225.   scale_param {
  2226.     bias_term: true
  2227.   }
  2228. }
  2229. layer {
  2230.   name: "glass/conv_4_2_pw"
  2231.   type: "Convolution"
  2232.   bottom: "glass/conv_4_1_linear"
  2233.   top: "glass/conv_4_2_pw"
  2234.   param {
  2235.     lr_mult: 1.0
  2236.     decay_mult: 1.0
  2237.   }
  2238.   convolution_param {
  2239.     num_output: 192
  2240.     bias_term: false
  2241.     pad: 0
  2242.     kernel_size: 1
  2243.     stride: 1
  2244.     weight_filler {
  2245.       type: "msra"
  2246.     }
  2247.     bias_filler {
  2248.       type: "constant"
  2249.       value: 0.0
  2250.     }
  2251.   }
  2252. }
  2253. layer {
  2254.   name: "glass/bn_4_2_pw"
  2255.   type: "BatchNorm"
  2256.   bottom: "glass/conv_4_2_pw"
  2257.   top: "glass/conv_4_2_pw"
  2258.   param {
  2259.     lr_mult: 0.0
  2260.     decay_mult: 0.0
  2261.   }
  2262.   param {
  2263.     lr_mult: 0.0
  2264.     decay_mult: 0.0
  2265.   }
  2266.   param {
  2267.     lr_mult: 0.0
  2268.     decay_mult: 0.0
  2269.   }
  2270. }
  2271. layer {
  2272.   name: "glass/scale_4_2_pw"
  2273.   type: "Scale"
  2274.   bottom: "glass/conv_4_2_pw"
  2275.   top: "glass/conv_4_2_pw"
  2276.   scale_param {
  2277.     bias_term: true
  2278.   }
  2279. }
  2280. layer {
  2281.   name: "glass/relu_4_2_pw"
  2282.   type: "PReLU"
  2283.   bottom: "glass/conv_4_2_pw"
  2284.   top: "glass/conv_4_2_pw"
  2285. }
  2286. layer {
  2287.   name: "glass/conv_4_2_dw"
  2288.   type: "ConvolutionDepthwise"
  2289.   bottom: "glass/conv_4_2_pw"
  2290.   top: "glass/conv_4_2_dw"
  2291.   param {
  2292.     lr_mult: 1.0
  2293.     decay_mult: 1.0
  2294.   }
  2295.   convolution_param {
  2296.     num_output: 192
  2297.     bias_term: false
  2298.     pad: 1
  2299.     kernel_size: 3
  2300.     stride: 1
  2301.     weight_filler {
  2302.       type: "msra"
  2303.     }
  2304.     bias_filler {
  2305.       type: "constant"
  2306.       value: 0.0
  2307.     }
  2308.   }
  2309. }
  2310. layer {
  2311.   name: "glass/bn_4_2_dw"
  2312.   type: "BatchNorm"
  2313.   bottom: "glass/conv_4_2_dw"
  2314.   top: "glass/conv_4_2_dw"
  2315.   param {
  2316.     lr_mult: 0.0
  2317.     decay_mult: 0.0
  2318.   }
  2319.   param {
  2320.     lr_mult: 0.0
  2321.     decay_mult: 0.0
  2322.   }
  2323.   param {
  2324.     lr_mult: 0.0
  2325.     decay_mult: 0.0
  2326.   }
  2327. }
  2328. layer {
  2329.   name: "glass/scale_4_2_dw"
  2330.   type: "Scale"
  2331.   bottom: "glass/conv_4_2_dw"
  2332.   top: "glass/conv_4_2_dw"
  2333.   scale_param {
  2334.     bias_term: true
  2335.   }
  2336. }
  2337. layer {
  2338.   name: "glass/relu_4_2_dw"
  2339.   type: "PReLU"
  2340.   bottom: "glass/conv_4_2_dw"
  2341.   top: "glass/conv_4_2_dw"
  2342. }
  2343. layer {
  2344.   name: "glass/conv_4_2_linear"
  2345.   type: "Convolution"
  2346.   bottom: "glass/conv_4_2_dw"
  2347.   top: "glass/conv_4_2_linear"
  2348.   param {
  2349.     lr_mult: 1.0
  2350.     decay_mult: 1.0
  2351.   }
  2352.   convolution_param {
  2353.     num_output: 96
  2354.     bias_term: false
  2355.     pad: 0
  2356.     kernel_size: 1
  2357.     stride: 1
  2358.     weight_filler {
  2359.       type: "msra"
  2360.     }
  2361.     bias_filler {
  2362.       type: "constant"
  2363.       value: 0.0
  2364.     }
  2365.   }
  2366. }
  2367. layer {
  2368.   name: "glass/bn_4_2_linear"
  2369.   type: "BatchNorm"
  2370.   bottom: "glass/conv_4_2_linear"
  2371.   top: "glass/conv_4_2_linear"
  2372.   param {
  2373.     lr_mult: 0.0
  2374.     decay_mult: 0.0
  2375.   }
  2376.   param {
  2377.     lr_mult: 0.0
  2378.     decay_mult: 0.0
  2379.   }
  2380.   param {
  2381.     lr_mult: 0.0
  2382.     decay_mult: 0.0
  2383.   }
  2384. }
  2385. layer {
  2386.   name: "glass/scale_4_2_linear"
  2387.   type: "Scale"
  2388.   bottom: "glass/conv_4_2_linear"
  2389.   top: "glass/conv_4_2_linear"
  2390.   scale_param {
  2391.     bias_term: true
  2392.   }
  2393. }
  2394. layer {
  2395.   name: "glass/add_4_2"
  2396.   type: "Eltwise"
  2397.   bottom: "glass/conv_4_1_linear"
  2398.   bottom: "glass/conv_4_2_linear"
  2399.   top: "glass/add_4_2"
  2400. }
  2401.  
  2402. layer {
  2403.   name: "glass/conv1_"
  2404.   type: "Convolution"
  2405.   bottom: "glass/add_4_2"
  2406.   top: "glass/conv1_"
  2407.   param {
  2408.     lr_mult: 1
  2409.     decay_mult: 1
  2410.   }
  2411.   param {
  2412.     lr_mult: 2
  2413.     decay_mult: 0
  2414.   }
  2415.   convolution_param {
  2416.     num_output: 128
  2417.     kernel_size: 3
  2418.     stride: 1
  2419.     weight_filler {
  2420.       type: "xavier"
  2421.     }
  2422.     bias_filler {
  2423.       type: "constant"
  2424.       value: 0
  2425.     }
  2426.   }
  2427. }
  2428. layer {
  2429.   name: "glass/relu1_"
  2430.   type: "PReLU"
  2431.   bottom: "glass/conv1_"
  2432.   top: "glass/conv1_"
  2433. }
  2434. layer {
  2435.   name: "glass/pool1_"
  2436.   type: "Pooling"
  2437.   bottom: "glass/conv1_"
  2438.   top: "glass/pool1_"
  2439.   pooling_param {
  2440.     pool: AVE
  2441.     kernel_size: 4
  2442.     stride: 4
  2443.   }
  2444. }
  2445. layer {
  2446.   name: "glass/ip1"
  2447.   type: "InnerProduct"
  2448.   bottom: "glass/pool1_"
  2449.   top: "glass/ip1"
  2450.   param {
  2451.     lr_mult: 1
  2452.   }
  2453.   param {
  2454.     lr_mult: 2
  2455.   }
  2456.   inner_product_param {
  2457.     num_output: 3
  2458.     weight_filler {
  2459.       type: "xavier"
  2460.     }
  2461.     bias_filler {
  2462.       type: "constant"
  2463.     }
  2464.   }
  2465. }
  2466.  
  2467. layer {
  2468.   name: "race/conv_4_1_pw"
  2469.   type: "Convolution"
  2470.   bottom: "add_6_1"
  2471.   top: "race/conv_4_1_pw"
  2472.   param {
  2473.     lr_mult: 1.0
  2474.     decay_mult: 1.0
  2475.   }
  2476.   convolution_param {
  2477.     num_output: 192
  2478.     bias_term: false
  2479.     pad: 0
  2480.     kernel_size: 1
  2481.     stride: 1
  2482.     weight_filler {
  2483.       type: "msra"
  2484.     }
  2485.     bias_filler {
  2486.       type: "constant"
  2487.       value: 0.0
  2488.     }
  2489.   }
  2490. }
  2491. layer {
  2492.   name: "race/bn_4_1_pw"
  2493.   type: "BatchNorm"
  2494.   bottom: "race/conv_4_1_pw"
  2495.   top: "race/conv_4_1_pw"
  2496.   param {
  2497.     lr_mult: 0.0
  2498.     decay_mult: 0.0
  2499.   }
  2500.   param {
  2501.     lr_mult: 0.0
  2502.     decay_mult: 0.0
  2503.   }
  2504.   param {
  2505.     lr_mult: 0.0
  2506.     decay_mult: 0.0
  2507.   }
  2508. }
  2509. layer {
  2510.   name: "race/scale_4_1_pw"
  2511.   type: "Scale"
  2512.   bottom: "race/conv_4_1_pw"
  2513.   top: "race/conv_4_1_pw"
  2514.   scale_param {
  2515.     bias_term: true
  2516.   }
  2517. }
  2518. layer {
  2519.   name: "race/relu_4_1_pw"
  2520.   type: "PReLU"
  2521.   bottom: "race/conv_4_1_pw"
  2522.   top: "race/conv_4_1_pw"
  2523. }
  2524. layer {
  2525.   name: "race/conv_4_1_dw"
  2526.   type: "ConvolutionDepthwise"
  2527.   bottom: "race/conv_4_1_pw"
  2528.   top: "race/conv_4_1_dw"
  2529.   param {
  2530.     lr_mult: 1.0
  2531.     decay_mult: 1.0
  2532.   }
  2533.   convolution_param {
  2534.     num_output: 192
  2535.     bias_term: false
  2536.     pad: 1
  2537.     kernel_size: 3
  2538.     stride: 2
  2539.     weight_filler {
  2540.       type: "msra"
  2541.     }
  2542.     bias_filler {
  2543.       type: "constant"
  2544.       value: 0.0
  2545.     }
  2546.   }
  2547. }
  2548. layer {
  2549.   name: "race/bn_4_1_dw"
  2550.   type: "BatchNorm"
  2551.   bottom: "race/conv_4_1_dw"
  2552.   top: "race/conv_4_1_dw"
  2553.   param {
  2554.     lr_mult: 0.0
  2555.     decay_mult: 0.0
  2556.   }
  2557.   param {
  2558.     lr_mult: 0.0
  2559.     decay_mult: 0.0
  2560.   }
  2561.   param {
  2562.     lr_mult: 0.0
  2563.     decay_mult: 0.0
  2564.   }
  2565. }
  2566. layer {
  2567.   name: "race/scale_4_1_dw"
  2568.   type: "Scale"
  2569.   bottom: "race/conv_4_1_dw"
  2570.   top: "race/conv_4_1_dw"
  2571.   scale_param {
  2572.     bias_term: true
  2573.   }
  2574. }
  2575. layer {
  2576.   name: "race/relu_4_1_dw"
  2577.   type: "PReLU"
  2578.   bottom: "race/conv_4_1_dw"
  2579.   top: "race/conv_4_1_dw"
  2580. }
  2581. layer {
  2582.   name: "race/conv_4_1_linear"
  2583.   type: "Convolution"
  2584.   bottom: "race/conv_4_1_dw"
  2585.   top: "race/conv_4_1_linear"
  2586.   param {
  2587.     lr_mult: 1.0
  2588.     decay_mult: 1.0
  2589.   }
  2590.   convolution_param {
  2591.     num_output: 96
  2592.     bias_term: false
  2593.     pad: 0
  2594.     kernel_size: 1
  2595.     stride: 1
  2596.     weight_filler {
  2597.       type: "msra"
  2598.     }
  2599.     bias_filler {
  2600.       type: "constant"
  2601.       value: 0.0
  2602.     }
  2603.   }
  2604. }
  2605. layer {
  2606.   name: "race/bn_4_1_linear"
  2607.   type: "BatchNorm"
  2608.   bottom: "race/conv_4_1_linear"
  2609.   top: "race/conv_4_1_linear"
  2610.   param {
  2611.     lr_mult: 0.0
  2612.     decay_mult: 0.0
  2613.   }
  2614.   param {
  2615.     lr_mult: 0.0
  2616.     decay_mult: 0.0
  2617.   }
  2618.   param {
  2619.     lr_mult: 0.0
  2620.     decay_mult: 0.0
  2621.   }
  2622. }
  2623. layer {
  2624.   name: "race/scale_4_1_linear"
  2625.   type: "Scale"
  2626.   bottom: "race/conv_4_1_linear"
  2627.   top: "race/conv_4_1_linear"
  2628.   scale_param {
  2629.     bias_term: true
  2630.   }
  2631. }
  2632. layer {
  2633.   name: "race/conv_4_2_pw"
  2634.   type: "Convolution"
  2635.   bottom: "race/conv_4_1_linear"
  2636.   top: "race/conv_4_2_pw"
  2637.   param {
  2638.     lr_mult: 1.0
  2639.     decay_mult: 1.0
  2640.   }
  2641.   convolution_param {
  2642.     num_output: 192
  2643.     bias_term: false
  2644.     pad: 0
  2645.     kernel_size: 1
  2646.     stride: 1
  2647.     weight_filler {
  2648.       type: "msra"
  2649.     }
  2650.     bias_filler {
  2651.       type: "constant"
  2652.       value: 0.0
  2653.     }
  2654.   }
  2655. }
  2656. layer {
  2657.   name: "race/bn_4_2_pw"
  2658.   type: "BatchNorm"
  2659.   bottom: "race/conv_4_2_pw"
  2660.   top: "race/conv_4_2_pw"
  2661.   param {
  2662.     lr_mult: 0.0
  2663.     decay_mult: 0.0
  2664.   }
  2665.   param {
  2666.     lr_mult: 0.0
  2667.     decay_mult: 0.0
  2668.   }
  2669.   param {
  2670.     lr_mult: 0.0
  2671.     decay_mult: 0.0
  2672.   }
  2673. }
  2674. layer {
  2675.   name: "race/scale_4_2_pw"
  2676.   type: "Scale"
  2677.   bottom: "race/conv_4_2_pw"
  2678.   top: "race/conv_4_2_pw"
  2679.   scale_param {
  2680.     bias_term: true
  2681.   }
  2682. }
  2683. layer {
  2684.   name: "race/relu_4_2_pw"
  2685.   type: "PReLU"
  2686.   bottom: "race/conv_4_2_pw"
  2687.   top: "race/conv_4_2_pw"
  2688. }
  2689. layer {
  2690.   name: "race/conv_4_2_dw"
  2691.   type: "ConvolutionDepthwise"
  2692.   bottom: "race/conv_4_2_pw"
  2693.   top: "race/conv_4_2_dw"
  2694.   param {
  2695.     lr_mult: 1.0
  2696.     decay_mult: 1.0
  2697.   }
  2698.   convolution_param {
  2699.     num_output: 192
  2700.     bias_term: false
  2701.     pad: 1
  2702.     kernel_size: 3
  2703.     stride: 1
  2704.     weight_filler {
  2705.       type: "msra"
  2706.     }
  2707.     bias_filler {
  2708.       type: "constant"
  2709.       value: 0.0
  2710.     }
  2711.   }
  2712. }
  2713. layer {
  2714.   name: "race/bn_4_2_dw"
  2715.   type: "BatchNorm"
  2716.   bottom: "race/conv_4_2_dw"
  2717.   top: "race/conv_4_2_dw"
  2718.   param {
  2719.     lr_mult: 0.0
  2720.     decay_mult: 0.0
  2721.   }
  2722.   param {
  2723.     lr_mult: 0.0
  2724.     decay_mult: 0.0
  2725.   }
  2726.   param {
  2727.     lr_mult: 0.0
  2728.     decay_mult: 0.0
  2729.   }
  2730. }
  2731. layer {
  2732.   name: "race/scale_4_2_dw"
  2733.   type: "Scale"
  2734.   bottom: "race/conv_4_2_dw"
  2735.   top: "race/conv_4_2_dw"
  2736.   scale_param {
  2737.     bias_term: true
  2738.   }
  2739. }
  2740. layer {
  2741.   name: "race/relu_4_2_dw"
  2742.   type: "PReLU"
  2743.   bottom: "race/conv_4_2_dw"
  2744.   top: "race/conv_4_2_dw"
  2745. }
  2746. layer {
  2747.   name: "race/conv_4_2_linear"
  2748.   type: "Convolution"
  2749.   bottom: "race/conv_4_2_dw"
  2750.   top: "race/conv_4_2_linear"
  2751.   param {
  2752.     lr_mult: 1.0
  2753.     decay_mult: 1.0
  2754.   }
  2755.   convolution_param {
  2756.     num_output: 96
  2757.     bias_term: false
  2758.     pad: 0
  2759.     kernel_size: 1
  2760.     stride: 1
  2761.     weight_filler {
  2762.       type: "msra"
  2763.     }
  2764.     bias_filler {
  2765.       type: "constant"
  2766.       value: 0.0
  2767.     }
  2768.   }
  2769. }
  2770. layer {
  2771.   name: "race/bn_4_2_linear"
  2772.   type: "BatchNorm"
  2773.   bottom: "race/conv_4_2_linear"
  2774.   top: "race/conv_4_2_linear"
  2775.   param {
  2776.     lr_mult: 0.0
  2777.     decay_mult: 0.0
  2778.   }
  2779.   param {
  2780.     lr_mult: 0.0
  2781.     decay_mult: 0.0
  2782.   }
  2783.   param {
  2784.     lr_mult: 0.0
  2785.     decay_mult: 0.0
  2786.   }
  2787. }
  2788. layer {
  2789.   name: "race/scale_4_2_linear"
  2790.   type: "Scale"
  2791.   bottom: "race/conv_4_2_linear"
  2792.   top: "race/conv_4_2_linear"
  2793.   scale_param {
  2794.     bias_term: true
  2795.   }
  2796. }
  2797. layer {
  2798.   name: "race/add_4_2"
  2799.   type: "Eltwise"
  2800.   bottom: "race/conv_4_1_linear"
  2801.   bottom: "race/conv_4_2_linear"
  2802.   top: "race/add_4_2"
  2803. }
  2804.  
  2805. layer {
  2806.   name: "race/conv1_"
  2807.   type: "Convolution"
  2808.   bottom: "race/add_4_2"
  2809.   top: "race/conv1_"
  2810.   param {
  2811.     lr_mult: 1
  2812.     decay_mult: 1
  2813.   }
  2814.   param {
  2815.     lr_mult: 2
  2816.     decay_mult: 0
  2817.   }
  2818.   convolution_param {
  2819.     num_output: 128
  2820.     kernel_size: 3
  2821.     stride: 1
  2822.     weight_filler {
  2823.       type: "xavier"
  2824.     }
  2825.     bias_filler {
  2826.       type: "constant"
  2827.       value: 0
  2828.     }
  2829.   }
  2830. }
  2831. layer {
  2832.   name: "race/relu1_"
  2833.   type: "PReLU"
  2834.   bottom: "race/conv1_"
  2835.   top: "race/conv1_"
  2836. }
  2837. layer {
  2838.   name: "race/pool1_"
  2839.   type: "Pooling"
  2840.   bottom: "race/conv1_"
  2841.   top: "race/pool1_"
  2842.   pooling_param {
  2843.     pool: AVE
  2844.     kernel_size: 4
  2845.     stride: 4
  2846.   }
  2847. }
  2848. layer {
  2849.   name: "race/ip1"
  2850.   type: "InnerProduct"
  2851.   bottom: "race/pool1_"
  2852.   top: "race/ip1"
  2853.   param {
  2854.     lr_mult: 1
  2855.   }
  2856.   param {
  2857.     lr_mult: 2
  2858.   }
  2859.   inner_product_param {
  2860.     num_output: 4
  2861.     weight_filler {
  2862.       type: "xavier"
  2863.     }
  2864.     bias_filler {
  2865.       type: "constant"
  2866.     }
  2867.   }
  2868. }
  2869.  
  2870.  
  2871. layer {
  2872.   name: "slice"
  2873.   type: "Slice"
  2874.   bottom: "label"
  2875.   top: "label_age"
  2876.   top: "label_emotion"
  2877.   top: "label_sex"
  2878.   top: "label_glass"
  2879.   top: "label_race"
  2880.   slice_param {
  2881.     axis: 1
  2882.   }
  2883. }
  2884.  
  2885. layer {
  2886.   name: "loss_age"
  2887.   type: "AbsoluteLoss"
  2888.   bottom: "age/ip2"
  2889.   bottom: "label_age"
  2890.   top: "loss_age"
  2891.   loss_weight: 0.1
  2892. }
  2893.  
  2894. #layer {
  2895. #  name: "loss_age"
  2896. #  type: "EuclideanLoss"
  2897. #  bottom: "age/ip2"
  2898. #  bottom: "label_age"
  2899. #  top: "loss_age"
  2900. #}
  2901.  
  2902. layer {
  2903.   name: "accuracy_age_abs"
  2904.   type: "AbsoluteLoss"
  2905.   bottom: "age/ip2"
  2906.   bottom: "label_age"
  2907.   top: "accuracy_age"
  2908.   include {
  2909.     phase: TEST
  2910.   }
  2911. }
  2912.  
  2913. #layer {
  2914. #  name: "accuracy_age_euc"
  2915. #  type: "EuclideanLoss"
  2916. #  bottom: "age/ip2"
  2917. #  bottom: "label_age"
  2918. #  top: "accuracy_age2"
  2919. #  include {
  2920. #    phase: TEST
  2921. #  }
  2922. #}
  2923.  
  2924.  
  2925. layer {
  2926.   name: "loss_emotion"
  2927.   type: "FocalLoss"
  2928.   bottom: "emotion/ip1"
  2929.   bottom: "label_emotion"
  2930.   top: "loss_emotion"
  2931. }
  2932.  
  2933. layer {
  2934.   name: "accuracy_emotion"
  2935.   type: "Accuracy"
  2936.   bottom: "emotion/ip1"
  2937.   bottom: "label_emotion"
  2938.   top: "accuracy_emotion"
  2939.   include {
  2940.     phase: TEST
  2941.   }
  2942. }
  2943.  
  2944. layer {
  2945.   name: "loss_sex"
  2946.   type: "FocalLoss"
  2947.   bottom: "sex/ip1"
  2948.   bottom: "label_sex"
  2949.   top: "loss_sex"
  2950. }
  2951.  
  2952. layer {
  2953.   name: "accuracy_sex"
  2954.   type: "Accuracy"
  2955.   bottom: "sex/ip1"
  2956.   bottom: "label_sex"
  2957.   top: "accuracy_sex"
  2958.   include {
  2959.     phase: TEST
  2960.   }
  2961. }
  2962.  
  2963.  
  2964.  
  2965. layer {
  2966.   name: "loss_glass"
  2967.   type: "FocalLoss"
  2968.   bottom: "glass/ip1"
  2969.   bottom: "label_glass"
  2970.   top: "loss_glass"
  2971. }
  2972.  
  2973. layer {
  2974.   name: "accuracy_glass"
  2975.   type: "Accuracy"
  2976.   bottom: "glass/ip1"
  2977.   bottom: "label_glass"
  2978.   top: "accuracy_glass"
  2979.   include {
  2980.     phase: TEST
  2981.   }
  2982. }
  2983.  
  2984. layer {
  2985.   name: "loss_race"
  2986.   type: "FocalLoss"
  2987.   bottom: "race/ip1"
  2988.   bottom: "label_race"
  2989.   top: "loss_race"
  2990. }
  2991.  
  2992. layer {
  2993.   name: "accuracy_race"
  2994.   type: "Accuracy"
  2995.   bottom: "race/ip1"
  2996.   bottom: "label_race"
  2997.   top: "accuracy_race"
  2998.   include {
  2999.     phase: TEST
  3000.   }
  3001. }

 

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