name: "VGG_ILSVRC_19_layer" layer {
       name: "data"   type: "ImageData"   top: "data"   top: "label"   include {
         phase: TRAIN   }     image_data_param {
         batch_size: 12     source: "../../fine_tuning_data/HAT_fineTuning_data/train_data_fineTuning.txt"     root_folder: "../../fine_tuning_data/HAT_fineTuning_data/train_data/"   } } layer {
       name: "data"   type: "ImageData"   top: "data"   top: "label"   include {
         phase: TEST   }   transform_param {
         mirror: false   }   image_data_param {
         batch_size: 10     source: "../../fine_tuning_data/HAT_fineTuning_data/test_data_fineTuning.txt"     root_folder: "../../fine_tuning_data/HAT_fineTuning_data/test_data/"   } } layer {
       bottom:"data"   top:"conv1_1"   name:"conv1_1"   type:"Convolution"   convolution_param {
         num_output:64     pad:1     kernel_size:3   } } layer {
       bottom:"conv1_1"   top:"conv1_1"   name:"relu1_1"   type:"ReLU" } layer {
       bottom:"conv1_1"   top:"conv1_2"   name:"conv1_2"   type:"Convolution"   convolution_param {
         num_output:64     pad:1     kernel_size:3   } } layer {
       bottom:"conv1_2"   top:"conv1_2"   name:"relu1_2"   type:"ReLU" } layer {
       bottom:"conv1_2"   top:"pool1"   name:"pool1"   type:"Pooling"   pooling_param {
         pool:MAX     kernel_size:2     stride:2   } } layer {
       bottom:"pool1"   top:"conv2_1"   name:"conv2_1"   type:"Convolution"   convolution_param {
         num_output:128     pad:1     kernel_size:3   } } layer {
       bottom:"conv2_1"   top:"conv2_1"   name:"relu2_1"   type:"ReLU" } layer {
       bottom:"conv2_1"   top:"conv2_2"   name:"conv2_2"   type:"Convolution"   convolution_param {
         num_output:128     pad:1     kernel_size:3   } } layer {
       bottom:"conv2_2"   top:"conv2_2"   name:"relu2_2"   type:"ReLU" } layer {
       bottom:"conv2_2"   top:"pool2"   name:"pool2"   type:"Pooling"   pooling_param {
         pool:MAX     kernel_size:2     stride:2   } } layer {
       bottom:"pool2"   top:"conv3_1"   name: "conv3_1"   type:"Convolution"   convolution_param {
         num_output:256     pad:1     kernel_size:3   } } layer {
       bottom:"conv3_1"   top:"conv3_1"   name:"relu3_1"   type:"ReLU" } layer {
       bottom:"conv3_1"   top:"conv3_2"   name:"conv3_2"   type:"Convolution"   convolution_param {
         num_output:256     pad:1     kernel_size:3   } } layer {
       bottom:"conv3_2"   top:"conv3_2"   name:"relu3_2"   type:"ReLU" } layer {
       bottom:"conv3_2"   top:"conv3_3"   name:"conv3_3"   type:"Convolution"   convolution_param {
         num_output:256     pad:1     kernel_size:3   } } layer {
       bottom:"conv3_3"   top:"conv3_3"   name:"relu3_3"   type:"ReLU" } layer {
       bottom:"conv3_3"   top:"conv3_4"   name:"conv3_4"   type:"Convolution"   convolution_param {
         num_output:256     pad:1     kernel_size:3   } } layer {
       bottom:"conv3_4"   top:"conv3_4"   name:"relu3_4"   type:"ReLU" } layer {
       bottom:"conv3_4"   top:"pool3"   name:"pool3"   type:"Pooling"   pooling_param {
         pool:MAX     kernel_size: 2     stride: 2   } } layer {
       bottom:"pool3"   top:"conv4_1"   name:"conv4_1"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv4_1"   top:"conv4_1"   name:"relu4_1"   type:"ReLU" } layer {
       bottom:"conv4_1"   top:"conv4_2"   name:"conv4_2"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv4_2"   top:"conv4_2"   name:"relu4_2"   type:"ReLU" } layer {
       bottom:"conv4_2"   top:"conv4_3"   name:"conv4_3"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv4_3"   top:"conv4_3"   name:"relu4_3"   type:"ReLU" } layer {
       bottom:"conv4_3"   top:"conv4_4"   name:"conv4_4"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv4_4"   top:"conv4_4"   name:"relu4_4"   type:"ReLU" } layer {
       bottom:"conv4_4"   top:"pool4"   name:"pool4"   type:"Pooling"   pooling_param {
         pool:MAX     kernel_size: 2     stride: 2   } } layer {
       bottom:"pool4"   top:"conv5_1"   name:"conv5_1"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv5_1"   top:"conv5_1"   name:"relu5_1"   type:"ReLU" } layer {
       bottom:"conv5_1"   top:"conv5_2"   name:"conv5_2"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv5_2"   top:"conv5_2"   name:"relu5_2"   type:"ReLU" } layer {
       bottom:"conv5_2"   top:"conv5_3"   name:"conv5_3"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv5_3"   top:"conv5_3"   name:"relu5_3"   type:"ReLU" } layer {
       bottom:"conv5_3"   top:"conv5_4"   name:"conv5_4"   type:"Convolution"   convolution_param {
         num_output: 512     pad: 1     kernel_size: 3   } } layer {
       bottom:"conv5_4"   top:"conv5_4"   name:"relu5_4"   type:"ReLU" } layer {
       bottom:"conv5_4"   top:"pool5"   name:"pool5"   type:"Pooling"   pooling_param {
         pool:MAX     kernel_size: 2     stride: 2   } } layer {
       bottom:"pool5"   top:"fc6_"   name:"fc6_"   type:"InnerProduct"   inner_product_param {
         num_output: 4096   } } layer {
       bottom:"fc6_"   top:"fc6_"   name:"relu6"   type:"ReLU" } layer {
       bottom:"fc6_"   top:"fc6_"   name:"drop6"   type:"Dropout"   dropout_param {
         dropout_ratio: 0.5   } } layer {
       bottom:"fc6_"   top:"fc7"   name:"fc7"   type:"InnerProduct"   inner_product_param {
         num_output: 4096   } } layer {
       bottom:"fc7"   top:"fc7"   name:"relu7"   type:"ReLU" } layer {
       bottom:"fc7"   top:"fc7"   name:"drop7"   type:"Dropout"   dropout_param {
         dropout_ratio: 0.5   } } layer {
       bottom:"fc7"   top:"fc8_"   name:"fc8_"   type:"InnerProduct"   inner_product_param {
         num_output: 27   } } layer {
       name: "sigmoid"   type: "Sigmoid"   bottom: "fc8_"   top: "fc8_" }  layer {
        name: "accuracy"    type: "Accuracy"    bottom: "fc8_"    bottom: "label"    top: "accuracy"    include {
          phase: TEST    }  } layer {
       name: "loss"   type: "EuclideanLoss"   bottom: "fc8_"   bottom: "label"   top: "loss" }