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  1. name: "CaffeNet"
  2. layer {
  3.   name: "data"
  4.   type: "Input"
  5.   top: "data"
  6.   input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } }
  7. }
  8. layer {
  9.   name: "conv1"
  10.   type: "Convolution"
  11.   bottom: "data"
  12.   top: "conv1"
  13.   convolution_param {
  14.     num_output: 96
  15.     kernel_size: 11
  16.     stride: 4
  17.   }
  18. }
  19. layer {
  20.   name: "relu1"
  21.   type: "ReLU"
  22.   bottom: "conv1"
  23.   top: "conv1"
  24. }
  25. layer {
  26.   name: "pool1"
  27.   type: "Pooling"
  28.   bottom: "conv1"
  29.   top: "pool1"
  30.   pooling_param {
  31.     pool: MAX
  32.     kernel_size: 3
  33.     stride: 2
  34.   }
  35. }
  36. layer {
  37.   name: "norm1"
  38.   type: "LRN"
  39.   bottom: "pool1"
  40.   top: "norm1"
  41.   lrn_param {
  42.     local_size: 5
  43.     alpha: 0.0001
  44.     beta: 0.75
  45.   }
  46. }
  47. layer {
  48.   name: "conv2"
  49.   type: "Convolution"
  50.   bottom: "norm1"
  51.   top: "conv2"
  52.   convolution_param {
  53.     num_output: 256
  54.     pad: 2
  55.     kernel_size: 5
  56.     group: 2
  57.   }
  58. }
  59. layer {
  60.   name: "relu2"
  61.   type: "ReLU"
  62.   bottom: "conv2"
  63.   top: "conv2"
  64. }
  65. layer {
  66.   name: "pool2"
  67.   type: "Pooling"
  68.   bottom: "conv2"
  69.   top: "pool2"
  70.   pooling_param {
  71.     pool: MAX
  72.     kernel_size: 3
  73.     stride: 2
  74.   }
  75. }
  76. layer {
  77.   name: "norm2"
  78.   type: "LRN"
  79.   bottom: "pool2"
  80.   top: "norm2"
  81.   lrn_param {
  82.     local_size: 5
  83.     alpha: 0.0001
  84.     beta: 0.75
  85.   }
  86. }
  87. layer {
  88.   name: "conv3"
  89.   type: "Convolution"
  90.   bottom: "norm2"
  91.   top: "conv3"
  92.   convolution_param {
  93.     num_output: 384
  94.     pad: 1
  95.     kernel_size: 3
  96.   }
  97. }
  98. layer {
  99.   name: "relu3"
  100.   type: "ReLU"
  101.   bottom: "conv3"
  102.   top: "conv3"
  103. }
  104. layer {
  105.   name: "conv5-new"
  106.   type: "Convolution"
  107.   bottom: "conv3"
  108.   top: "conv5-new"
  109.   convolution_param {
  110.     num_output: 256
  111.     pad: 1
  112.     kernel_size: 3
  113.     group: 2
  114.   }
  115. }
  116. layer {
  117.   name: "relu5-new"
  118.   type: "ReLU"
  119.   bottom: "conv5-new"
  120.   top: "conv5-new"
  121. }
  122. layer {
  123.   name: "pool5-new"
  124.   type: "Pooling"
  125.   bottom: "conv5-new"
  126.   top: "pool5-new"
  127.   pooling_param {
  128.     pool: MAX
  129.     kernel_size: 3
  130.     stride: 2
  131.   }
  132. }
  133. layer {
  134.   name: "fc6"
  135.   type: "InnerProduct"
  136.   bottom: "pool5-new"
  137.   top: "fc6"
  138.   inner_product_param {
  139.     num_output: 4096
  140.   }
  141. }
  142. layer {
  143.   name: "relu6"
  144.   type: "ReLU"
  145.   bottom: "fc6"
  146.   top: "fc6"
  147. }
  148. layer {
  149.   name: "drop6"
  150.   type: "Dropout"
  151.   bottom: "fc6"
  152.   top: "fc6"
  153.   dropout_param {
  154.     dropout_ratio: 0.5
  155.   }
  156. }
  157. layer {
  158.   name: "fc7"
  159.   type: "InnerProduct"
  160.   bottom: "fc6"
  161.   top: "fc7"
  162.   inner_product_param {
  163.     num_output: 4096
  164.   }
  165. }
  166. layer {
  167.   name: "relu7"
  168.   type: "ReLU"
  169.   bottom: "fc7"
  170.   top: "fc7"
  171. }
  172. layer {
  173.   name: "drop7"
  174.   type: "Dropout"
  175.   bottom: "fc7"
  176.   top: "fc7"
  177.   dropout_param {
  178.     dropout_ratio: 0.5
  179.   }
  180. }
  181. layer {
  182.   name: "fc8"
  183.   type: "InnerProduct"
  184.   bottom: "fc7"
  185.   top: "fc8"
  186.   inner_product_param {
  187.     num_output: 1000
  188.   }
  189. }
  190. layer {
  191.   name: "prob"
  192.   type: "Softmax"
  193.   bottom: "fc8"
  194.   top: "prob"
  195. }
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https://ideone.com/1PhzSs
language:
Text (text 6.10)
created:
7 years ago
visibility:
public

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