diff --git a/cls/resnext/deploy_vgg13-pytorch.prototxt b/cls/resnext/deploy_vgg13-pytorch.prototxt
deleted file mode 100644
index cf4a4b9..0000000
--- a/cls/resnext/deploy_vgg13-pytorch.prototxt
+++ /dev/null
@@ -1,348 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_2"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_2"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_2"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg13bn-pytorch.prototxt b/cls/resnext/deploy_vgg13bn-pytorch.prototxt
deleted file mode 100644
index 73f81c5..0000000
--- a/cls/resnext/deploy_vgg13bn-pytorch.prototxt
+++ /dev/null
@@ -1,518 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_2"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_2"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_2"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg16-3c4x.prototxt b/cls/resnext/deploy_vgg16-3c4x.prototxt
deleted file mode 100755
index 78b499a..0000000
--- a/cls/resnext/deploy_vgg16-3c4x.prototxt
+++ /dev/null
@@ -1,889 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224
-  dim: 224
-}
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-layer {
-  name: "conv1_2_V"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2_V"
-  convolution_param {
-    num_output: 22
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv1_2_H"
-  type: "Convolution"
-  bottom: "conv1_2_V"
-  top: "conv1_2_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 22
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv1_2_P"
-  type: "Convolution"
-  bottom: "conv1_2_H"
-  top: "conv1_2_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 59
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2_P"
-  top: "conv1_2_P"
-}
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2_P"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv2_1_V"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1_V"
-  convolution_param {
-    num_output: 37
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv2_1_H"
-  type: "Convolution"
-  bottom: "conv2_1_V"
-  top: "conv2_1_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 37
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_1_P"
-  type: "Convolution"
-  bottom: "conv2_1_H"
-  top: "conv2_1_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 118
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1_P"
-  top: "conv2_1_P"
-}
-layer {
-  name: "conv2_2_V"
-  type: "Convolution"
-  bottom: "conv2_1_P"
-  top: "conv2_2_V"
-  convolution_param {
-    num_output: 47
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv2_2_H"
-  type: "Convolution"
-  bottom: "conv2_2_V"
-  top: "conv2_2_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 47
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv2_2_P"
-  type: "Convolution"
-  bottom: "conv2_2_H"
-  top: "conv2_2_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 119
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2_P"
-  top: "conv2_2_P"
-}
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2_P"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv3_1_V"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1_V"
-  convolution_param {
-    num_output: 83
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv3_1_H"
-  type: "Convolution"
-  bottom: "conv3_1_V"
-  top: "conv3_1_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 83
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_1_P"
-  type: "Convolution"
-  bottom: "conv3_1_H"
-  top: "conv3_1_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 226
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1_P"
-  top: "conv3_1_P"
-}
-layer {
-  name: "conv3_2_V"
-  type: "Convolution"
-  bottom: "conv3_1_P"
-  top: "conv3_2_V"
-  convolution_param {
-    num_output: 89
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv3_2_H"
-  type: "Convolution"
-  bottom: "conv3_2_V"
-  top: "conv3_2_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 89
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_2_P"
-  type: "Convolution"
-  bottom: "conv3_2_H"
-  top: "conv3_2_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 243
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2_P"
-  top: "conv3_2_P"
-}
-layer {
-  name: "conv3_3_V"
-  type: "Convolution"
-  bottom: "conv3_2_P"
-  top: "conv3_3_V"
-  convolution_param {
-    num_output: 106
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv3_3_H"
-  type: "Convolution"
-  bottom: "conv3_3_V"
-  top: "conv3_3_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 106
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv3_3_P"
-  type: "Convolution"
-  bottom: "conv3_3_H"
-  top: "conv3_3_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 256
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3_P"
-  top: "conv3_3_P"
-}
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_3_P"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv4_1_V"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1_V"
-  convolution_param {
-    num_output: 175
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv4_1_H"
-  type: "Convolution"
-  bottom: "conv4_1_V"
-  top: "conv4_1_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 175
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_1_P"
-  type: "Convolution"
-  bottom: "conv4_1_H"
-  top: "conv4_1_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 482
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1_P"
-  top: "conv4_1_P"
-}
-layer {
-  name: "conv4_2_V"
-  type: "Convolution"
-  bottom: "conv4_1_P"
-  top: "conv4_2_V"
-  convolution_param {
-    num_output: 192
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv4_2_H"
-  type: "Convolution"
-  bottom: "conv4_2_V"
-  top: "conv4_2_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 192
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_2_P"
-  type: "Convolution"
-  bottom: "conv4_2_H"
-  top: "conv4_2_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 457
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2_P"
-  top: "conv4_2_P"
-}
-layer {
-  name: "conv4_3_V"
-  type: "Convolution"
-  bottom: "conv4_2_P"
-  top: "conv4_3_V"
-  convolution_param {
-    num_output: 227
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv4_3_H"
-  type: "Convolution"
-  bottom: "conv4_3_V"
-  top: "conv4_3_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 227
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "conv4_3_P"
-  type: "Convolution"
-  bottom: "conv4_3_H"
-  top: "conv4_3_P"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  param {
-    lr_mult: 1.0
-    decay_mult: 2.0
-  }
-  convolution_param {
-    num_output: 512
-    pad: 0
-    kernel_size: 1
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-    bias_filler {
-      type: "constant"
-      value: 0.0
-    }
-  }
-}
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3_P"
-  top: "conv4_3_P"
-}
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_3_P"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv5_1_V"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1_V"
-  convolution_param {
-    num_output: 398
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv5_1_H"
-  type: "Convolution"
-  bottom: "conv5_1_V"
-  top: "conv5_1_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1_H"
-  top: "conv5_1_H"
-}
-layer {
-  name: "conv5_2_V"
-  type: "Convolution"
-  bottom: "conv5_1_H"
-  top: "conv5_2_V"
-  convolution_param {
-    num_output: 390
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv5_2_H"
-  type: "Convolution"
-  bottom: "conv5_2_V"
-  top: "conv5_2_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2_H"
-  top: "conv5_2_H"
-}
-layer {
-  name: "conv5_3_V"
-  type: "Convolution"
-  bottom: "conv5_2_H"
-  top: "conv5_3_V"
-  convolution_param {
-    num_output: 379
-    pad: 1
-    pad: 0
-    kernel_size: 3
-    kernel_size: 1
-    stride: 1
-  }
-}
-layer {
-  name: "conv5_3_H"
-  type: "Convolution"
-  bottom: "conv5_3_V"
-  top: "conv5_3_H"
-  param {
-    lr_mult: 1.0
-    decay_mult: 1.0
-  }
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    pad: 0
-    pad: 1
-    kernel_size: 1
-    kernel_size: 3
-    stride: 1
-    weight_filler {
-      type: "msra"
-    }
-  }
-}
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3_H"
-  top: "conv5_3_H"
-}
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_3_H"
-  top: "pool5"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "fc6"
-  type: "InnerProduct"
-  bottom: "pool5"
-  top: "fc6"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-layer {
-  name: "drop6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc7"
-  type: "InnerProduct"
-  bottom: "fc6"
-  top: "fc7"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-layer {
-  name: "drop7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc8"
-  type: "InnerProduct"
-  bottom: "fc7"
-  top: "fc8"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "fc8"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg16-5x.prototxt b/cls/resnext/deploy_vgg16-5x.prototxt
deleted file mode 100644
index f496339..0000000
--- a/cls/resnext/deploy_vgg16-5x.prototxt
+++ /dev/null
@@ -1,347 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224
-  dim: 224
-}
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    num_output: 24
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    num_output: 22
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    num_output: 41
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    num_output: 51
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    num_output: 108
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    num_output: 89
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    num_output: 111
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_3"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    num_output: 184
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    num_output: 276
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    num_output: 228
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_3"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-  }
-}
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_3"
-  top: "pool5"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layer {
-  name: "fc6"
-  type: "InnerProduct"
-  bottom: "pool5"
-  top: "fc6"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-layer {
-  name: "drop6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc7"
-  type: "InnerProduct"
-  bottom: "fc6"
-  top: "fc7"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-layer {
-  name: "drop7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-layer {
-  name: "fc8"
-  type: "InnerProduct"
-  bottom: "fc7"
-  top: "fc8"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "fc8"
-  top: "prob"
-}
-
diff --git a/cls/resnext/deploy_vgg16-dsd.prototxt b/cls/resnext/deploy_vgg16-dsd.prototxt
deleted file mode 100755
index 41f494f..0000000
--- a/cls/resnext/deploy_vgg16-dsd.prototxt
+++ /dev/null
@@ -1,347 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224
-  dim: 224
-}
-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: "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: "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: "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: 1000
-  }
-}
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "fc8"
-  top: "prob"
-}
-
diff --git a/cls/resnext/deploy_vgg16-pytorch.prototxt b/cls/resnext/deploy_vgg16-pytorch.prototxt
deleted file mode 100644
index 336a3dc..0000000
--- a/cls/resnext/deploy_vgg16-pytorch.prototxt
+++ /dev/null
@@ -1,411 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_3"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_3"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
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-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_3"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg16-tf.prototxt b/cls/resnext/deploy_vgg16-tf.prototxt
deleted file mode 100755
index d648d96..0000000
--- a/cls/resnext/deploy_vgg16-tf.prototxt
+++ /dev/null
@@ -1,433 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_3"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_3"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_3"
-  top: "pool5"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "fc6"
-  type: "Convolution"
-  bottom: "pool5"
-  top: "fc6"
-  convolution_param {
-    bias_term: true
-    num_output: 4096
-    kernel_size: 7
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  name: "fc7"
-  type: "Convolution"
-  bottom: "fc6"
-  top: "fc7"
-  convolution_param {
-    bias_term: true
-    num_output: 4096
-    kernel_size: 1
-    stride: 1
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  name: "fc8"
-  type: "Convolution"
-  bottom: "fc7"
-  top: "fc8"
-  convolution_param {
-    bias_term: true
-    num_output: 1000
-    kernel_size: 1
-    stride: 1
-  }
-}
-
-layer {
-  name: "reshape"
-  type: "Reshape"
-  bottom: "fc8"
-  top: "reshape"
-  reshape_param {
-    shape {
-      dim: 0
-      dim: 0
-    }
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "reshape"
-  top: "prob"
-}
\ No newline at end of file
diff --git a/cls/resnext/deploy_vgg16bn-pytorch.prototxt b/cls/resnext/deploy_vgg16bn-pytorch.prototxt
deleted file mode 100644
index 73397b2..0000000
--- a/cls/resnext/deploy_vgg16bn-pytorch.prototxt
+++ /dev/null
@@ -1,632 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_3"
-  top: "conv3_3"
-  name: "conv3_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_3"
-  top: "conv3_3"
-  name: "conv3_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_3"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_3"
-  top: "conv4_3"
-  name: "conv4_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_3"
-  top: "conv4_3"
-  name: "conv4_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_3"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_3"
-  top: "conv5_3"
-  name: "conv5_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_3"
-  top: "conv5_3"
-  name: "conv5_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_3"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg19-pytorch.prototxt b/cls/resnext/deploy_vgg19-pytorch.prototxt
deleted file mode 100644
index f0286c3..0000000
--- a/cls/resnext/deploy_vgg19-pytorch.prototxt
+++ /dev/null
@@ -1,457 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-layer {
-  name: "conv3_4"
-  type: "Convolution"
-  bottom: "conv3_3"
-  top: "conv3_4"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu3_4"
-  type: "ReLU"
-  bottom: "conv3_4"
-  top: "conv3_4"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_4"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-
-layer {
-  name: "conv4_4"
-  type: "Convolution"
-  bottom: "conv4_3"
-  top: "conv4_4"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu4_4"
-  type: "ReLU"
-  bottom: "conv4_4"
-  top: "conv4_4"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_4"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-
-layer {
-  name: "conv5_4"
-  type: "Convolution"
-  bottom: "conv5_3"
-  top: "conv5_4"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  name: "relu5_4"
-  type: "ReLU"
-  bottom: "conv5_4"
-  top: "conv5_4"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_4"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}
diff --git a/cls/resnext/deploy_vgg19bn-pytorch.prototxt b/cls/resnext/deploy_vgg19bn-pytorch.prototxt
deleted file mode 100644
index 1edae84..0000000
--- a/cls/resnext/deploy_vgg19bn-pytorch.prototxt
+++ /dev/null
@@ -1,745 +0,0 @@
-input: "data"
-input_shape {
-  dim: 1
-  dim: 3
-  dim: 224 
-  dim: 224
-}
-
-layer {
-  name: "conv1_1"
-  type: "Convolution"
-  bottom: "data"
-  top: "conv1_1"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_1"
-  top: "conv1_1"
-  name: "conv1_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_1"
-  type: "ReLU"
-  bottom: "conv1_1"
-  top: "conv1_1"
-}
-
-layer {
-  name: "conv1_2"
-  type: "Convolution"
-  bottom: "conv1_1"
-  top: "conv1_2"
-  convolution_param {
-    bias_term: true
-    num_output: 64
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv1_2"
-  top: "conv1_2"
-  name: "conv1_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu1_2"
-  type: "ReLU"
-  bottom: "conv1_2"
-  top: "conv1_2"
-}
-
-layer {
-  name: "pool1"
-  type: "Pooling"
-  bottom: "conv1_2"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv2_1"
-  type: "Convolution"
-  bottom: "pool1"
-  top: "conv2_1"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_1"
-  top: "conv2_1"
-  name: "conv2_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_1"
-  type: "ReLU"
-  bottom: "conv2_1"
-  top: "conv2_1"
-}
-
-layer {
-  name: "conv2_2"
-  type: "Convolution"
-  bottom: "conv2_1"
-  top: "conv2_2"
-  convolution_param {
-    bias_term: true
-    num_output: 128
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv2_2"
-  top: "conv2_2"
-  name: "conv2_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu2_2"
-  type: "ReLU"
-  bottom: "conv2_2"
-  top: "conv2_2"
-}
-
-layer {
-  name: "pool2"
-  type: "Pooling"
-  bottom: "conv2_2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv3_1"
-  type: "Convolution"
-  bottom: "pool2"
-  top: "conv3_1"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_1"
-  top: "conv3_1"
-  name: "conv3_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_1"
-  type: "ReLU"
-  bottom: "conv3_1"
-  top: "conv3_1"
-}
-
-layer {
-  name: "conv3_2"
-  type: "Convolution"
-  bottom: "conv3_1"
-  top: "conv3_2"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_2"
-  top: "conv3_2"
-  name: "conv3_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_2"
-  type: "ReLU"
-  bottom: "conv3_2"
-  top: "conv3_2"
-}
-
-layer {
-  name: "conv3_3"
-  type: "Convolution"
-  bottom: "conv3_2"
-  top: "conv3_3"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_3"
-  top: "conv3_3"
-  name: "conv3_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_3"
-  top: "conv3_3"
-  name: "conv3_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_3"
-  type: "ReLU"
-  bottom: "conv3_3"
-  top: "conv3_3"
-}
-layer {
-  name: "conv3_4"
-  type: "Convolution"
-  bottom: "conv3_3"
-  top: "conv3_4"
-  convolution_param {
-    bias_term: true
-    num_output: 256
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv3_4"
-  top: "conv3_4"
-  name: "conv3_4_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv3_4"
-  top: "conv3_4"
-  name: "conv3_4_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu3_4"
-  type: "ReLU"
-  bottom: "conv3_4"
-  top: "conv3_4"
-}
-
-layer {
-  name: "pool3"
-  type: "Pooling"
-  bottom: "conv3_4"
-  top: "pool3"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv4_1"
-  type: "Convolution"
-  bottom: "pool3"
-  top: "conv4_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_1"
-  top: "conv4_1"
-  name: "conv4_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_1"
-  type: "ReLU"
-  bottom: "conv4_1"
-  top: "conv4_1"
-}
-
-layer {
-  name: "conv4_2"
-  type: "Convolution"
-  bottom: "conv4_1"
-  top: "conv4_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_2"
-  top: "conv4_2"
-  name: "conv4_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_2"
-  type: "ReLU"
-  bottom: "conv4_2"
-  top: "conv4_2"
-}
-
-layer {
-  name: "conv4_3"
-  type: "Convolution"
-  bottom: "conv4_2"
-  top: "conv4_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_3"
-  top: "conv4_3"
-  name: "conv4_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_3"
-  top: "conv4_3"
-  name: "conv4_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_3"
-  type: "ReLU"
-  bottom: "conv4_3"
-  top: "conv4_3"
-}
-
-layer {
-  name: "conv4_4"
-  type: "Convolution"
-  bottom: "conv4_3"
-  top: "conv4_4"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv4_4"
-  top: "conv4_4"
-  name: "conv4_4_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv4_4"
-  top: "conv4_4"
-  name: "conv4_4_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu4_4"
-  type: "ReLU"
-  bottom: "conv4_4"
-  top: "conv4_4"
-}
-
-layer {
-  name: "pool4"
-  type: "Pooling"
-  bottom: "conv4_4"
-  top: "pool4"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-
-layer {
-  name: "conv5_1"
-  type: "Convolution"
-  bottom: "pool4"
-  top: "conv5_1"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_1"
-  top: "conv5_1"
-  name: "conv5_1_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_1"
-  type: "ReLU"
-  bottom: "conv5_1"
-  top: "conv5_1"
-}
-
-layer {
-  name: "conv5_2"
-  type: "Convolution"
-  bottom: "conv5_1"
-  top: "conv5_2"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_2"
-  top: "conv5_2"
-  name: "conv5_2_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_2"
-  type: "ReLU"
-  bottom: "conv5_2"
-  top: "conv5_2"
-}
-
-layer {
-  name: "conv5_3"
-  type: "Convolution"
-  bottom: "conv5_2"
-  top: "conv5_3"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_3"
-  top: "conv5_3"
-  name: "conv5_3_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_3"
-  top: "conv5_3"
-  name: "conv5_3_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_3"
-  type: "ReLU"
-  bottom: "conv5_3"
-  top: "conv5_3"
-}
-
-layer {
-  name: "conv5_4"
-  type: "Convolution"
-  bottom: "conv5_3"
-  top: "conv5_4"
-  convolution_param {
-    bias_term: true
-    num_output: 512
-    pad: 1
-    kernel_size: 3
-    stride: 1
-  }
-}
-layer {
-  bottom: "conv5_4"
-  top: "conv5_4"
-  name: "conv5_4_bn"
-  type: "BatchNorm"
-  batch_norm_param {
-    use_global_stats: true
-  }
-}
-layer {
-  bottom: "conv5_4"
-  top: "conv5_4"
-  name: "conv5_4_scale"
-  type: "Scale"
-  scale_param {
-    bias_term: true
-  }
-}
-layer {
-  name: "relu5_4"
-  type: "ReLU"
-  bottom: "conv5_4"
-  top: "conv5_4"
-}
-
-layer {
-  name: "pool5"
-  type: "Pooling"
-  bottom: "conv5_4"
-  top: "pool5"
-  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 {
-  name: "relu6"
-  type: "ReLU"
-  bottom: "fc6"
-  top: "fc6"
-}
-
-layer {
-  name: "dropout6"
-  type: "Dropout"
-  bottom: "fc6"
-  top: "fc6"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc6"
-  top: "fc7"
-  name: "fc7"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 4096
-  }
-}
-
-layer {
-  name: "relu7"
-  type: "ReLU"
-  bottom: "fc7"
-  top: "fc7"
-}
-
-layer {
-  name: "dropout7"
-  type: "Dropout"
-  bottom: "fc7"
-  top: "fc7"
-  dropout_param {
-    dropout_ratio: 0.5
-  }
-}
-
-layer {
-  bottom: "fc7"
-  top: "classifier"
-  name: "classifier"
-  type: "InnerProduct"
-  inner_product_param {
-    num_output: 1000
-  }
-}
-
-layer {
-  name: "prob"
-  type: "Softmax"
-  bottom: "classifier"
-  top: "prob"
-}