0x0

mia's file "the null pointer" hosting application -- l0bster h0sted
Log | Files | Refs | LICENSE

deploy.prototxt (60617B)

      1 name: "ResNet_50_1by2_nsfw"
      2 layer {
      3   name: "data"
      4   type: "Input"
      5   top: "data"
      6   input_param { shape: { dim: 1 dim: 3 dim: 224 dim: 224 } }
      7 }
      8 layer {
      9   name: "conv_1"
     10   type: "Convolution"
     11   bottom: "data"
     12   top: "conv_1"
     13   param {
     14     lr_mult: 1
     15     decay_mult: 1
     16   }
     17   param {
     18     lr_mult: 2
     19     decay_mult: 0
     20   }
     21   convolution_param {
     22     num_output: 64
     23     pad: 3
     24     kernel_size: 7
     25     stride: 2
     26     weight_filler {
     27       type: "xavier"
     28     }
     29     bias_filler {
     30       type: "constant"
     31       value: 0
     32     }
     33   }
     34 }
     35 layer {
     36   name: "bn_1"
     37   type: "BatchNorm"
     38   bottom: "conv_1"
     39   top: "conv_1"
     40   param {
     41     lr_mult: 0
     42     decay_mult: 0
     43   }
     44   param {
     45     lr_mult: 0
     46     decay_mult: 0
     47   }
     48   param {
     49     lr_mult: 0
     50     decay_mult: 0
     51   }
     52   batch_norm_param {
     53     use_global_stats: true
     54   }
     55 }
     56 layer {
     57   name: "scale_1"
     58   type: "Scale"
     59   bottom: "conv_1"
     60   top: "conv_1"
     61   scale_param {
     62     bias_term: true
     63   }
     64 }
     65 layer {
     66   name: "relu_1"
     67   type: "ReLU"
     68   bottom: "conv_1"
     69   top: "conv_1"
     70 }
     71 layer {
     72   name: "pool1"
     73   type: "Pooling"
     74   bottom: "conv_1"
     75   top: "pool1"
     76   pooling_param {
     77     pool: MAX
     78     kernel_size: 3
     79     stride: 2
     80   }
     81 }
     82 layer {
     83   name: "conv_stage0_block0_proj_shortcut"
     84   type: "Convolution"
     85   bottom: "pool1"
     86   top: "conv_stage0_block0_proj_shortcut"
     87   param {
     88     lr_mult: 1
     89     decay_mult: 1
     90   }
     91   param {
     92     lr_mult: 2
     93     decay_mult: 0
     94   }
     95   convolution_param {
     96     num_output: 128
     97     pad: 0
     98     kernel_size: 1
     99     stride: 1
    100     weight_filler {
    101       type: "xavier"
    102     }
    103     bias_filler {
    104       type: "constant"
    105       value: 0
    106     }
    107   }
    108 }
    109 layer {
    110   name: "bn_stage0_block0_proj_shortcut"
    111   type: "BatchNorm"
    112   bottom: "conv_stage0_block0_proj_shortcut"
    113   top: "conv_stage0_block0_proj_shortcut"
    114   param {
    115     lr_mult: 0
    116     decay_mult: 0
    117   }
    118   param {
    119     lr_mult: 0
    120     decay_mult: 0
    121   }
    122   param {
    123     lr_mult: 0
    124     decay_mult: 0
    125   }
    126   batch_norm_param {
    127     use_global_stats: true
    128   }
    129 }
    130 layer {
    131   name: "scale_stage0_block0_proj_shortcut"
    132   type: "Scale"
    133   bottom: "conv_stage0_block0_proj_shortcut"
    134   top: "conv_stage0_block0_proj_shortcut"
    135   scale_param {
    136     bias_term: true
    137   }
    138 }
    139 layer {
    140   name: "conv_stage0_block0_branch2a"
    141   type: "Convolution"
    142   bottom: "pool1"
    143   top: "conv_stage0_block0_branch2a"
    144   param {
    145     lr_mult: 1
    146     decay_mult: 1
    147   }
    148   param {
    149     lr_mult: 2
    150     decay_mult: 0
    151   }
    152   convolution_param {
    153     num_output: 32
    154     pad: 0
    155     kernel_size: 1
    156     stride: 1
    157     weight_filler {
    158       type: "xavier"
    159     }
    160     bias_filler {
    161       type: "constant"
    162       value: 0
    163     }
    164   }
    165 }
    166 layer {
    167   name: "bn_stage0_block0_branch2a"
    168   type: "BatchNorm"
    169   bottom: "conv_stage0_block0_branch2a"
    170   top: "conv_stage0_block0_branch2a"
    171   param {
    172     lr_mult: 0
    173     decay_mult: 0
    174   }
    175   param {
    176     lr_mult: 0
    177     decay_mult: 0
    178   }
    179   param {
    180     lr_mult: 0
    181     decay_mult: 0
    182   }
    183   batch_norm_param {
    184     use_global_stats: true
    185   }
    186 }
    187 layer {
    188   name: "scale_stage0_block0_branch2a"
    189   type: "Scale"
    190   bottom: "conv_stage0_block0_branch2a"
    191   top: "conv_stage0_block0_branch2a"
    192   scale_param {
    193     bias_term: true
    194   }
    195 }
    196 layer {
    197   name: "relu_stage0_block0_branch2a"
    198   type: "ReLU"
    199   bottom: "conv_stage0_block0_branch2a"
    200   top: "conv_stage0_block0_branch2a"
    201 }
    202 layer {
    203   name: "conv_stage0_block0_branch2b"
    204   type: "Convolution"
    205   bottom: "conv_stage0_block0_branch2a"
    206   top: "conv_stage0_block0_branch2b"
    207   param {
    208     lr_mult: 1
    209     decay_mult: 1
    210   }
    211   param {
    212     lr_mult: 2
    213     decay_mult: 0
    214   }
    215   convolution_param {
    216     num_output: 32
    217     pad: 1
    218     kernel_size: 3
    219     stride: 1
    220     weight_filler {
    221       type: "xavier"
    222     }
    223     bias_filler {
    224       type: "constant"
    225       value: 0
    226     }
    227   }
    228 }
    229 layer {
    230   name: "bn_stage0_block0_branch2b"
    231   type: "BatchNorm"
    232   bottom: "conv_stage0_block0_branch2b"
    233   top: "conv_stage0_block0_branch2b"
    234   param {
    235     lr_mult: 0
    236     decay_mult: 0
    237   }
    238   param {
    239     lr_mult: 0
    240     decay_mult: 0
    241   }
    242   param {
    243     lr_mult: 0
    244     decay_mult: 0
    245   }
    246   batch_norm_param {
    247     use_global_stats: true
    248   }
    249 }
    250 layer {
    251   name: "scale_stage0_block0_branch2b"
    252   type: "Scale"
    253   bottom: "conv_stage0_block0_branch2b"
    254   top: "conv_stage0_block0_branch2b"
    255   scale_param {
    256     bias_term: true
    257   }
    258 }
    259 layer {
    260   name: "relu_stage0_block0_branch2b"
    261   type: "ReLU"
    262   bottom: "conv_stage0_block0_branch2b"
    263   top: "conv_stage0_block0_branch2b"
    264 }
    265 layer {
    266   name: "conv_stage0_block0_branch2c"
    267   type: "Convolution"
    268   bottom: "conv_stage0_block0_branch2b"
    269   top: "conv_stage0_block0_branch2c"
    270   param {
    271     lr_mult: 1
    272     decay_mult: 1
    273   }
    274   param {
    275     lr_mult: 2
    276     decay_mult: 0
    277   }
    278   convolution_param {
    279     num_output: 128
    280     pad: 0
    281     kernel_size: 1
    282     stride: 1
    283     weight_filler {
    284       type: "xavier"
    285     }
    286     bias_filler {
    287       type: "constant"
    288       value: 0
    289     }
    290   }
    291 }
    292 layer {
    293   name: "bn_stage0_block0_branch2c"
    294   type: "BatchNorm"
    295   bottom: "conv_stage0_block0_branch2c"
    296   top: "conv_stage0_block0_branch2c"
    297   param {
    298     lr_mult: 0
    299     decay_mult: 0
    300   }
    301   param {
    302     lr_mult: 0
    303     decay_mult: 0
    304   }
    305   param {
    306     lr_mult: 0
    307     decay_mult: 0
    308   }
    309   batch_norm_param {
    310     use_global_stats: true
    311   }
    312 }
    313 layer {
    314   name: "scale_stage0_block0_branch2c"
    315   type: "Scale"
    316   bottom: "conv_stage0_block0_branch2c"
    317   top: "conv_stage0_block0_branch2c"
    318   scale_param {
    319     bias_term: true
    320   }
    321 }
    322 layer {
    323   name: "eltwise_stage0_block0"
    324   type: "Eltwise"
    325   bottom: "conv_stage0_block0_proj_shortcut"
    326   bottom: "conv_stage0_block0_branch2c"
    327   top: "eltwise_stage0_block0"
    328 }
    329 layer {
    330   name: "relu_stage0_block0"
    331   type: "ReLU"
    332   bottom: "eltwise_stage0_block0"
    333   top: "eltwise_stage0_block0"
    334 }
    335 layer {
    336   name: "conv_stage0_block1_branch2a"
    337   type: "Convolution"
    338   bottom: "eltwise_stage0_block0"
    339   top: "conv_stage0_block1_branch2a"
    340   param {
    341     lr_mult: 1
    342     decay_mult: 1
    343   }
    344   param {
    345     lr_mult: 2
    346     decay_mult: 0
    347   }
    348   convolution_param {
    349     num_output: 32
    350     pad: 0
    351     kernel_size: 1
    352     stride: 1
    353     weight_filler {
    354       type: "xavier"
    355     }
    356     bias_filler {
    357       type: "constant"
    358       value: 0
    359     }
    360   }
    361 }
    362 layer {
    363   name: "bn_stage0_block1_branch2a"
    364   type: "BatchNorm"
    365   bottom: "conv_stage0_block1_branch2a"
    366   top: "conv_stage0_block1_branch2a"
    367   param {
    368     lr_mult: 0
    369     decay_mult: 0
    370   }
    371   param {
    372     lr_mult: 0
    373     decay_mult: 0
    374   }
    375   param {
    376     lr_mult: 0
    377     decay_mult: 0
    378   }
    379   batch_norm_param {
    380     use_global_stats: true
    381   }
    382 }
    383 layer {
    384   name: "scale_stage0_block1_branch2a"
    385   type: "Scale"
    386   bottom: "conv_stage0_block1_branch2a"
    387   top: "conv_stage0_block1_branch2a"
    388   scale_param {
    389     bias_term: true
    390   }
    391 }
    392 layer {
    393   name: "relu_stage0_block1_branch2a"
    394   type: "ReLU"
    395   bottom: "conv_stage0_block1_branch2a"
    396   top: "conv_stage0_block1_branch2a"
    397 }
    398 layer {
    399   name: "conv_stage0_block1_branch2b"
    400   type: "Convolution"
    401   bottom: "conv_stage0_block1_branch2a"
    402   top: "conv_stage0_block1_branch2b"
    403   param {
    404     lr_mult: 1
    405     decay_mult: 1
    406   }
    407   param {
    408     lr_mult: 2
    409     decay_mult: 0
    410   }
    411   convolution_param {
    412     num_output: 32
    413     pad: 1
    414     kernel_size: 3
    415     stride: 1
    416     weight_filler {
    417       type: "xavier"
    418     }
    419     bias_filler {
    420       type: "constant"
    421       value: 0
    422     }
    423   }
    424 }
    425 layer {
    426   name: "bn_stage0_block1_branch2b"
    427   type: "BatchNorm"
    428   bottom: "conv_stage0_block1_branch2b"
    429   top: "conv_stage0_block1_branch2b"
    430   param {
    431     lr_mult: 0
    432     decay_mult: 0
    433   }
    434   param {
    435     lr_mult: 0
    436     decay_mult: 0
    437   }
    438   param {
    439     lr_mult: 0
    440     decay_mult: 0
    441   }
    442   batch_norm_param {
    443     use_global_stats: true
    444   }
    445 }
    446 layer {
    447   name: "scale_stage0_block1_branch2b"
    448   type: "Scale"
    449   bottom: "conv_stage0_block1_branch2b"
    450   top: "conv_stage0_block1_branch2b"
    451   scale_param {
    452     bias_term: true
    453   }
    454 }
    455 layer {
    456   name: "relu_stage0_block1_branch2b"
    457   type: "ReLU"
    458   bottom: "conv_stage0_block1_branch2b"
    459   top: "conv_stage0_block1_branch2b"
    460 }
    461 layer {
    462   name: "conv_stage0_block1_branch2c"
    463   type: "Convolution"
    464   bottom: "conv_stage0_block1_branch2b"
    465   top: "conv_stage0_block1_branch2c"
    466   param {
    467     lr_mult: 1
    468     decay_mult: 1
    469   }
    470   param {
    471     lr_mult: 2
    472     decay_mult: 0
    473   }
    474   convolution_param {
    475     num_output: 128
    476     pad: 0
    477     kernel_size: 1
    478     stride: 1
    479     weight_filler {
    480       type: "xavier"
    481     }
    482     bias_filler {
    483       type: "constant"
    484       value: 0
    485     }
    486   }
    487 }
    488 layer {
    489   name: "bn_stage0_block1_branch2c"
    490   type: "BatchNorm"
    491   bottom: "conv_stage0_block1_branch2c"
    492   top: "conv_stage0_block1_branch2c"
    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   batch_norm_param {
    506     use_global_stats: true
    507   }
    508 }
    509 layer {
    510   name: "scale_stage0_block1_branch2c"
    511   type: "Scale"
    512   bottom: "conv_stage0_block1_branch2c"
    513   top: "conv_stage0_block1_branch2c"
    514   scale_param {
    515     bias_term: true
    516   }
    517 }
    518 layer {
    519   name: "eltwise_stage0_block1"
    520   type: "Eltwise"
    521   bottom: "eltwise_stage0_block0"
    522   bottom: "conv_stage0_block1_branch2c"
    523   top: "eltwise_stage0_block1"
    524 }
    525 layer {
    526   name: "relu_stage0_block1"
    527   type: "ReLU"
    528   bottom: "eltwise_stage0_block1"
    529   top: "eltwise_stage0_block1"
    530 }
    531 layer {
    532   name: "conv_stage0_block2_branch2a"
    533   type: "Convolution"
    534   bottom: "eltwise_stage0_block1"
    535   top: "conv_stage0_block2_branch2a"
    536   param {
    537     lr_mult: 1
    538     decay_mult: 1
    539   }
    540   param {
    541     lr_mult: 2
    542     decay_mult: 0
    543   }
    544   convolution_param {
    545     num_output: 32
    546     pad: 0
    547     kernel_size: 1
    548     stride: 1
    549     weight_filler {
    550       type: "xavier"
    551     }
    552     bias_filler {
    553       type: "constant"
    554       value: 0
    555     }
    556   }
    557 }
    558 layer {
    559   name: "bn_stage0_block2_branch2a"
    560   type: "BatchNorm"
    561   bottom: "conv_stage0_block2_branch2a"
    562   top: "conv_stage0_block2_branch2a"
    563   param {
    564     lr_mult: 0
    565     decay_mult: 0
    566   }
    567   param {
    568     lr_mult: 0
    569     decay_mult: 0
    570   }
    571   param {
    572     lr_mult: 0
    573     decay_mult: 0
    574   }
    575   batch_norm_param {
    576     use_global_stats: true
    577   }
    578 }
    579 layer {
    580   name: "scale_stage0_block2_branch2a"
    581   type: "Scale"
    582   bottom: "conv_stage0_block2_branch2a"
    583   top: "conv_stage0_block2_branch2a"
    584   scale_param {
    585     bias_term: true
    586   }
    587 }
    588 layer {
    589   name: "relu_stage0_block2_branch2a"
    590   type: "ReLU"
    591   bottom: "conv_stage0_block2_branch2a"
    592   top: "conv_stage0_block2_branch2a"
    593 }
    594 layer {
    595   name: "conv_stage0_block2_branch2b"
    596   type: "Convolution"
    597   bottom: "conv_stage0_block2_branch2a"
    598   top: "conv_stage0_block2_branch2b"
    599   param {
    600     lr_mult: 1
    601     decay_mult: 1
    602   }
    603   param {
    604     lr_mult: 2
    605     decay_mult: 0
    606   }
    607   convolution_param {
    608     num_output: 32
    609     pad: 1
    610     kernel_size: 3
    611     stride: 1
    612     weight_filler {
    613       type: "xavier"
    614     }
    615     bias_filler {
    616       type: "constant"
    617       value: 0
    618     }
    619   }
    620 }
    621 layer {
    622   name: "bn_stage0_block2_branch2b"
    623   type: "BatchNorm"
    624   bottom: "conv_stage0_block2_branch2b"
    625   top: "conv_stage0_block2_branch2b"
    626   param {
    627     lr_mult: 0
    628     decay_mult: 0
    629   }
    630   param {
    631     lr_mult: 0
    632     decay_mult: 0
    633   }
    634   param {
    635     lr_mult: 0
    636     decay_mult: 0
    637   }
    638   batch_norm_param {
    639     use_global_stats: true
    640   }
    641 }
    642 layer {
    643   name: "scale_stage0_block2_branch2b"
    644   type: "Scale"
    645   bottom: "conv_stage0_block2_branch2b"
    646   top: "conv_stage0_block2_branch2b"
    647   scale_param {
    648     bias_term: true
    649   }
    650 }
    651 layer {
    652   name: "relu_stage0_block2_branch2b"
    653   type: "ReLU"
    654   bottom: "conv_stage0_block2_branch2b"
    655   top: "conv_stage0_block2_branch2b"
    656 }
    657 layer {
    658   name: "conv_stage0_block2_branch2c"
    659   type: "Convolution"
    660   bottom: "conv_stage0_block2_branch2b"
    661   top: "conv_stage0_block2_branch2c"
    662   param {
    663     lr_mult: 1
    664     decay_mult: 1
    665   }
    666   param {
    667     lr_mult: 2
    668     decay_mult: 0
    669   }
    670   convolution_param {
    671     num_output: 128
    672     pad: 0
    673     kernel_size: 1
    674     stride: 1
    675     weight_filler {
    676       type: "xavier"
    677     }
    678     bias_filler {
    679       type: "constant"
    680       value: 0
    681     }
    682   }
    683 }
    684 layer {
    685   name: "bn_stage0_block2_branch2c"
    686   type: "BatchNorm"
    687   bottom: "conv_stage0_block2_branch2c"
    688   top: "conv_stage0_block2_branch2c"
    689   param {
    690     lr_mult: 0
    691     decay_mult: 0
    692   }
    693   param {
    694     lr_mult: 0
    695     decay_mult: 0
    696   }
    697   param {
    698     lr_mult: 0
    699     decay_mult: 0
    700   }
    701   batch_norm_param {
    702     use_global_stats: true
    703   }
    704 }
    705 layer {
    706   name: "scale_stage0_block2_branch2c"
    707   type: "Scale"
    708   bottom: "conv_stage0_block2_branch2c"
    709   top: "conv_stage0_block2_branch2c"
    710   scale_param {
    711     bias_term: true
    712   }
    713 }
    714 layer {
    715   name: "eltwise_stage0_block2"
    716   type: "Eltwise"
    717   bottom: "eltwise_stage0_block1"
    718   bottom: "conv_stage0_block2_branch2c"
    719   top: "eltwise_stage0_block2"
    720 }
    721 layer {
    722   name: "relu_stage0_block2"
    723   type: "ReLU"
    724   bottom: "eltwise_stage0_block2"
    725   top: "eltwise_stage0_block2"
    726 }
    727 layer {
    728   name: "conv_stage1_block0_proj_shortcut"
    729   type: "Convolution"
    730   bottom: "eltwise_stage0_block2"
    731   top: "conv_stage1_block0_proj_shortcut"
    732   param {
    733     lr_mult: 1
    734     decay_mult: 1
    735   }
    736   param {
    737     lr_mult: 2
    738     decay_mult: 0
    739   }
    740   convolution_param {
    741     num_output: 256
    742     pad: 0
    743     kernel_size: 1
    744     stride: 2
    745     weight_filler {
    746       type: "xavier"
    747     }
    748     bias_filler {
    749       type: "constant"
    750       value: 0
    751     }
    752   }
    753 }
    754 layer {
    755   name: "bn_stage1_block0_proj_shortcut"
    756   type: "BatchNorm"
    757   bottom: "conv_stage1_block0_proj_shortcut"
    758   top: "conv_stage1_block0_proj_shortcut"
    759   param {
    760     lr_mult: 0
    761     decay_mult: 0
    762   }
    763   param {
    764     lr_mult: 0
    765     decay_mult: 0
    766   }
    767   param {
    768     lr_mult: 0
    769     decay_mult: 0
    770   }
    771   batch_norm_param {
    772     use_global_stats: true
    773   }
    774 }
    775 layer {
    776   name: "scale_stage1_block0_proj_shortcut"
    777   type: "Scale"
    778   bottom: "conv_stage1_block0_proj_shortcut"
    779   top: "conv_stage1_block0_proj_shortcut"
    780   scale_param {
    781     bias_term: true
    782   }
    783 }
    784 layer {
    785   name: "conv_stage1_block0_branch2a"
    786   type: "Convolution"
    787   bottom: "eltwise_stage0_block2"
    788   top: "conv_stage1_block0_branch2a"
    789   param {
    790     lr_mult: 1
    791     decay_mult: 1
    792   }
    793   param {
    794     lr_mult: 2
    795     decay_mult: 0
    796   }
    797   convolution_param {
    798     num_output: 64
    799     pad: 0
    800     kernel_size: 1
    801     stride: 2
    802     weight_filler {
    803       type: "xavier"
    804     }
    805     bias_filler {
    806       type: "constant"
    807       value: 0
    808     }
    809   }
    810 }
    811 layer {
    812   name: "bn_stage1_block0_branch2a"
    813   type: "BatchNorm"
    814   bottom: "conv_stage1_block0_branch2a"
    815   top: "conv_stage1_block0_branch2a"
    816   param {
    817     lr_mult: 0
    818     decay_mult: 0
    819   }
    820   param {
    821     lr_mult: 0
    822     decay_mult: 0
    823   }
    824   param {
    825     lr_mult: 0
    826     decay_mult: 0
    827   }
    828   batch_norm_param {
    829     use_global_stats: true
    830   }
    831 }
    832 layer {
    833   name: "scale_stage1_block0_branch2a"
    834   type: "Scale"
    835   bottom: "conv_stage1_block0_branch2a"
    836   top: "conv_stage1_block0_branch2a"
    837   scale_param {
    838     bias_term: true
    839   }
    840 }
    841 layer {
    842   name: "relu_stage1_block0_branch2a"
    843   type: "ReLU"
    844   bottom: "conv_stage1_block0_branch2a"
    845   top: "conv_stage1_block0_branch2a"
    846 }
    847 layer {
    848   name: "conv_stage1_block0_branch2b"
    849   type: "Convolution"
    850   bottom: "conv_stage1_block0_branch2a"
    851   top: "conv_stage1_block0_branch2b"
    852   param {
    853     lr_mult: 1
    854     decay_mult: 1
    855   }
    856   param {
    857     lr_mult: 2
    858     decay_mult: 0
    859   }
    860   convolution_param {
    861     num_output: 64
    862     pad: 1
    863     kernel_size: 3
    864     stride: 1
    865     weight_filler {
    866       type: "xavier"
    867     }
    868     bias_filler {
    869       type: "constant"
    870       value: 0
    871     }
    872   }
    873 }
    874 layer {
    875   name: "bn_stage1_block0_branch2b"
    876   type: "BatchNorm"
    877   bottom: "conv_stage1_block0_branch2b"
    878   top: "conv_stage1_block0_branch2b"
    879   param {
    880     lr_mult: 0
    881     decay_mult: 0
    882   }
    883   param {
    884     lr_mult: 0
    885     decay_mult: 0
    886   }
    887   param {
    888     lr_mult: 0
    889     decay_mult: 0
    890   }
    891   batch_norm_param {
    892     use_global_stats: true
    893   }
    894 }
    895 layer {
    896   name: "scale_stage1_block0_branch2b"
    897   type: "Scale"
    898   bottom: "conv_stage1_block0_branch2b"
    899   top: "conv_stage1_block0_branch2b"
    900   scale_param {
    901     bias_term: true
    902   }
    903 }
    904 layer {
    905   name: "relu_stage1_block0_branch2b"
    906   type: "ReLU"
    907   bottom: "conv_stage1_block0_branch2b"
    908   top: "conv_stage1_block0_branch2b"
    909 }
    910 layer {
    911   name: "conv_stage1_block0_branch2c"
    912   type: "Convolution"
    913   bottom: "conv_stage1_block0_branch2b"
    914   top: "conv_stage1_block0_branch2c"
    915   param {
    916     lr_mult: 1
    917     decay_mult: 1
    918   }
    919   param {
    920     lr_mult: 2
    921     decay_mult: 0
    922   }
    923   convolution_param {
    924     num_output: 256
    925     pad: 0
    926     kernel_size: 1
    927     stride: 1
    928     weight_filler {
    929       type: "xavier"
    930     }
    931     bias_filler {
    932       type: "constant"
    933       value: 0
    934     }
    935   }
    936 }
    937 layer {
    938   name: "bn_stage1_block0_branch2c"
    939   type: "BatchNorm"
    940   bottom: "conv_stage1_block0_branch2c"
    941   top: "conv_stage1_block0_branch2c"
    942   param {
    943     lr_mult: 0
    944     decay_mult: 0
    945   }
    946   param {
    947     lr_mult: 0
    948     decay_mult: 0
    949   }
    950   param {
    951     lr_mult: 0
    952     decay_mult: 0
    953   }
    954   batch_norm_param {
    955     use_global_stats: true
    956   }
    957 }
    958 layer {
    959   name: "scale_stage1_block0_branch2c"
    960   type: "Scale"
    961   bottom: "conv_stage1_block0_branch2c"
    962   top: "conv_stage1_block0_branch2c"
    963   scale_param {
    964     bias_term: true
    965   }
    966 }
    967 layer {
    968   name: "eltwise_stage1_block0"
    969   type: "Eltwise"
    970   bottom: "conv_stage1_block0_proj_shortcut"
    971   bottom: "conv_stage1_block0_branch2c"
    972   top: "eltwise_stage1_block0"
    973 }
    974 layer {
    975   name: "relu_stage1_block0"
    976   type: "ReLU"
    977   bottom: "eltwise_stage1_block0"
    978   top: "eltwise_stage1_block0"
    979 }
    980 layer {
    981   name: "conv_stage1_block1_branch2a"
    982   type: "Convolution"
    983   bottom: "eltwise_stage1_block0"
    984   top: "conv_stage1_block1_branch2a"
    985   param {
    986     lr_mult: 1
    987     decay_mult: 1
    988   }
    989   param {
    990     lr_mult: 2
    991     decay_mult: 0
    992   }
    993   convolution_param {
    994     num_output: 64
    995     pad: 0
    996     kernel_size: 1
    997     stride: 1
    998     weight_filler {
    999       type: "xavier"
   1000     }
   1001     bias_filler {
   1002       type: "constant"
   1003       value: 0
   1004     }
   1005   }
   1006 }
   1007 layer {
   1008   name: "bn_stage1_block1_branch2a"
   1009   type: "BatchNorm"
   1010   bottom: "conv_stage1_block1_branch2a"
   1011   top: "conv_stage1_block1_branch2a"
   1012   param {
   1013     lr_mult: 0
   1014     decay_mult: 0
   1015   }
   1016   param {
   1017     lr_mult: 0
   1018     decay_mult: 0
   1019   }
   1020   param {
   1021     lr_mult: 0
   1022     decay_mult: 0
   1023   }
   1024   batch_norm_param {
   1025     use_global_stats: true
   1026   }
   1027 }
   1028 layer {
   1029   name: "scale_stage1_block1_branch2a"
   1030   type: "Scale"
   1031   bottom: "conv_stage1_block1_branch2a"
   1032   top: "conv_stage1_block1_branch2a"
   1033   scale_param {
   1034     bias_term: true
   1035   }
   1036 }
   1037 layer {
   1038   name: "relu_stage1_block1_branch2a"
   1039   type: "ReLU"
   1040   bottom: "conv_stage1_block1_branch2a"
   1041   top: "conv_stage1_block1_branch2a"
   1042 }
   1043 layer {
   1044   name: "conv_stage1_block1_branch2b"
   1045   type: "Convolution"
   1046   bottom: "conv_stage1_block1_branch2a"
   1047   top: "conv_stage1_block1_branch2b"
   1048   param {
   1049     lr_mult: 1
   1050     decay_mult: 1
   1051   }
   1052   param {
   1053     lr_mult: 2
   1054     decay_mult: 0
   1055   }
   1056   convolution_param {
   1057     num_output: 64
   1058     pad: 1
   1059     kernel_size: 3
   1060     stride: 1
   1061     weight_filler {
   1062       type: "xavier"
   1063     }
   1064     bias_filler {
   1065       type: "constant"
   1066       value: 0
   1067     }
   1068   }
   1069 }
   1070 layer {
   1071   name: "bn_stage1_block1_branch2b"
   1072   type: "BatchNorm"
   1073   bottom: "conv_stage1_block1_branch2b"
   1074   top: "conv_stage1_block1_branch2b"
   1075   param {
   1076     lr_mult: 0
   1077     decay_mult: 0
   1078   }
   1079   param {
   1080     lr_mult: 0
   1081     decay_mult: 0
   1082   }
   1083   param {
   1084     lr_mult: 0
   1085     decay_mult: 0
   1086   }
   1087   batch_norm_param {
   1088     use_global_stats: true
   1089   }
   1090 }
   1091 layer {
   1092   name: "scale_stage1_block1_branch2b"
   1093   type: "Scale"
   1094   bottom: "conv_stage1_block1_branch2b"
   1095   top: "conv_stage1_block1_branch2b"
   1096   scale_param {
   1097     bias_term: true
   1098   }
   1099 }
   1100 layer {
   1101   name: "relu_stage1_block1_branch2b"
   1102   type: "ReLU"
   1103   bottom: "conv_stage1_block1_branch2b"
   1104   top: "conv_stage1_block1_branch2b"
   1105 }
   1106 layer {
   1107   name: "conv_stage1_block1_branch2c"
   1108   type: "Convolution"
   1109   bottom: "conv_stage1_block1_branch2b"
   1110   top: "conv_stage1_block1_branch2c"
   1111   param {
   1112     lr_mult: 1
   1113     decay_mult: 1
   1114   }
   1115   param {
   1116     lr_mult: 2
   1117     decay_mult: 0
   1118   }
   1119   convolution_param {
   1120     num_output: 256
   1121     pad: 0
   1122     kernel_size: 1
   1123     stride: 1
   1124     weight_filler {
   1125       type: "xavier"
   1126     }
   1127     bias_filler {
   1128       type: "constant"
   1129       value: 0
   1130     }
   1131   }
   1132 }
   1133 layer {
   1134   name: "bn_stage1_block1_branch2c"
   1135   type: "BatchNorm"
   1136   bottom: "conv_stage1_block1_branch2c"
   1137   top: "conv_stage1_block1_branch2c"
   1138   param {
   1139     lr_mult: 0
   1140     decay_mult: 0
   1141   }
   1142   param {
   1143     lr_mult: 0
   1144     decay_mult: 0
   1145   }
   1146   param {
   1147     lr_mult: 0
   1148     decay_mult: 0
   1149   }
   1150   batch_norm_param {
   1151     use_global_stats: true
   1152   }
   1153 }
   1154 layer {
   1155   name: "scale_stage1_block1_branch2c"
   1156   type: "Scale"
   1157   bottom: "conv_stage1_block1_branch2c"
   1158   top: "conv_stage1_block1_branch2c"
   1159   scale_param {
   1160     bias_term: true
   1161   }
   1162 }
   1163 layer {
   1164   name: "eltwise_stage1_block1"
   1165   type: "Eltwise"
   1166   bottom: "eltwise_stage1_block0"
   1167   bottom: "conv_stage1_block1_branch2c"
   1168   top: "eltwise_stage1_block1"
   1169 }
   1170 layer {
   1171   name: "relu_stage1_block1"
   1172   type: "ReLU"
   1173   bottom: "eltwise_stage1_block1"
   1174   top: "eltwise_stage1_block1"
   1175 }
   1176 layer {
   1177   name: "conv_stage1_block2_branch2a"
   1178   type: "Convolution"
   1179   bottom: "eltwise_stage1_block1"
   1180   top: "conv_stage1_block2_branch2a"
   1181   param {
   1182     lr_mult: 1
   1183     decay_mult: 1
   1184   }
   1185   param {
   1186     lr_mult: 2
   1187     decay_mult: 0
   1188   }
   1189   convolution_param {
   1190     num_output: 64
   1191     pad: 0
   1192     kernel_size: 1
   1193     stride: 1
   1194     weight_filler {
   1195       type: "xavier"
   1196     }
   1197     bias_filler {
   1198       type: "constant"
   1199       value: 0
   1200     }
   1201   }
   1202 }
   1203 layer {
   1204   name: "bn_stage1_block2_branch2a"
   1205   type: "BatchNorm"
   1206   bottom: "conv_stage1_block2_branch2a"
   1207   top: "conv_stage1_block2_branch2a"
   1208   param {
   1209     lr_mult: 0
   1210     decay_mult: 0
   1211   }
   1212   param {
   1213     lr_mult: 0
   1214     decay_mult: 0
   1215   }
   1216   param {
   1217     lr_mult: 0
   1218     decay_mult: 0
   1219   }
   1220   batch_norm_param {
   1221     use_global_stats: true
   1222   }
   1223 }
   1224 layer {
   1225   name: "scale_stage1_block2_branch2a"
   1226   type: "Scale"
   1227   bottom: "conv_stage1_block2_branch2a"
   1228   top: "conv_stage1_block2_branch2a"
   1229   scale_param {
   1230     bias_term: true
   1231   }
   1232 }
   1233 layer {
   1234   name: "relu_stage1_block2_branch2a"
   1235   type: "ReLU"
   1236   bottom: "conv_stage1_block2_branch2a"
   1237   top: "conv_stage1_block2_branch2a"
   1238 }
   1239 layer {
   1240   name: "conv_stage1_block2_branch2b"
   1241   type: "Convolution"
   1242   bottom: "conv_stage1_block2_branch2a"
   1243   top: "conv_stage1_block2_branch2b"
   1244   param {
   1245     lr_mult: 1
   1246     decay_mult: 1
   1247   }
   1248   param {
   1249     lr_mult: 2
   1250     decay_mult: 0
   1251   }
   1252   convolution_param {
   1253     num_output: 64
   1254     pad: 1
   1255     kernel_size: 3
   1256     stride: 1
   1257     weight_filler {
   1258       type: "xavier"
   1259     }
   1260     bias_filler {
   1261       type: "constant"
   1262       value: 0
   1263     }
   1264   }
   1265 }
   1266 layer {
   1267   name: "bn_stage1_block2_branch2b"
   1268   type: "BatchNorm"
   1269   bottom: "conv_stage1_block2_branch2b"
   1270   top: "conv_stage1_block2_branch2b"
   1271   param {
   1272     lr_mult: 0
   1273     decay_mult: 0
   1274   }
   1275   param {
   1276     lr_mult: 0
   1277     decay_mult: 0
   1278   }
   1279   param {
   1280     lr_mult: 0
   1281     decay_mult: 0
   1282   }
   1283   batch_norm_param {
   1284     use_global_stats: true
   1285   }
   1286 }
   1287 layer {
   1288   name: "scale_stage1_block2_branch2b"
   1289   type: "Scale"
   1290   bottom: "conv_stage1_block2_branch2b"
   1291   top: "conv_stage1_block2_branch2b"
   1292   scale_param {
   1293     bias_term: true
   1294   }
   1295 }
   1296 layer {
   1297   name: "relu_stage1_block2_branch2b"
   1298   type: "ReLU"
   1299   bottom: "conv_stage1_block2_branch2b"
   1300   top: "conv_stage1_block2_branch2b"
   1301 }
   1302 layer {
   1303   name: "conv_stage1_block2_branch2c"
   1304   type: "Convolution"
   1305   bottom: "conv_stage1_block2_branch2b"
   1306   top: "conv_stage1_block2_branch2c"
   1307   param {
   1308     lr_mult: 1
   1309     decay_mult: 1
   1310   }
   1311   param {
   1312     lr_mult: 2
   1313     decay_mult: 0
   1314   }
   1315   convolution_param {
   1316     num_output: 256
   1317     pad: 0
   1318     kernel_size: 1
   1319     stride: 1
   1320     weight_filler {
   1321       type: "xavier"
   1322     }
   1323     bias_filler {
   1324       type: "constant"
   1325       value: 0
   1326     }
   1327   }
   1328 }
   1329 layer {
   1330   name: "bn_stage1_block2_branch2c"
   1331   type: "BatchNorm"
   1332   bottom: "conv_stage1_block2_branch2c"
   1333   top: "conv_stage1_block2_branch2c"
   1334   param {
   1335     lr_mult: 0
   1336     decay_mult: 0
   1337   }
   1338   param {
   1339     lr_mult: 0
   1340     decay_mult: 0
   1341   }
   1342   param {
   1343     lr_mult: 0
   1344     decay_mult: 0
   1345   }
   1346   batch_norm_param {
   1347     use_global_stats: true
   1348   }
   1349 }
   1350 layer {
   1351   name: "scale_stage1_block2_branch2c"
   1352   type: "Scale"
   1353   bottom: "conv_stage1_block2_branch2c"
   1354   top: "conv_stage1_block2_branch2c"
   1355   scale_param {
   1356     bias_term: true
   1357   }
   1358 }
   1359 layer {
   1360   name: "eltwise_stage1_block2"
   1361   type: "Eltwise"
   1362   bottom: "eltwise_stage1_block1"
   1363   bottom: "conv_stage1_block2_branch2c"
   1364   top: "eltwise_stage1_block2"
   1365 }
   1366 layer {
   1367   name: "relu_stage1_block2"
   1368   type: "ReLU"
   1369   bottom: "eltwise_stage1_block2"
   1370   top: "eltwise_stage1_block2"
   1371 }
   1372 layer {
   1373   name: "conv_stage1_block3_branch2a"
   1374   type: "Convolution"
   1375   bottom: "eltwise_stage1_block2"
   1376   top: "conv_stage1_block3_branch2a"
   1377   param {
   1378     lr_mult: 1
   1379     decay_mult: 1
   1380   }
   1381   param {
   1382     lr_mult: 2
   1383     decay_mult: 0
   1384   }
   1385   convolution_param {
   1386     num_output: 64
   1387     pad: 0
   1388     kernel_size: 1
   1389     stride: 1
   1390     weight_filler {
   1391       type: "xavier"
   1392     }
   1393     bias_filler {
   1394       type: "constant"
   1395       value: 0
   1396     }
   1397   }
   1398 }
   1399 layer {
   1400   name: "bn_stage1_block3_branch2a"
   1401   type: "BatchNorm"
   1402   bottom: "conv_stage1_block3_branch2a"
   1403   top: "conv_stage1_block3_branch2a"
   1404   param {
   1405     lr_mult: 0
   1406     decay_mult: 0
   1407   }
   1408   param {
   1409     lr_mult: 0
   1410     decay_mult: 0
   1411   }
   1412   param {
   1413     lr_mult: 0
   1414     decay_mult: 0
   1415   }
   1416   batch_norm_param {
   1417     use_global_stats: true
   1418   }
   1419 }
   1420 layer {
   1421   name: "scale_stage1_block3_branch2a"
   1422   type: "Scale"
   1423   bottom: "conv_stage1_block3_branch2a"
   1424   top: "conv_stage1_block3_branch2a"
   1425   scale_param {
   1426     bias_term: true
   1427   }
   1428 }
   1429 layer {
   1430   name: "relu_stage1_block3_branch2a"
   1431   type: "ReLU"
   1432   bottom: "conv_stage1_block3_branch2a"
   1433   top: "conv_stage1_block3_branch2a"
   1434 }
   1435 layer {
   1436   name: "conv_stage1_block3_branch2b"
   1437   type: "Convolution"
   1438   bottom: "conv_stage1_block3_branch2a"
   1439   top: "conv_stage1_block3_branch2b"
   1440   param {
   1441     lr_mult: 1
   1442     decay_mult: 1
   1443   }
   1444   param {
   1445     lr_mult: 2
   1446     decay_mult: 0
   1447   }
   1448   convolution_param {
   1449     num_output: 64
   1450     pad: 1
   1451     kernel_size: 3
   1452     stride: 1
   1453     weight_filler {
   1454       type: "xavier"
   1455     }
   1456     bias_filler {
   1457       type: "constant"
   1458       value: 0
   1459     }
   1460   }
   1461 }
   1462 layer {
   1463   name: "bn_stage1_block3_branch2b"
   1464   type: "BatchNorm"
   1465   bottom: "conv_stage1_block3_branch2b"
   1466   top: "conv_stage1_block3_branch2b"
   1467   param {
   1468     lr_mult: 0
   1469     decay_mult: 0
   1470   }
   1471   param {
   1472     lr_mult: 0
   1473     decay_mult: 0
   1474   }
   1475   param {
   1476     lr_mult: 0
   1477     decay_mult: 0
   1478   }
   1479   batch_norm_param {
   1480     use_global_stats: true
   1481   }
   1482 }
   1483 layer {
   1484   name: "scale_stage1_block3_branch2b"
   1485   type: "Scale"
   1486   bottom: "conv_stage1_block3_branch2b"
   1487   top: "conv_stage1_block3_branch2b"
   1488   scale_param {
   1489     bias_term: true
   1490   }
   1491 }
   1492 layer {
   1493   name: "relu_stage1_block3_branch2b"
   1494   type: "ReLU"
   1495   bottom: "conv_stage1_block3_branch2b"
   1496   top: "conv_stage1_block3_branch2b"
   1497 }
   1498 layer {
   1499   name: "conv_stage1_block3_branch2c"
   1500   type: "Convolution"
   1501   bottom: "conv_stage1_block3_branch2b"
   1502   top: "conv_stage1_block3_branch2c"
   1503   param {
   1504     lr_mult: 1
   1505     decay_mult: 1
   1506   }
   1507   param {
   1508     lr_mult: 2
   1509     decay_mult: 0
   1510   }
   1511   convolution_param {
   1512     num_output: 256
   1513     pad: 0
   1514     kernel_size: 1
   1515     stride: 1
   1516     weight_filler {
   1517       type: "xavier"
   1518     }
   1519     bias_filler {
   1520       type: "constant"
   1521       value: 0
   1522     }
   1523   }
   1524 }
   1525 layer {
   1526   name: "bn_stage1_block3_branch2c"
   1527   type: "BatchNorm"
   1528   bottom: "conv_stage1_block3_branch2c"
   1529   top: "conv_stage1_block3_branch2c"
   1530   param {
   1531     lr_mult: 0
   1532     decay_mult: 0
   1533   }
   1534   param {
   1535     lr_mult: 0
   1536     decay_mult: 0
   1537   }
   1538   param {
   1539     lr_mult: 0
   1540     decay_mult: 0
   1541   }
   1542   batch_norm_param {
   1543     use_global_stats: true
   1544   }
   1545 }
   1546 layer {
   1547   name: "scale_stage1_block3_branch2c"
   1548   type: "Scale"
   1549   bottom: "conv_stage1_block3_branch2c"
   1550   top: "conv_stage1_block3_branch2c"
   1551   scale_param {
   1552     bias_term: true
   1553   }
   1554 }
   1555 layer {
   1556   name: "eltwise_stage1_block3"
   1557   type: "Eltwise"
   1558   bottom: "eltwise_stage1_block2"
   1559   bottom: "conv_stage1_block3_branch2c"
   1560   top: "eltwise_stage1_block3"
   1561 }
   1562 layer {
   1563   name: "relu_stage1_block3"
   1564   type: "ReLU"
   1565   bottom: "eltwise_stage1_block3"
   1566   top: "eltwise_stage1_block3"
   1567 }
   1568 layer {
   1569   name: "conv_stage2_block0_proj_shortcut"
   1570   type: "Convolution"
   1571   bottom: "eltwise_stage1_block3"
   1572   top: "conv_stage2_block0_proj_shortcut"
   1573   param {
   1574     lr_mult: 1
   1575     decay_mult: 1
   1576   }
   1577   param {
   1578     lr_mult: 2
   1579     decay_mult: 0
   1580   }
   1581   convolution_param {
   1582     num_output: 512
   1583     pad: 0
   1584     kernel_size: 1
   1585     stride: 2
   1586     weight_filler {
   1587       type: "xavier"
   1588     }
   1589     bias_filler {
   1590       type: "constant"
   1591       value: 0
   1592     }
   1593   }
   1594 }
   1595 layer {
   1596   name: "bn_stage2_block0_proj_shortcut"
   1597   type: "BatchNorm"
   1598   bottom: "conv_stage2_block0_proj_shortcut"
   1599   top: "conv_stage2_block0_proj_shortcut"
   1600   param {
   1601     lr_mult: 0
   1602     decay_mult: 0
   1603   }
   1604   param {
   1605     lr_mult: 0
   1606     decay_mult: 0
   1607   }
   1608   param {
   1609     lr_mult: 0
   1610     decay_mult: 0
   1611   }
   1612   batch_norm_param {
   1613     use_global_stats: true
   1614   }
   1615 }
   1616 layer {
   1617   name: "scale_stage2_block0_proj_shortcut"
   1618   type: "Scale"
   1619   bottom: "conv_stage2_block0_proj_shortcut"
   1620   top: "conv_stage2_block0_proj_shortcut"
   1621   scale_param {
   1622     bias_term: true
   1623   }
   1624 }
   1625 layer {
   1626   name: "conv_stage2_block0_branch2a"
   1627   type: "Convolution"
   1628   bottom: "eltwise_stage1_block3"
   1629   top: "conv_stage2_block0_branch2a"
   1630   param {
   1631     lr_mult: 1
   1632     decay_mult: 1
   1633   }
   1634   param {
   1635     lr_mult: 2
   1636     decay_mult: 0
   1637   }
   1638   convolution_param {
   1639     num_output: 128
   1640     pad: 0
   1641     kernel_size: 1
   1642     stride: 2
   1643     weight_filler {
   1644       type: "xavier"
   1645     }
   1646     bias_filler {
   1647       type: "constant"
   1648       value: 0
   1649     }
   1650   }
   1651 }
   1652 layer {
   1653   name: "bn_stage2_block0_branch2a"
   1654   type: "BatchNorm"
   1655   bottom: "conv_stage2_block0_branch2a"
   1656   top: "conv_stage2_block0_branch2a"
   1657   param {
   1658     lr_mult: 0
   1659     decay_mult: 0
   1660   }
   1661   param {
   1662     lr_mult: 0
   1663     decay_mult: 0
   1664   }
   1665   param {
   1666     lr_mult: 0
   1667     decay_mult: 0
   1668   }
   1669   batch_norm_param {
   1670     use_global_stats: true
   1671   }
   1672 }
   1673 layer {
   1674   name: "scale_stage2_block0_branch2a"
   1675   type: "Scale"
   1676   bottom: "conv_stage2_block0_branch2a"
   1677   top: "conv_stage2_block0_branch2a"
   1678   scale_param {
   1679     bias_term: true
   1680   }
   1681 }
   1682 layer {
   1683   name: "relu_stage2_block0_branch2a"
   1684   type: "ReLU"
   1685   bottom: "conv_stage2_block0_branch2a"
   1686   top: "conv_stage2_block0_branch2a"
   1687 }
   1688 layer {
   1689   name: "conv_stage2_block0_branch2b"
   1690   type: "Convolution"
   1691   bottom: "conv_stage2_block0_branch2a"
   1692   top: "conv_stage2_block0_branch2b"
   1693   param {
   1694     lr_mult: 1
   1695     decay_mult: 1
   1696   }
   1697   param {
   1698     lr_mult: 2
   1699     decay_mult: 0
   1700   }
   1701   convolution_param {
   1702     num_output: 128
   1703     pad: 1
   1704     kernel_size: 3
   1705     stride: 1
   1706     weight_filler {
   1707       type: "xavier"
   1708     }
   1709     bias_filler {
   1710       type: "constant"
   1711       value: 0
   1712     }
   1713   }
   1714 }
   1715 layer {
   1716   name: "bn_stage2_block0_branch2b"
   1717   type: "BatchNorm"
   1718   bottom: "conv_stage2_block0_branch2b"
   1719   top: "conv_stage2_block0_branch2b"
   1720   param {
   1721     lr_mult: 0
   1722     decay_mult: 0
   1723   }
   1724   param {
   1725     lr_mult: 0
   1726     decay_mult: 0
   1727   }
   1728   param {
   1729     lr_mult: 0
   1730     decay_mult: 0
   1731   }
   1732   batch_norm_param {
   1733     use_global_stats: true
   1734   }
   1735 }
   1736 layer {
   1737   name: "scale_stage2_block0_branch2b"
   1738   type: "Scale"
   1739   bottom: "conv_stage2_block0_branch2b"
   1740   top: "conv_stage2_block0_branch2b"
   1741   scale_param {
   1742     bias_term: true
   1743   }
   1744 }
   1745 layer {
   1746   name: "relu_stage2_block0_branch2b"
   1747   type: "ReLU"
   1748   bottom: "conv_stage2_block0_branch2b"
   1749   top: "conv_stage2_block0_branch2b"
   1750 }
   1751 layer {
   1752   name: "conv_stage2_block0_branch2c"
   1753   type: "Convolution"
   1754   bottom: "conv_stage2_block0_branch2b"
   1755   top: "conv_stage2_block0_branch2c"
   1756   param {
   1757     lr_mult: 1
   1758     decay_mult: 1
   1759   }
   1760   param {
   1761     lr_mult: 2
   1762     decay_mult: 0
   1763   }
   1764   convolution_param {
   1765     num_output: 512
   1766     pad: 0
   1767     kernel_size: 1
   1768     stride: 1
   1769     weight_filler {
   1770       type: "xavier"
   1771     }
   1772     bias_filler {
   1773       type: "constant"
   1774       value: 0
   1775     }
   1776   }
   1777 }
   1778 layer {
   1779   name: "bn_stage2_block0_branch2c"
   1780   type: "BatchNorm"
   1781   bottom: "conv_stage2_block0_branch2c"
   1782   top: "conv_stage2_block0_branch2c"
   1783   param {
   1784     lr_mult: 0
   1785     decay_mult: 0
   1786   }
   1787   param {
   1788     lr_mult: 0
   1789     decay_mult: 0
   1790   }
   1791   param {
   1792     lr_mult: 0
   1793     decay_mult: 0
   1794   }
   1795   batch_norm_param {
   1796     use_global_stats: true
   1797   }
   1798 }
   1799 layer {
   1800   name: "scale_stage2_block0_branch2c"
   1801   type: "Scale"
   1802   bottom: "conv_stage2_block0_branch2c"
   1803   top: "conv_stage2_block0_branch2c"
   1804   scale_param {
   1805     bias_term: true
   1806   }
   1807 }
   1808 layer {
   1809   name: "eltwise_stage2_block0"
   1810   type: "Eltwise"
   1811   bottom: "conv_stage2_block0_proj_shortcut"
   1812   bottom: "conv_stage2_block0_branch2c"
   1813   top: "eltwise_stage2_block0"
   1814 }
   1815 layer {
   1816   name: "relu_stage2_block0"
   1817   type: "ReLU"
   1818   bottom: "eltwise_stage2_block0"
   1819   top: "eltwise_stage2_block0"
   1820 }
   1821 layer {
   1822   name: "conv_stage2_block1_branch2a"
   1823   type: "Convolution"
   1824   bottom: "eltwise_stage2_block0"
   1825   top: "conv_stage2_block1_branch2a"
   1826   param {
   1827     lr_mult: 1
   1828     decay_mult: 1
   1829   }
   1830   param {
   1831     lr_mult: 2
   1832     decay_mult: 0
   1833   }
   1834   convolution_param {
   1835     num_output: 128
   1836     pad: 0
   1837     kernel_size: 1
   1838     stride: 1
   1839     weight_filler {
   1840       type: "xavier"
   1841     }
   1842     bias_filler {
   1843       type: "constant"
   1844       value: 0
   1845     }
   1846   }
   1847 }
   1848 layer {
   1849   name: "bn_stage2_block1_branch2a"
   1850   type: "BatchNorm"
   1851   bottom: "conv_stage2_block1_branch2a"
   1852   top: "conv_stage2_block1_branch2a"
   1853   param {
   1854     lr_mult: 0
   1855     decay_mult: 0
   1856   }
   1857   param {
   1858     lr_mult: 0
   1859     decay_mult: 0
   1860   }
   1861   param {
   1862     lr_mult: 0
   1863     decay_mult: 0
   1864   }
   1865   batch_norm_param {
   1866     use_global_stats: true
   1867   }
   1868 }
   1869 layer {
   1870   name: "scale_stage2_block1_branch2a"
   1871   type: "Scale"
   1872   bottom: "conv_stage2_block1_branch2a"
   1873   top: "conv_stage2_block1_branch2a"
   1874   scale_param {
   1875     bias_term: true
   1876   }
   1877 }
   1878 layer {
   1879   name: "relu_stage2_block1_branch2a"
   1880   type: "ReLU"
   1881   bottom: "conv_stage2_block1_branch2a"
   1882   top: "conv_stage2_block1_branch2a"
   1883 }
   1884 layer {
   1885   name: "conv_stage2_block1_branch2b"
   1886   type: "Convolution"
   1887   bottom: "conv_stage2_block1_branch2a"
   1888   top: "conv_stage2_block1_branch2b"
   1889   param {
   1890     lr_mult: 1
   1891     decay_mult: 1
   1892   }
   1893   param {
   1894     lr_mult: 2
   1895     decay_mult: 0
   1896   }
   1897   convolution_param {
   1898     num_output: 128
   1899     pad: 1
   1900     kernel_size: 3
   1901     stride: 1
   1902     weight_filler {
   1903       type: "xavier"
   1904     }
   1905     bias_filler {
   1906       type: "constant"
   1907       value: 0
   1908     }
   1909   }
   1910 }
   1911 layer {
   1912   name: "bn_stage2_block1_branch2b"
   1913   type: "BatchNorm"
   1914   bottom: "conv_stage2_block1_branch2b"
   1915   top: "conv_stage2_block1_branch2b"
   1916   param {
   1917     lr_mult: 0
   1918     decay_mult: 0
   1919   }
   1920   param {
   1921     lr_mult: 0
   1922     decay_mult: 0
   1923   }
   1924   param {
   1925     lr_mult: 0
   1926     decay_mult: 0
   1927   }
   1928   batch_norm_param {
   1929     use_global_stats: true
   1930   }
   1931 }
   1932 layer {
   1933   name: "scale_stage2_block1_branch2b"
   1934   type: "Scale"
   1935   bottom: "conv_stage2_block1_branch2b"
   1936   top: "conv_stage2_block1_branch2b"
   1937   scale_param {
   1938     bias_term: true
   1939   }
   1940 }
   1941 layer {
   1942   name: "relu_stage2_block1_branch2b"
   1943   type: "ReLU"
   1944   bottom: "conv_stage2_block1_branch2b"
   1945   top: "conv_stage2_block1_branch2b"
   1946 }
   1947 layer {
   1948   name: "conv_stage2_block1_branch2c"
   1949   type: "Convolution"
   1950   bottom: "conv_stage2_block1_branch2b"
   1951   top: "conv_stage2_block1_branch2c"
   1952   param {
   1953     lr_mult: 1
   1954     decay_mult: 1
   1955   }
   1956   param {
   1957     lr_mult: 2
   1958     decay_mult: 0
   1959   }
   1960   convolution_param {
   1961     num_output: 512
   1962     pad: 0
   1963     kernel_size: 1
   1964     stride: 1
   1965     weight_filler {
   1966       type: "xavier"
   1967     }
   1968     bias_filler {
   1969       type: "constant"
   1970       value: 0
   1971     }
   1972   }
   1973 }
   1974 layer {
   1975   name: "bn_stage2_block1_branch2c"
   1976   type: "BatchNorm"
   1977   bottom: "conv_stage2_block1_branch2c"
   1978   top: "conv_stage2_block1_branch2c"
   1979   param {
   1980     lr_mult: 0
   1981     decay_mult: 0
   1982   }
   1983   param {
   1984     lr_mult: 0
   1985     decay_mult: 0
   1986   }
   1987   param {
   1988     lr_mult: 0
   1989     decay_mult: 0
   1990   }
   1991   batch_norm_param {
   1992     use_global_stats: true
   1993   }
   1994 }
   1995 layer {
   1996   name: "scale_stage2_block1_branch2c"
   1997   type: "Scale"
   1998   bottom: "conv_stage2_block1_branch2c"
   1999   top: "conv_stage2_block1_branch2c"
   2000   scale_param {
   2001     bias_term: true
   2002   }
   2003 }
   2004 layer {
   2005   name: "eltwise_stage2_block1"
   2006   type: "Eltwise"
   2007   bottom: "eltwise_stage2_block0"
   2008   bottom: "conv_stage2_block1_branch2c"
   2009   top: "eltwise_stage2_block1"
   2010 }
   2011 layer {
   2012   name: "relu_stage2_block1"
   2013   type: "ReLU"
   2014   bottom: "eltwise_stage2_block1"
   2015   top: "eltwise_stage2_block1"
   2016 }
   2017 layer {
   2018   name: "conv_stage2_block2_branch2a"
   2019   type: "Convolution"
   2020   bottom: "eltwise_stage2_block1"
   2021   top: "conv_stage2_block2_branch2a"
   2022   param {
   2023     lr_mult: 1
   2024     decay_mult: 1
   2025   }
   2026   param {
   2027     lr_mult: 2
   2028     decay_mult: 0
   2029   }
   2030   convolution_param {
   2031     num_output: 128
   2032     pad: 0
   2033     kernel_size: 1
   2034     stride: 1
   2035     weight_filler {
   2036       type: "xavier"
   2037     }
   2038     bias_filler {
   2039       type: "constant"
   2040       value: 0
   2041     }
   2042   }
   2043 }
   2044 layer {
   2045   name: "bn_stage2_block2_branch2a"
   2046   type: "BatchNorm"
   2047   bottom: "conv_stage2_block2_branch2a"
   2048   top: "conv_stage2_block2_branch2a"
   2049   param {
   2050     lr_mult: 0
   2051     decay_mult: 0
   2052   }
   2053   param {
   2054     lr_mult: 0
   2055     decay_mult: 0
   2056   }
   2057   param {
   2058     lr_mult: 0
   2059     decay_mult: 0
   2060   }
   2061   batch_norm_param {
   2062     use_global_stats: true
   2063   }
   2064 }
   2065 layer {
   2066   name: "scale_stage2_block2_branch2a"
   2067   type: "Scale"
   2068   bottom: "conv_stage2_block2_branch2a"
   2069   top: "conv_stage2_block2_branch2a"
   2070   scale_param {
   2071     bias_term: true
   2072   }
   2073 }
   2074 layer {
   2075   name: "relu_stage2_block2_branch2a"
   2076   type: "ReLU"
   2077   bottom: "conv_stage2_block2_branch2a"
   2078   top: "conv_stage2_block2_branch2a"
   2079 }
   2080 layer {
   2081   name: "conv_stage2_block2_branch2b"
   2082   type: "Convolution"
   2083   bottom: "conv_stage2_block2_branch2a"
   2084   top: "conv_stage2_block2_branch2b"
   2085   param {
   2086     lr_mult: 1
   2087     decay_mult: 1
   2088   }
   2089   param {
   2090     lr_mult: 2
   2091     decay_mult: 0
   2092   }
   2093   convolution_param {
   2094     num_output: 128
   2095     pad: 1
   2096     kernel_size: 3
   2097     stride: 1
   2098     weight_filler {
   2099       type: "xavier"
   2100     }
   2101     bias_filler {
   2102       type: "constant"
   2103       value: 0
   2104     }
   2105   }
   2106 }
   2107 layer {
   2108   name: "bn_stage2_block2_branch2b"
   2109   type: "BatchNorm"
   2110   bottom: "conv_stage2_block2_branch2b"
   2111   top: "conv_stage2_block2_branch2b"
   2112   param {
   2113     lr_mult: 0
   2114     decay_mult: 0
   2115   }
   2116   param {
   2117     lr_mult: 0
   2118     decay_mult: 0
   2119   }
   2120   param {
   2121     lr_mult: 0
   2122     decay_mult: 0
   2123   }
   2124   batch_norm_param {
   2125     use_global_stats: true
   2126   }
   2127 }
   2128 layer {
   2129   name: "scale_stage2_block2_branch2b"
   2130   type: "Scale"
   2131   bottom: "conv_stage2_block2_branch2b"
   2132   top: "conv_stage2_block2_branch2b"
   2133   scale_param {
   2134     bias_term: true
   2135   }
   2136 }
   2137 layer {
   2138   name: "relu_stage2_block2_branch2b"
   2139   type: "ReLU"
   2140   bottom: "conv_stage2_block2_branch2b"
   2141   top: "conv_stage2_block2_branch2b"
   2142 }
   2143 layer {
   2144   name: "conv_stage2_block2_branch2c"
   2145   type: "Convolution"
   2146   bottom: "conv_stage2_block2_branch2b"
   2147   top: "conv_stage2_block2_branch2c"
   2148   param {
   2149     lr_mult: 1
   2150     decay_mult: 1
   2151   }
   2152   param {
   2153     lr_mult: 2
   2154     decay_mult: 0
   2155   }
   2156   convolution_param {
   2157     num_output: 512
   2158     pad: 0
   2159     kernel_size: 1
   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: "bn_stage2_block2_branch2c"
   2172   type: "BatchNorm"
   2173   bottom: "conv_stage2_block2_branch2c"
   2174   top: "conv_stage2_block2_branch2c"
   2175   param {
   2176     lr_mult: 0
   2177     decay_mult: 0
   2178   }
   2179   param {
   2180     lr_mult: 0
   2181     decay_mult: 0
   2182   }
   2183   param {
   2184     lr_mult: 0
   2185     decay_mult: 0
   2186   }
   2187   batch_norm_param {
   2188     use_global_stats: true
   2189   }
   2190 }
   2191 layer {
   2192   name: "scale_stage2_block2_branch2c"
   2193   type: "Scale"
   2194   bottom: "conv_stage2_block2_branch2c"
   2195   top: "conv_stage2_block2_branch2c"
   2196   scale_param {
   2197     bias_term: true
   2198   }
   2199 }
   2200 layer {
   2201   name: "eltwise_stage2_block2"
   2202   type: "Eltwise"
   2203   bottom: "eltwise_stage2_block1"
   2204   bottom: "conv_stage2_block2_branch2c"
   2205   top: "eltwise_stage2_block2"
   2206 }
   2207 layer {
   2208   name: "relu_stage2_block2"
   2209   type: "ReLU"
   2210   bottom: "eltwise_stage2_block2"
   2211   top: "eltwise_stage2_block2"
   2212 }
   2213 layer {
   2214   name: "conv_stage2_block3_branch2a"
   2215   type: "Convolution"
   2216   bottom: "eltwise_stage2_block2"
   2217   top: "conv_stage2_block3_branch2a"
   2218   param {
   2219     lr_mult: 1
   2220     decay_mult: 1
   2221   }
   2222   param {
   2223     lr_mult: 2
   2224     decay_mult: 0
   2225   }
   2226   convolution_param {
   2227     num_output: 128
   2228     pad: 0
   2229     kernel_size: 1
   2230     stride: 1
   2231     weight_filler {
   2232       type: "xavier"
   2233     }
   2234     bias_filler {
   2235       type: "constant"
   2236       value: 0
   2237     }
   2238   }
   2239 }
   2240 layer {
   2241   name: "bn_stage2_block3_branch2a"
   2242   type: "BatchNorm"
   2243   bottom: "conv_stage2_block3_branch2a"
   2244   top: "conv_stage2_block3_branch2a"
   2245   param {
   2246     lr_mult: 0
   2247     decay_mult: 0
   2248   }
   2249   param {
   2250     lr_mult: 0
   2251     decay_mult: 0
   2252   }
   2253   param {
   2254     lr_mult: 0
   2255     decay_mult: 0
   2256   }
   2257   batch_norm_param {
   2258     use_global_stats: true
   2259   }
   2260 }
   2261 layer {
   2262   name: "scale_stage2_block3_branch2a"
   2263   type: "Scale"
   2264   bottom: "conv_stage2_block3_branch2a"
   2265   top: "conv_stage2_block3_branch2a"
   2266   scale_param {
   2267     bias_term: true
   2268   }
   2269 }
   2270 layer {
   2271   name: "relu_stage2_block3_branch2a"
   2272   type: "ReLU"
   2273   bottom: "conv_stage2_block3_branch2a"
   2274   top: "conv_stage2_block3_branch2a"
   2275 }
   2276 layer {
   2277   name: "conv_stage2_block3_branch2b"
   2278   type: "Convolution"
   2279   bottom: "conv_stage2_block3_branch2a"
   2280   top: "conv_stage2_block3_branch2b"
   2281   param {
   2282     lr_mult: 1
   2283     decay_mult: 1
   2284   }
   2285   param {
   2286     lr_mult: 2
   2287     decay_mult: 0
   2288   }
   2289   convolution_param {
   2290     num_output: 128
   2291     pad: 1
   2292     kernel_size: 3
   2293     stride: 1
   2294     weight_filler {
   2295       type: "xavier"
   2296     }
   2297     bias_filler {
   2298       type: "constant"
   2299       value: 0
   2300     }
   2301   }
   2302 }
   2303 layer {
   2304   name: "bn_stage2_block3_branch2b"
   2305   type: "BatchNorm"
   2306   bottom: "conv_stage2_block3_branch2b"
   2307   top: "conv_stage2_block3_branch2b"
   2308   param {
   2309     lr_mult: 0
   2310     decay_mult: 0
   2311   }
   2312   param {
   2313     lr_mult: 0
   2314     decay_mult: 0
   2315   }
   2316   param {
   2317     lr_mult: 0
   2318     decay_mult: 0
   2319   }
   2320   batch_norm_param {
   2321     use_global_stats: true
   2322   }
   2323 }
   2324 layer {
   2325   name: "scale_stage2_block3_branch2b"
   2326   type: "Scale"
   2327   bottom: "conv_stage2_block3_branch2b"
   2328   top: "conv_stage2_block3_branch2b"
   2329   scale_param {
   2330     bias_term: true
   2331   }
   2332 }
   2333 layer {
   2334   name: "relu_stage2_block3_branch2b"
   2335   type: "ReLU"
   2336   bottom: "conv_stage2_block3_branch2b"
   2337   top: "conv_stage2_block3_branch2b"
   2338 }
   2339 layer {
   2340   name: "conv_stage2_block3_branch2c"
   2341   type: "Convolution"
   2342   bottom: "conv_stage2_block3_branch2b"
   2343   top: "conv_stage2_block3_branch2c"
   2344   param {
   2345     lr_mult: 1
   2346     decay_mult: 1
   2347   }
   2348   param {
   2349     lr_mult: 2
   2350     decay_mult: 0
   2351   }
   2352   convolution_param {
   2353     num_output: 512
   2354     pad: 0
   2355     kernel_size: 1
   2356     stride: 1
   2357     weight_filler {
   2358       type: "xavier"
   2359     }
   2360     bias_filler {
   2361       type: "constant"
   2362       value: 0
   2363     }
   2364   }
   2365 }
   2366 layer {
   2367   name: "bn_stage2_block3_branch2c"
   2368   type: "BatchNorm"
   2369   bottom: "conv_stage2_block3_branch2c"
   2370   top: "conv_stage2_block3_branch2c"
   2371   param {
   2372     lr_mult: 0
   2373     decay_mult: 0
   2374   }
   2375   param {
   2376     lr_mult: 0
   2377     decay_mult: 0
   2378   }
   2379   param {
   2380     lr_mult: 0
   2381     decay_mult: 0
   2382   }
   2383   batch_norm_param {
   2384     use_global_stats: true
   2385   }
   2386 }
   2387 layer {
   2388   name: "scale_stage2_block3_branch2c"
   2389   type: "Scale"
   2390   bottom: "conv_stage2_block3_branch2c"
   2391   top: "conv_stage2_block3_branch2c"
   2392   scale_param {
   2393     bias_term: true
   2394   }
   2395 }
   2396 layer {
   2397   name: "eltwise_stage2_block3"
   2398   type: "Eltwise"
   2399   bottom: "eltwise_stage2_block2"
   2400   bottom: "conv_stage2_block3_branch2c"
   2401   top: "eltwise_stage2_block3"
   2402 }
   2403 layer {
   2404   name: "relu_stage2_block3"
   2405   type: "ReLU"
   2406   bottom: "eltwise_stage2_block3"
   2407   top: "eltwise_stage2_block3"
   2408 }
   2409 layer {
   2410   name: "conv_stage2_block4_branch2a"
   2411   type: "Convolution"
   2412   bottom: "eltwise_stage2_block3"
   2413   top: "conv_stage2_block4_branch2a"
   2414   param {
   2415     lr_mult: 1
   2416     decay_mult: 1
   2417   }
   2418   param {
   2419     lr_mult: 2
   2420     decay_mult: 0
   2421   }
   2422   convolution_param {
   2423     num_output: 128
   2424     pad: 0
   2425     kernel_size: 1
   2426     stride: 1
   2427     weight_filler {
   2428       type: "xavier"
   2429     }
   2430     bias_filler {
   2431       type: "constant"
   2432       value: 0
   2433     }
   2434   }
   2435 }
   2436 layer {
   2437   name: "bn_stage2_block4_branch2a"
   2438   type: "BatchNorm"
   2439   bottom: "conv_stage2_block4_branch2a"
   2440   top: "conv_stage2_block4_branch2a"
   2441   param {
   2442     lr_mult: 0
   2443     decay_mult: 0
   2444   }
   2445   param {
   2446     lr_mult: 0
   2447     decay_mult: 0
   2448   }
   2449   param {
   2450     lr_mult: 0
   2451     decay_mult: 0
   2452   }
   2453   batch_norm_param {
   2454     use_global_stats: true
   2455   }
   2456 }
   2457 layer {
   2458   name: "scale_stage2_block4_branch2a"
   2459   type: "Scale"
   2460   bottom: "conv_stage2_block4_branch2a"
   2461   top: "conv_stage2_block4_branch2a"
   2462   scale_param {
   2463     bias_term: true
   2464   }
   2465 }
   2466 layer {
   2467   name: "relu_stage2_block4_branch2a"
   2468   type: "ReLU"
   2469   bottom: "conv_stage2_block4_branch2a"
   2470   top: "conv_stage2_block4_branch2a"
   2471 }
   2472 layer {
   2473   name: "conv_stage2_block4_branch2b"
   2474   type: "Convolution"
   2475   bottom: "conv_stage2_block4_branch2a"
   2476   top: "conv_stage2_block4_branch2b"
   2477   param {
   2478     lr_mult: 1
   2479     decay_mult: 1
   2480   }
   2481   param {
   2482     lr_mult: 2
   2483     decay_mult: 0
   2484   }
   2485   convolution_param {
   2486     num_output: 128
   2487     pad: 1
   2488     kernel_size: 3
   2489     stride: 1
   2490     weight_filler {
   2491       type: "xavier"
   2492     }
   2493     bias_filler {
   2494       type: "constant"
   2495       value: 0
   2496     }
   2497   }
   2498 }
   2499 layer {
   2500   name: "bn_stage2_block4_branch2b"
   2501   type: "BatchNorm"
   2502   bottom: "conv_stage2_block4_branch2b"
   2503   top: "conv_stage2_block4_branch2b"
   2504   param {
   2505     lr_mult: 0
   2506     decay_mult: 0
   2507   }
   2508   param {
   2509     lr_mult: 0
   2510     decay_mult: 0
   2511   }
   2512   param {
   2513     lr_mult: 0
   2514     decay_mult: 0
   2515   }
   2516   batch_norm_param {
   2517     use_global_stats: true
   2518   }
   2519 }
   2520 layer {
   2521   name: "scale_stage2_block4_branch2b"
   2522   type: "Scale"
   2523   bottom: "conv_stage2_block4_branch2b"
   2524   top: "conv_stage2_block4_branch2b"
   2525   scale_param {
   2526     bias_term: true
   2527   }
   2528 }
   2529 layer {
   2530   name: "relu_stage2_block4_branch2b"
   2531   type: "ReLU"
   2532   bottom: "conv_stage2_block4_branch2b"
   2533   top: "conv_stage2_block4_branch2b"
   2534 }
   2535 layer {
   2536   name: "conv_stage2_block4_branch2c"
   2537   type: "Convolution"
   2538   bottom: "conv_stage2_block4_branch2b"
   2539   top: "conv_stage2_block4_branch2c"
   2540   param {
   2541     lr_mult: 1
   2542     decay_mult: 1
   2543   }
   2544   param {
   2545     lr_mult: 2
   2546     decay_mult: 0
   2547   }
   2548   convolution_param {
   2549     num_output: 512
   2550     pad: 0
   2551     kernel_size: 1
   2552     stride: 1
   2553     weight_filler {
   2554       type: "xavier"
   2555     }
   2556     bias_filler {
   2557       type: "constant"
   2558       value: 0
   2559     }
   2560   }
   2561 }
   2562 layer {
   2563   name: "bn_stage2_block4_branch2c"
   2564   type: "BatchNorm"
   2565   bottom: "conv_stage2_block4_branch2c"
   2566   top: "conv_stage2_block4_branch2c"
   2567   param {
   2568     lr_mult: 0
   2569     decay_mult: 0
   2570   }
   2571   param {
   2572     lr_mult: 0
   2573     decay_mult: 0
   2574   }
   2575   param {
   2576     lr_mult: 0
   2577     decay_mult: 0
   2578   }
   2579   batch_norm_param {
   2580     use_global_stats: true
   2581   }
   2582 }
   2583 layer {
   2584   name: "scale_stage2_block4_branch2c"
   2585   type: "Scale"
   2586   bottom: "conv_stage2_block4_branch2c"
   2587   top: "conv_stage2_block4_branch2c"
   2588   scale_param {
   2589     bias_term: true
   2590   }
   2591 }
   2592 layer {
   2593   name: "eltwise_stage2_block4"
   2594   type: "Eltwise"
   2595   bottom: "eltwise_stage2_block3"
   2596   bottom: "conv_stage2_block4_branch2c"
   2597   top: "eltwise_stage2_block4"
   2598 }
   2599 layer {
   2600   name: "relu_stage2_block4"
   2601   type: "ReLU"
   2602   bottom: "eltwise_stage2_block4"
   2603   top: "eltwise_stage2_block4"
   2604 }
   2605 layer {
   2606   name: "conv_stage2_block5_branch2a"
   2607   type: "Convolution"
   2608   bottom: "eltwise_stage2_block4"
   2609   top: "conv_stage2_block5_branch2a"
   2610   param {
   2611     lr_mult: 1
   2612     decay_mult: 1
   2613   }
   2614   param {
   2615     lr_mult: 2
   2616     decay_mult: 0
   2617   }
   2618   convolution_param {
   2619     num_output: 128
   2620     pad: 0
   2621     kernel_size: 1
   2622     stride: 1
   2623     weight_filler {
   2624       type: "xavier"
   2625     }
   2626     bias_filler {
   2627       type: "constant"
   2628       value: 0
   2629     }
   2630   }
   2631 }
   2632 layer {
   2633   name: "bn_stage2_block5_branch2a"
   2634   type: "BatchNorm"
   2635   bottom: "conv_stage2_block5_branch2a"
   2636   top: "conv_stage2_block5_branch2a"
   2637   param {
   2638     lr_mult: 0
   2639     decay_mult: 0
   2640   }
   2641   param {
   2642     lr_mult: 0
   2643     decay_mult: 0
   2644   }
   2645   param {
   2646     lr_mult: 0
   2647     decay_mult: 0
   2648   }
   2649   batch_norm_param {
   2650     use_global_stats: true
   2651   }
   2652 }
   2653 layer {
   2654   name: "scale_stage2_block5_branch2a"
   2655   type: "Scale"
   2656   bottom: "conv_stage2_block5_branch2a"
   2657   top: "conv_stage2_block5_branch2a"
   2658   scale_param {
   2659     bias_term: true
   2660   }
   2661 }
   2662 layer {
   2663   name: "relu_stage2_block5_branch2a"
   2664   type: "ReLU"
   2665   bottom: "conv_stage2_block5_branch2a"
   2666   top: "conv_stage2_block5_branch2a"
   2667 }
   2668 layer {
   2669   name: "conv_stage2_block5_branch2b"
   2670   type: "Convolution"
   2671   bottom: "conv_stage2_block5_branch2a"
   2672   top: "conv_stage2_block5_branch2b"
   2673   param {
   2674     lr_mult: 1
   2675     decay_mult: 1
   2676   }
   2677   param {
   2678     lr_mult: 2
   2679     decay_mult: 0
   2680   }
   2681   convolution_param {
   2682     num_output: 128
   2683     pad: 1
   2684     kernel_size: 3
   2685     stride: 1
   2686     weight_filler {
   2687       type: "xavier"
   2688     }
   2689     bias_filler {
   2690       type: "constant"
   2691       value: 0
   2692     }
   2693   }
   2694 }
   2695 layer {
   2696   name: "bn_stage2_block5_branch2b"
   2697   type: "BatchNorm"
   2698   bottom: "conv_stage2_block5_branch2b"
   2699   top: "conv_stage2_block5_branch2b"
   2700   param {
   2701     lr_mult: 0
   2702     decay_mult: 0
   2703   }
   2704   param {
   2705     lr_mult: 0
   2706     decay_mult: 0
   2707   }
   2708   param {
   2709     lr_mult: 0
   2710     decay_mult: 0
   2711   }
   2712   batch_norm_param {
   2713     use_global_stats: true
   2714   }
   2715 }
   2716 layer {
   2717   name: "scale_stage2_block5_branch2b"
   2718   type: "Scale"
   2719   bottom: "conv_stage2_block5_branch2b"
   2720   top: "conv_stage2_block5_branch2b"
   2721   scale_param {
   2722     bias_term: true
   2723   }
   2724 }
   2725 layer {
   2726   name: "relu_stage2_block5_branch2b"
   2727   type: "ReLU"
   2728   bottom: "conv_stage2_block5_branch2b"
   2729   top: "conv_stage2_block5_branch2b"
   2730 }
   2731 layer {
   2732   name: "conv_stage2_block5_branch2c"
   2733   type: "Convolution"
   2734   bottom: "conv_stage2_block5_branch2b"
   2735   top: "conv_stage2_block5_branch2c"
   2736   param {
   2737     lr_mult: 1
   2738     decay_mult: 1
   2739   }
   2740   param {
   2741     lr_mult: 2
   2742     decay_mult: 0
   2743   }
   2744   convolution_param {
   2745     num_output: 512
   2746     pad: 0
   2747     kernel_size: 1
   2748     stride: 1
   2749     weight_filler {
   2750       type: "xavier"
   2751     }
   2752     bias_filler {
   2753       type: "constant"
   2754       value: 0
   2755     }
   2756   }
   2757 }
   2758 layer {
   2759   name: "bn_stage2_block5_branch2c"
   2760   type: "BatchNorm"
   2761   bottom: "conv_stage2_block5_branch2c"
   2762   top: "conv_stage2_block5_branch2c"
   2763   param {
   2764     lr_mult: 0
   2765     decay_mult: 0
   2766   }
   2767   param {
   2768     lr_mult: 0
   2769     decay_mult: 0
   2770   }
   2771   param {
   2772     lr_mult: 0
   2773     decay_mult: 0
   2774   }
   2775   batch_norm_param {
   2776     use_global_stats: true
   2777   }
   2778 }
   2779 layer {
   2780   name: "scale_stage2_block5_branch2c"
   2781   type: "Scale"
   2782   bottom: "conv_stage2_block5_branch2c"
   2783   top: "conv_stage2_block5_branch2c"
   2784   scale_param {
   2785     bias_term: true
   2786   }
   2787 }
   2788 layer {
   2789   name: "eltwise_stage2_block5"
   2790   type: "Eltwise"
   2791   bottom: "eltwise_stage2_block4"
   2792   bottom: "conv_stage2_block5_branch2c"
   2793   top: "eltwise_stage2_block5"
   2794 }
   2795 layer {
   2796   name: "relu_stage2_block5"
   2797   type: "ReLU"
   2798   bottom: "eltwise_stage2_block5"
   2799   top: "eltwise_stage2_block5"
   2800 }
   2801 layer {
   2802   name: "conv_stage3_block0_proj_shortcut"
   2803   type: "Convolution"
   2804   bottom: "eltwise_stage2_block5"
   2805   top: "conv_stage3_block0_proj_shortcut"
   2806   param {
   2807     lr_mult: 1
   2808     decay_mult: 1
   2809   }
   2810   param {
   2811     lr_mult: 2
   2812     decay_mult: 0
   2813   }
   2814   convolution_param {
   2815     num_output: 1024
   2816     pad: 0
   2817     kernel_size: 1
   2818     stride: 2
   2819     weight_filler {
   2820       type: "xavier"
   2821     }
   2822     bias_filler {
   2823       type: "constant"
   2824       value: 0
   2825     }
   2826   }
   2827 }
   2828 layer {
   2829   name: "bn_stage3_block0_proj_shortcut"
   2830   type: "BatchNorm"
   2831   bottom: "conv_stage3_block0_proj_shortcut"
   2832   top: "conv_stage3_block0_proj_shortcut"
   2833   param {
   2834     lr_mult: 0
   2835     decay_mult: 0
   2836   }
   2837   param {
   2838     lr_mult: 0
   2839     decay_mult: 0
   2840   }
   2841   param {
   2842     lr_mult: 0
   2843     decay_mult: 0
   2844   }
   2845   batch_norm_param {
   2846     use_global_stats: true
   2847   }
   2848 }
   2849 layer {
   2850   name: "scale_stage3_block0_proj_shortcut"
   2851   type: "Scale"
   2852   bottom: "conv_stage3_block0_proj_shortcut"
   2853   top: "conv_stage3_block0_proj_shortcut"
   2854   scale_param {
   2855     bias_term: true
   2856   }
   2857 }
   2858 layer {
   2859   name: "conv_stage3_block0_branch2a"
   2860   type: "Convolution"
   2861   bottom: "eltwise_stage2_block5"
   2862   top: "conv_stage3_block0_branch2a"
   2863   param {
   2864     lr_mult: 1
   2865     decay_mult: 1
   2866   }
   2867   param {
   2868     lr_mult: 2
   2869     decay_mult: 0
   2870   }
   2871   convolution_param {
   2872     num_output: 256
   2873     pad: 0
   2874     kernel_size: 1
   2875     stride: 2
   2876     weight_filler {
   2877       type: "xavier"
   2878     }
   2879     bias_filler {
   2880       type: "constant"
   2881       value: 0
   2882     }
   2883   }
   2884 }
   2885 layer {
   2886   name: "bn_stage3_block0_branch2a"
   2887   type: "BatchNorm"
   2888   bottom: "conv_stage3_block0_branch2a"
   2889   top: "conv_stage3_block0_branch2a"
   2890   param {
   2891     lr_mult: 0
   2892     decay_mult: 0
   2893   }
   2894   param {
   2895     lr_mult: 0
   2896     decay_mult: 0
   2897   }
   2898   param {
   2899     lr_mult: 0
   2900     decay_mult: 0
   2901   }
   2902   batch_norm_param {
   2903     use_global_stats: true
   2904   }
   2905 }
   2906 layer {
   2907   name: "scale_stage3_block0_branch2a"
   2908   type: "Scale"
   2909   bottom: "conv_stage3_block0_branch2a"
   2910   top: "conv_stage3_block0_branch2a"
   2911   scale_param {
   2912     bias_term: true
   2913   }
   2914 }
   2915 layer {
   2916   name: "relu_stage3_block0_branch2a"
   2917   type: "ReLU"
   2918   bottom: "conv_stage3_block0_branch2a"
   2919   top: "conv_stage3_block0_branch2a"
   2920 }
   2921 layer {
   2922   name: "conv_stage3_block0_branch2b"
   2923   type: "Convolution"
   2924   bottom: "conv_stage3_block0_branch2a"
   2925   top: "conv_stage3_block0_branch2b"
   2926   param {
   2927     lr_mult: 1
   2928     decay_mult: 1
   2929   }
   2930   param {
   2931     lr_mult: 2
   2932     decay_mult: 0
   2933   }
   2934   convolution_param {
   2935     num_output: 256
   2936     pad: 1
   2937     kernel_size: 3
   2938     stride: 1
   2939     weight_filler {
   2940       type: "xavier"
   2941     }
   2942     bias_filler {
   2943       type: "constant"
   2944       value: 0
   2945     }
   2946   }
   2947 }
   2948 layer {
   2949   name: "bn_stage3_block0_branch2b"
   2950   type: "BatchNorm"
   2951   bottom: "conv_stage3_block0_branch2b"
   2952   top: "conv_stage3_block0_branch2b"
   2953   param {
   2954     lr_mult: 0
   2955     decay_mult: 0
   2956   }
   2957   param {
   2958     lr_mult: 0
   2959     decay_mult: 0
   2960   }
   2961   param {
   2962     lr_mult: 0
   2963     decay_mult: 0
   2964   }
   2965   batch_norm_param {
   2966     use_global_stats: true
   2967   }
   2968 }
   2969 layer {
   2970   name: "scale_stage3_block0_branch2b"
   2971   type: "Scale"
   2972   bottom: "conv_stage3_block0_branch2b"
   2973   top: "conv_stage3_block0_branch2b"
   2974   scale_param {
   2975     bias_term: true
   2976   }
   2977 }
   2978 layer {
   2979   name: "relu_stage3_block0_branch2b"
   2980   type: "ReLU"
   2981   bottom: "conv_stage3_block0_branch2b"
   2982   top: "conv_stage3_block0_branch2b"
   2983 }
   2984 layer {
   2985   name: "conv_stage3_block0_branch2c"
   2986   type: "Convolution"
   2987   bottom: "conv_stage3_block0_branch2b"
   2988   top: "conv_stage3_block0_branch2c"
   2989   param {
   2990     lr_mult: 1
   2991     decay_mult: 1
   2992   }
   2993   param {
   2994     lr_mult: 2
   2995     decay_mult: 0
   2996   }
   2997   convolution_param {
   2998     num_output: 1024
   2999     pad: 0
   3000     kernel_size: 1
   3001     stride: 1
   3002     weight_filler {
   3003       type: "xavier"
   3004     }
   3005     bias_filler {
   3006       type: "constant"
   3007       value: 0
   3008     }
   3009   }
   3010 }
   3011 layer {
   3012   name: "bn_stage3_block0_branch2c"
   3013   type: "BatchNorm"
   3014   bottom: "conv_stage3_block0_branch2c"
   3015   top: "conv_stage3_block0_branch2c"
   3016   param {
   3017     lr_mult: 0
   3018     decay_mult: 0
   3019   }
   3020   param {
   3021     lr_mult: 0
   3022     decay_mult: 0
   3023   }
   3024   param {
   3025     lr_mult: 0
   3026     decay_mult: 0
   3027   }
   3028   batch_norm_param {
   3029     use_global_stats: true
   3030   }
   3031 }
   3032 layer {
   3033   name: "scale_stage3_block0_branch2c"
   3034   type: "Scale"
   3035   bottom: "conv_stage3_block0_branch2c"
   3036   top: "conv_stage3_block0_branch2c"
   3037   scale_param {
   3038     bias_term: true
   3039   }
   3040 }
   3041 layer {
   3042   name: "eltwise_stage3_block0"
   3043   type: "Eltwise"
   3044   bottom: "conv_stage3_block0_proj_shortcut"
   3045   bottom: "conv_stage3_block0_branch2c"
   3046   top: "eltwise_stage3_block0"
   3047 }
   3048 layer {
   3049   name: "relu_stage3_block0"
   3050   type: "ReLU"
   3051   bottom: "eltwise_stage3_block0"
   3052   top: "eltwise_stage3_block0"
   3053 }
   3054 layer {
   3055   name: "conv_stage3_block1_branch2a"
   3056   type: "Convolution"
   3057   bottom: "eltwise_stage3_block0"
   3058   top: "conv_stage3_block1_branch2a"
   3059   param {
   3060     lr_mult: 1
   3061     decay_mult: 1
   3062   }
   3063   param {
   3064     lr_mult: 2
   3065     decay_mult: 0
   3066   }
   3067   convolution_param {
   3068     num_output: 256
   3069     pad: 0
   3070     kernel_size: 1
   3071     stride: 1
   3072     weight_filler {
   3073       type: "xavier"
   3074     }
   3075     bias_filler {
   3076       type: "constant"
   3077       value: 0
   3078     }
   3079   }
   3080 }
   3081 layer {
   3082   name: "bn_stage3_block1_branch2a"
   3083   type: "BatchNorm"
   3084   bottom: "conv_stage3_block1_branch2a"
   3085   top: "conv_stage3_block1_branch2a"
   3086   param {
   3087     lr_mult: 0
   3088     decay_mult: 0
   3089   }
   3090   param {
   3091     lr_mult: 0
   3092     decay_mult: 0
   3093   }
   3094   param {
   3095     lr_mult: 0
   3096     decay_mult: 0
   3097   }
   3098   batch_norm_param {
   3099     use_global_stats: true
   3100   }
   3101 }
   3102 layer {
   3103   name: "scale_stage3_block1_branch2a"
   3104   type: "Scale"
   3105   bottom: "conv_stage3_block1_branch2a"
   3106   top: "conv_stage3_block1_branch2a"
   3107   scale_param {
   3108     bias_term: true
   3109   }
   3110 }
   3111 layer {
   3112   name: "relu_stage3_block1_branch2a"
   3113   type: "ReLU"
   3114   bottom: "conv_stage3_block1_branch2a"
   3115   top: "conv_stage3_block1_branch2a"
   3116 }
   3117 layer {
   3118   name: "conv_stage3_block1_branch2b"
   3119   type: "Convolution"
   3120   bottom: "conv_stage3_block1_branch2a"
   3121   top: "conv_stage3_block1_branch2b"
   3122   param {
   3123     lr_mult: 1
   3124     decay_mult: 1
   3125   }
   3126   param {
   3127     lr_mult: 2
   3128     decay_mult: 0
   3129   }
   3130   convolution_param {
   3131     num_output: 256
   3132     pad: 1
   3133     kernel_size: 3
   3134     stride: 1
   3135     weight_filler {
   3136       type: "xavier"
   3137     }
   3138     bias_filler {
   3139       type: "constant"
   3140       value: 0
   3141     }
   3142   }
   3143 }
   3144 layer {
   3145   name: "bn_stage3_block1_branch2b"
   3146   type: "BatchNorm"
   3147   bottom: "conv_stage3_block1_branch2b"
   3148   top: "conv_stage3_block1_branch2b"
   3149   param {
   3150     lr_mult: 0
   3151     decay_mult: 0
   3152   }
   3153   param {
   3154     lr_mult: 0
   3155     decay_mult: 0
   3156   }
   3157   param {
   3158     lr_mult: 0
   3159     decay_mult: 0
   3160   }
   3161   batch_norm_param {
   3162     use_global_stats: true
   3163   }
   3164 }
   3165 layer {
   3166   name: "scale_stage3_block1_branch2b"
   3167   type: "Scale"
   3168   bottom: "conv_stage3_block1_branch2b"
   3169   top: "conv_stage3_block1_branch2b"
   3170   scale_param {
   3171     bias_term: true
   3172   }
   3173 }
   3174 layer {
   3175   name: "relu_stage3_block1_branch2b"
   3176   type: "ReLU"
   3177   bottom: "conv_stage3_block1_branch2b"
   3178   top: "conv_stage3_block1_branch2b"
   3179 }
   3180 layer {
   3181   name: "conv_stage3_block1_branch2c"
   3182   type: "Convolution"
   3183   bottom: "conv_stage3_block1_branch2b"
   3184   top: "conv_stage3_block1_branch2c"
   3185   param {
   3186     lr_mult: 1
   3187     decay_mult: 1
   3188   }
   3189   param {
   3190     lr_mult: 2
   3191     decay_mult: 0
   3192   }
   3193   convolution_param {
   3194     num_output: 1024
   3195     pad: 0
   3196     kernel_size: 1
   3197     stride: 1
   3198     weight_filler {
   3199       type: "xavier"
   3200     }
   3201     bias_filler {
   3202       type: "constant"
   3203       value: 0
   3204     }
   3205   }
   3206 }
   3207 layer {
   3208   name: "bn_stage3_block1_branch2c"
   3209   type: "BatchNorm"
   3210   bottom: "conv_stage3_block1_branch2c"
   3211   top: "conv_stage3_block1_branch2c"
   3212   param {
   3213     lr_mult: 0
   3214     decay_mult: 0
   3215   }
   3216   param {
   3217     lr_mult: 0
   3218     decay_mult: 0
   3219   }
   3220   param {
   3221     lr_mult: 0
   3222     decay_mult: 0
   3223   }
   3224   batch_norm_param {
   3225     use_global_stats: true
   3226   }
   3227 }
   3228 layer {
   3229   name: "scale_stage3_block1_branch2c"
   3230   type: "Scale"
   3231   bottom: "conv_stage3_block1_branch2c"
   3232   top: "conv_stage3_block1_branch2c"
   3233   scale_param {
   3234     bias_term: true
   3235   }
   3236 }
   3237 layer {
   3238   name: "eltwise_stage3_block1"
   3239   type: "Eltwise"
   3240   bottom: "eltwise_stage3_block0"
   3241   bottom: "conv_stage3_block1_branch2c"
   3242   top: "eltwise_stage3_block1"
   3243 }
   3244 layer {
   3245   name: "relu_stage3_block1"
   3246   type: "ReLU"
   3247   bottom: "eltwise_stage3_block1"
   3248   top: "eltwise_stage3_block1"
   3249 }
   3250 layer {
   3251   name: "conv_stage3_block2_branch2a"
   3252   type: "Convolution"
   3253   bottom: "eltwise_stage3_block1"
   3254   top: "conv_stage3_block2_branch2a"
   3255   param {
   3256     lr_mult: 1
   3257     decay_mult: 1
   3258   }
   3259   param {
   3260     lr_mult: 2
   3261     decay_mult: 0
   3262   }
   3263   convolution_param {
   3264     num_output: 256
   3265     pad: 0
   3266     kernel_size: 1
   3267     stride: 1
   3268     weight_filler {
   3269       type: "xavier"
   3270     }
   3271     bias_filler {
   3272       type: "constant"
   3273       value: 0
   3274     }
   3275   }
   3276 }
   3277 layer {
   3278   name: "bn_stage3_block2_branch2a"
   3279   type: "BatchNorm"
   3280   bottom: "conv_stage3_block2_branch2a"
   3281   top: "conv_stage3_block2_branch2a"
   3282   param {
   3283     lr_mult: 0
   3284     decay_mult: 0
   3285   }
   3286   param {
   3287     lr_mult: 0
   3288     decay_mult: 0
   3289   }
   3290   param {
   3291     lr_mult: 0
   3292     decay_mult: 0
   3293   }
   3294   batch_norm_param {
   3295     use_global_stats: true
   3296   }
   3297 }
   3298 layer {
   3299   name: "scale_stage3_block2_branch2a"
   3300   type: "Scale"
   3301   bottom: "conv_stage3_block2_branch2a"
   3302   top: "conv_stage3_block2_branch2a"
   3303   scale_param {
   3304     bias_term: true
   3305   }
   3306 }
   3307 layer {
   3308   name: "relu_stage3_block2_branch2a"
   3309   type: "ReLU"
   3310   bottom: "conv_stage3_block2_branch2a"
   3311   top: "conv_stage3_block2_branch2a"
   3312 }
   3313 layer {
   3314   name: "conv_stage3_block2_branch2b"
   3315   type: "Convolution"
   3316   bottom: "conv_stage3_block2_branch2a"
   3317   top: "conv_stage3_block2_branch2b"
   3318   param {
   3319     lr_mult: 1
   3320     decay_mult: 1
   3321   }
   3322   param {
   3323     lr_mult: 2
   3324     decay_mult: 0
   3325   }
   3326   convolution_param {
   3327     num_output: 256
   3328     pad: 1
   3329     kernel_size: 3
   3330     stride: 1
   3331     weight_filler {
   3332       type: "xavier"
   3333     }
   3334     bias_filler {
   3335       type: "constant"
   3336       value: 0
   3337     }
   3338   }
   3339 }
   3340 layer {
   3341   name: "bn_stage3_block2_branch2b"
   3342   type: "BatchNorm"
   3343   bottom: "conv_stage3_block2_branch2b"
   3344   top: "conv_stage3_block2_branch2b"
   3345   param {
   3346     lr_mult: 0
   3347     decay_mult: 0
   3348   }
   3349   param {
   3350     lr_mult: 0
   3351     decay_mult: 0
   3352   }
   3353   param {
   3354     lr_mult: 0
   3355     decay_mult: 0
   3356   }
   3357   batch_norm_param {
   3358     use_global_stats: true
   3359   }
   3360 }
   3361 layer {
   3362   name: "scale_stage3_block2_branch2b"
   3363   type: "Scale"
   3364   bottom: "conv_stage3_block2_branch2b"
   3365   top: "conv_stage3_block2_branch2b"
   3366   scale_param {
   3367     bias_term: true
   3368   }
   3369 }
   3370 layer {
   3371   name: "relu_stage3_block2_branch2b"
   3372   type: "ReLU"
   3373   bottom: "conv_stage3_block2_branch2b"
   3374   top: "conv_stage3_block2_branch2b"
   3375 }
   3376 layer {
   3377   name: "conv_stage3_block2_branch2c"
   3378   type: "Convolution"
   3379   bottom: "conv_stage3_block2_branch2b"
   3380   top: "conv_stage3_block2_branch2c"
   3381   param {
   3382     lr_mult: 1
   3383     decay_mult: 1
   3384   }
   3385   param {
   3386     lr_mult: 2
   3387     decay_mult: 0
   3388   }
   3389   convolution_param {
   3390     num_output: 1024
   3391     pad: 0
   3392     kernel_size: 1
   3393     stride: 1
   3394     weight_filler {
   3395       type: "xavier"
   3396     }
   3397     bias_filler {
   3398       type: "constant"
   3399       value: 0
   3400     }
   3401   }
   3402 }
   3403 layer {
   3404   name: "bn_stage3_block2_branch2c"
   3405   type: "BatchNorm"
   3406   bottom: "conv_stage3_block2_branch2c"
   3407   top: "conv_stage3_block2_branch2c"
   3408   param {
   3409     lr_mult: 0
   3410     decay_mult: 0
   3411   }
   3412   param {
   3413     lr_mult: 0
   3414     decay_mult: 0
   3415   }
   3416   param {
   3417     lr_mult: 0
   3418     decay_mult: 0
   3419   }
   3420   batch_norm_param {
   3421     use_global_stats: true
   3422   }
   3423 }
   3424 layer {
   3425   name: "scale_stage3_block2_branch2c"
   3426   type: "Scale"
   3427   bottom: "conv_stage3_block2_branch2c"
   3428   top: "conv_stage3_block2_branch2c"
   3429   scale_param {
   3430     bias_term: true
   3431   }
   3432 }
   3433 layer {
   3434   name: "eltwise_stage3_block2"
   3435   type: "Eltwise"
   3436   bottom: "eltwise_stage3_block1"
   3437   bottom: "conv_stage3_block2_branch2c"
   3438   top: "eltwise_stage3_block2"
   3439 }
   3440 layer {
   3441   name: "relu_stage3_block2"
   3442   type: "ReLU"
   3443   bottom: "eltwise_stage3_block2"
   3444   top: "eltwise_stage3_block2"
   3445 }
   3446 layer {
   3447   name: "pool"
   3448   type: "Pooling"
   3449   bottom: "eltwise_stage3_block2"
   3450   top: "pool"
   3451   pooling_param {
   3452     pool: AVE
   3453     kernel_size: 7
   3454     stride: 1
   3455   }
   3456 }
   3457 layer {
   3458    name: "fc_nsfw"
   3459    type: "InnerProduct"
   3460    bottom: "pool"
   3461    top: "fc_nsfw"
   3462    param {
   3463        lr_mult: 5
   3464        decay_mult: 1
   3465    }
   3466    param {
   3467        lr_mult: 10
   3468        decay_mult: 0
   3469    }
   3470    inner_product_param{
   3471 	   num_output: 2
   3472 	   weight_filler {
   3473 		 type: "xavier"
   3474 		 std: 0.01
   3475 	   }
   3476 	   bias_filler {
   3477 	      type: "xavier"
   3478 		  value: 0
   3479 	   }
   3480    }
   3481 }
   3482 layer {
   3483   name: "prob"
   3484   type: "Softmax"
   3485   bottom: "fc_nsfw"
   3486   top: "prob"
   3487 }
   3488