--- a
+++ b/deploy_3d_denseseg.prototxt
@@ -0,0 +1,3493 @@
+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 2
+      dim: 64
+      dim: 64
+      dim: 64
+    }
+  }
+}
+layer {
+  name: "conv1a"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv1a"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: -0.10000000149
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "bnorm1a"
+  type: "BatchNorm"
+  bottom: "conv1a"
+  top: "bnorm1a"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "scale1a"
+  type: "Scale"
+  bottom: "bnorm1a"
+  top: "bnorm1a"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "relu1a"
+  type: "ReLU"
+  bottom: "bnorm1a"
+  top: "bnorm1a"
+}
+layer {
+  name: "conv1b"
+  type: "Convolution"
+  bottom: "bnorm1a"
+  top: "conv1b"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "bnorm1b"
+  type: "BatchNorm"
+  bottom: "conv1b"
+  top: "bnorm1b"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "scale1b"
+  type: "Scale"
+  bottom: "bnorm1b"
+  top: "bnorm1b"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "relu1b"
+  type: "ReLU"
+  bottom: "bnorm1b"
+  top: "bnorm1b"
+}
+layer {
+  name: "conv1c"
+  type: "Convolution"
+  bottom: "bnorm1b"
+  top: "conv1c"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "bnorm1c"
+  type: "BatchNorm"
+  bottom: "conv1c"
+  top: "bnorm1c"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "scale1c"
+  type: "Scale"
+  bottom: "bnorm1c"
+  top: "bnorm1c"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "relu1c"
+  type: "ReLU"
+  bottom: "bnorm1c"
+  top: "bnorm1c"
+}
+layer {
+  name: "Conv_down_1"
+  type: "Convolution"
+  bottom: "bnorm1c"
+  top: "Conv_down_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 2
+    kernel_size: 2
+    kernel_size: 2
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm1"
+  type: "BatchNorm"
+  bottom: "Conv_down_1"
+  top: "BatchNorm1"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale1"
+  type: "Scale"
+  bottom: "BatchNorm1"
+  top: "BatchNorm1"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU1"
+  type: "ReLU"
+  bottom: "BatchNorm1"
+  top: "BatchNorm1"
+}
+layer {
+  name: "Convolution1"
+  type: "Convolution"
+  bottom: "BatchNorm1"
+  top: "Convolution1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm2"
+  type: "BatchNorm"
+  bottom: "Convolution1"
+  top: "BatchNorm2"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale2"
+  type: "Scale"
+  bottom: "BatchNorm2"
+  top: "BatchNorm2"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU2"
+  type: "ReLU"
+  bottom: "BatchNorm2"
+  top: "BatchNorm2"
+}
+layer {
+  name: "Convolution2"
+  type: "Convolution"
+  bottom: "BatchNorm2"
+  top: "Convolution2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout1"
+  type: "Dropout"
+  bottom: "Convolution2"
+  top: "Dropout1"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_1"
+  type: "Concat"
+  bottom: "Conv_down_1"
+  bottom: "Dropout1"
+  top: "Concat_1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm3"
+  type: "BatchNorm"
+  bottom: "Concat_1"
+  top: "BatchNorm3"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale3"
+  type: "Scale"
+  bottom: "BatchNorm3"
+  top: "BatchNorm3"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU3"
+  type: "ReLU"
+  bottom: "BatchNorm3"
+  top: "BatchNorm3"
+}
+layer {
+  name: "Convolution3"
+  type: "Convolution"
+  bottom: "BatchNorm3"
+  top: "Convolution3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm4"
+  type: "BatchNorm"
+  bottom: "Convolution3"
+  top: "BatchNorm4"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale4"
+  type: "Scale"
+  bottom: "BatchNorm4"
+  top: "BatchNorm4"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU4"
+  type: "ReLU"
+  bottom: "BatchNorm4"
+  top: "BatchNorm4"
+}
+layer {
+  name: "Convolution4"
+  type: "Convolution"
+  bottom: "BatchNorm4"
+  top: "Convolution4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout2"
+  type: "Dropout"
+  bottom: "Convolution4"
+  top: "Dropout2"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_2"
+  type: "Concat"
+  bottom: "Concat_1"
+  bottom: "Dropout2"
+  top: "Concat_2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm5"
+  type: "BatchNorm"
+  bottom: "Concat_2"
+  top: "BatchNorm5"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale5"
+  type: "Scale"
+  bottom: "BatchNorm5"
+  top: "BatchNorm5"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU5"
+  type: "ReLU"
+  bottom: "BatchNorm5"
+  top: "BatchNorm5"
+}
+layer {
+  name: "Convolution5"
+  type: "Convolution"
+  bottom: "BatchNorm5"
+  top: "Convolution5"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm6"
+  type: "BatchNorm"
+  bottom: "Convolution5"
+  top: "BatchNorm6"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale6"
+  type: "Scale"
+  bottom: "BatchNorm6"
+  top: "BatchNorm6"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU6"
+  type: "ReLU"
+  bottom: "BatchNorm6"
+  top: "BatchNorm6"
+}
+layer {
+  name: "Convolution6"
+  type: "Convolution"
+  bottom: "BatchNorm6"
+  top: "Convolution6"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout3"
+  type: "Dropout"
+  bottom: "Convolution6"
+  top: "Dropout3"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_3"
+  type: "Concat"
+  bottom: "Concat_2"
+  bottom: "Dropout3"
+  top: "Concat_3"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm7"
+  type: "BatchNorm"
+  bottom: "Concat_3"
+  top: "BatchNorm7"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale7"
+  type: "Scale"
+  bottom: "BatchNorm7"
+  top: "BatchNorm7"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU7"
+  type: "ReLU"
+  bottom: "BatchNorm7"
+  top: "BatchNorm7"
+}
+layer {
+  name: "Convolution7"
+  type: "Convolution"
+  bottom: "BatchNorm7"
+  top: "Convolution7"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm8"
+  type: "BatchNorm"
+  bottom: "Convolution7"
+  top: "BatchNorm8"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale8"
+  type: "Scale"
+  bottom: "BatchNorm8"
+  top: "BatchNorm8"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU8"
+  type: "ReLU"
+  bottom: "BatchNorm8"
+  top: "BatchNorm8"
+}
+layer {
+  name: "Convolution8"
+  type: "Convolution"
+  bottom: "BatchNorm8"
+  top: "Convolution8"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout4"
+  type: "Dropout"
+  bottom: "Convolution8"
+  top: "Dropout4"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_4"
+  type: "Concat"
+  bottom: "Concat_3"
+  bottom: "Dropout4"
+  top: "Concat_4"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Deconvolution_5"
+  type: "Deconvolution"
+  bottom: "Concat_4"
+  top: "Deconvolution_5"
+  param {
+    lr_mult: 0.10000000149
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 4
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 4
+    kernel_size: 4
+    kernel_size: 4
+    group: 4
+    stride: 2
+    stride: 2
+    stride: 2
+    weight_filler {
+      type: "bilinear_3D"
+    }
+  }
+}
+layer {
+  name: "BatchNorm9"
+  type: "BatchNorm"
+  bottom: "Concat_4"
+  top: "BatchNorm9"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale9"
+  type: "Scale"
+  bottom: "BatchNorm9"
+  top: "BatchNorm9"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU9"
+  type: "ReLU"
+  bottom: "BatchNorm9"
+  top: "BatchNorm9"
+}
+layer {
+  name: "Convolution9"
+  type: "Convolution"
+  bottom: "BatchNorm9"
+  top: "Convolution9"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 48
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm10"
+  type: "BatchNorm"
+  bottom: "Convolution9"
+  top: "BatchNorm10"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale10"
+  type: "Scale"
+  bottom: "BatchNorm10"
+  top: "BatchNorm10"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU10"
+  type: "ReLU"
+  bottom: "BatchNorm10"
+  top: "BatchNorm10"
+}
+layer {
+  name: "Conv_down_5"
+  type: "Convolution"
+  bottom: "BatchNorm10"
+  top: "Conv_down_5"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 48
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 2
+    kernel_size: 2
+    kernel_size: 2
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm11"
+  type: "BatchNorm"
+  bottom: "Conv_down_5"
+  top: "BatchNorm11"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale11"
+  type: "Scale"
+  bottom: "BatchNorm11"
+  top: "BatchNorm11"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU11"
+  type: "ReLU"
+  bottom: "BatchNorm11"
+  top: "BatchNorm11"
+}
+layer {
+  name: "Convolution10"
+  type: "Convolution"
+  bottom: "BatchNorm11"
+  top: "Convolution10"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm12"
+  type: "BatchNorm"
+  bottom: "Convolution10"
+  top: "BatchNorm12"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale12"
+  type: "Scale"
+  bottom: "BatchNorm12"
+  top: "BatchNorm12"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU12"
+  type: "ReLU"
+  bottom: "BatchNorm12"
+  top: "BatchNorm12"
+}
+layer {
+  name: "Convolution11"
+  type: "Convolution"
+  bottom: "BatchNorm12"
+  top: "Convolution11"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout5"
+  type: "Dropout"
+  bottom: "Convolution11"
+  top: "Dropout5"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_6"
+  type: "Concat"
+  bottom: "Conv_down_5"
+  bottom: "Dropout5"
+  top: "Concat_6"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm13"
+  type: "BatchNorm"
+  bottom: "Concat_6"
+  top: "BatchNorm13"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale13"
+  type: "Scale"
+  bottom: "BatchNorm13"
+  top: "BatchNorm13"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU13"
+  type: "ReLU"
+  bottom: "BatchNorm13"
+  top: "BatchNorm13"
+}
+layer {
+  name: "Convolution12"
+  type: "Convolution"
+  bottom: "BatchNorm13"
+  top: "Convolution12"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm14"
+  type: "BatchNorm"
+  bottom: "Convolution12"
+  top: "BatchNorm14"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale14"
+  type: "Scale"
+  bottom: "BatchNorm14"
+  top: "BatchNorm14"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU14"
+  type: "ReLU"
+  bottom: "BatchNorm14"
+  top: "BatchNorm14"
+}
+layer {
+  name: "Convolution13"
+  type: "Convolution"
+  bottom: "BatchNorm14"
+  top: "Convolution13"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout6"
+  type: "Dropout"
+  bottom: "Convolution13"
+  top: "Dropout6"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_7"
+  type: "Concat"
+  bottom: "Concat_6"
+  bottom: "Dropout6"
+  top: "Concat_7"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm15"
+  type: "BatchNorm"
+  bottom: "Concat_7"
+  top: "BatchNorm15"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale15"
+  type: "Scale"
+  bottom: "BatchNorm15"
+  top: "BatchNorm15"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU15"
+  type: "ReLU"
+  bottom: "BatchNorm15"
+  top: "BatchNorm15"
+}
+layer {
+  name: "Convolution14"
+  type: "Convolution"
+  bottom: "BatchNorm15"
+  top: "Convolution14"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm16"
+  type: "BatchNorm"
+  bottom: "Convolution14"
+  top: "BatchNorm16"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale16"
+  type: "Scale"
+  bottom: "BatchNorm16"
+  top: "BatchNorm16"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU16"
+  type: "ReLU"
+  bottom: "BatchNorm16"
+  top: "BatchNorm16"
+}
+layer {
+  name: "Convolution15"
+  type: "Convolution"
+  bottom: "BatchNorm16"
+  top: "Convolution15"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout7"
+  type: "Dropout"
+  bottom: "Convolution15"
+  top: "Dropout7"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_8"
+  type: "Concat"
+  bottom: "Concat_7"
+  bottom: "Dropout7"
+  top: "Concat_8"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm17"
+  type: "BatchNorm"
+  bottom: "Concat_8"
+  top: "BatchNorm17"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale17"
+  type: "Scale"
+  bottom: "BatchNorm17"
+  top: "BatchNorm17"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU17"
+  type: "ReLU"
+  bottom: "BatchNorm17"
+  top: "BatchNorm17"
+}
+layer {
+  name: "Convolution16"
+  type: "Convolution"
+  bottom: "BatchNorm17"
+  top: "Convolution16"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm18"
+  type: "BatchNorm"
+  bottom: "Convolution16"
+  top: "BatchNorm18"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale18"
+  type: "Scale"
+  bottom: "BatchNorm18"
+  top: "BatchNorm18"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU18"
+  type: "ReLU"
+  bottom: "BatchNorm18"
+  top: "BatchNorm18"
+}
+layer {
+  name: "Convolution17"
+  type: "Convolution"
+  bottom: "BatchNorm18"
+  top: "Convolution17"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout8"
+  type: "Dropout"
+  bottom: "Convolution17"
+  top: "Dropout8"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_9"
+  type: "Concat"
+  bottom: "Concat_8"
+  bottom: "Dropout8"
+  top: "Concat_9"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Deconvolution_10"
+  type: "Deconvolution"
+  bottom: "Concat_9"
+  top: "Deconvolution_10"
+  param {
+    lr_mult: 0.10000000149
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 4
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 6
+    kernel_size: 6
+    kernel_size: 6
+    group: 4
+    stride: 4
+    stride: 4
+    stride: 4
+    weight_filler {
+      type: "bilinear_3D"
+    }
+  }
+}
+layer {
+  name: "BatchNorm19"
+  type: "BatchNorm"
+  bottom: "Concat_9"
+  top: "BatchNorm19"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale19"
+  type: "Scale"
+  bottom: "BatchNorm19"
+  top: "BatchNorm19"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU19"
+  type: "ReLU"
+  bottom: "BatchNorm19"
+  top: "BatchNorm19"
+}
+layer {
+  name: "Convolution18"
+  type: "Convolution"
+  bottom: "BatchNorm19"
+  top: "Convolution18"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 56
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm20"
+  type: "BatchNorm"
+  bottom: "Convolution18"
+  top: "BatchNorm20"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale20"
+  type: "Scale"
+  bottom: "BatchNorm20"
+  top: "BatchNorm20"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU20"
+  type: "ReLU"
+  bottom: "BatchNorm20"
+  top: "BatchNorm20"
+}
+layer {
+  name: "Conv_down_10"
+  type: "Convolution"
+  bottom: "BatchNorm20"
+  top: "Conv_down_10"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 56
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 2
+    kernel_size: 2
+    kernel_size: 2
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm21"
+  type: "BatchNorm"
+  bottom: "Conv_down_10"
+  top: "BatchNorm21"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale21"
+  type: "Scale"
+  bottom: "BatchNorm21"
+  top: "BatchNorm21"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU21"
+  type: "ReLU"
+  bottom: "BatchNorm21"
+  top: "BatchNorm21"
+}
+layer {
+  name: "Convolution19"
+  type: "Convolution"
+  bottom: "BatchNorm21"
+  top: "Convolution19"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm22"
+  type: "BatchNorm"
+  bottom: "Convolution19"
+  top: "BatchNorm22"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale22"
+  type: "Scale"
+  bottom: "BatchNorm22"
+  top: "BatchNorm22"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU22"
+  type: "ReLU"
+  bottom: "BatchNorm22"
+  top: "BatchNorm22"
+}
+layer {
+  name: "Convolution20"
+  type: "Convolution"
+  bottom: "BatchNorm22"
+  top: "Convolution20"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout9"
+  type: "Dropout"
+  bottom: "Convolution20"
+  top: "Dropout9"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_11"
+  type: "Concat"
+  bottom: "Conv_down_10"
+  bottom: "Dropout9"
+  top: "Concat_11"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm23"
+  type: "BatchNorm"
+  bottom: "Concat_11"
+  top: "BatchNorm23"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale23"
+  type: "Scale"
+  bottom: "BatchNorm23"
+  top: "BatchNorm23"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU23"
+  type: "ReLU"
+  bottom: "BatchNorm23"
+  top: "BatchNorm23"
+}
+layer {
+  name: "Convolution21"
+  type: "Convolution"
+  bottom: "BatchNorm23"
+  top: "Convolution21"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm24"
+  type: "BatchNorm"
+  bottom: "Convolution21"
+  top: "BatchNorm24"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale24"
+  type: "Scale"
+  bottom: "BatchNorm24"
+  top: "BatchNorm24"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU24"
+  type: "ReLU"
+  bottom: "BatchNorm24"
+  top: "BatchNorm24"
+}
+layer {
+  name: "Convolution22"
+  type: "Convolution"
+  bottom: "BatchNorm24"
+  top: "Convolution22"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout10"
+  type: "Dropout"
+  bottom: "Convolution22"
+  top: "Dropout10"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_12"
+  type: "Concat"
+  bottom: "Concat_11"
+  bottom: "Dropout10"
+  top: "Concat_12"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm25"
+  type: "BatchNorm"
+  bottom: "Concat_12"
+  top: "BatchNorm25"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale25"
+  type: "Scale"
+  bottom: "BatchNorm25"
+  top: "BatchNorm25"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU25"
+  type: "ReLU"
+  bottom: "BatchNorm25"
+  top: "BatchNorm25"
+}
+layer {
+  name: "Convolution23"
+  type: "Convolution"
+  bottom: "BatchNorm25"
+  top: "Convolution23"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm26"
+  type: "BatchNorm"
+  bottom: "Convolution23"
+  top: "BatchNorm26"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale26"
+  type: "Scale"
+  bottom: "BatchNorm26"
+  top: "BatchNorm26"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU26"
+  type: "ReLU"
+  bottom: "BatchNorm26"
+  top: "BatchNorm26"
+}
+layer {
+  name: "Convolution24"
+  type: "Convolution"
+  bottom: "BatchNorm26"
+  top: "Convolution24"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout11"
+  type: "Dropout"
+  bottom: "Convolution24"
+  top: "Dropout11"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_13"
+  type: "Concat"
+  bottom: "Concat_12"
+  bottom: "Dropout11"
+  top: "Concat_13"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm27"
+  type: "BatchNorm"
+  bottom: "Concat_13"
+  top: "BatchNorm27"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale27"
+  type: "Scale"
+  bottom: "BatchNorm27"
+  top: "BatchNorm27"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU27"
+  type: "ReLU"
+  bottom: "BatchNorm27"
+  top: "BatchNorm27"
+}
+layer {
+  name: "Convolution25"
+  type: "Convolution"
+  bottom: "BatchNorm27"
+  top: "Convolution25"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm28"
+  type: "BatchNorm"
+  bottom: "Convolution25"
+  top: "BatchNorm28"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale28"
+  type: "Scale"
+  bottom: "BatchNorm28"
+  top: "BatchNorm28"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU28"
+  type: "ReLU"
+  bottom: "BatchNorm28"
+  top: "BatchNorm28"
+}
+layer {
+  name: "Convolution26"
+  type: "Convolution"
+  bottom: "BatchNorm28"
+  top: "Convolution26"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout12"
+  type: "Dropout"
+  bottom: "Convolution26"
+  top: "Dropout12"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_14"
+  type: "Concat"
+  bottom: "Concat_13"
+  bottom: "Dropout12"
+  top: "Concat_14"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Deconvolution_15"
+  type: "Deconvolution"
+  bottom: "Concat_14"
+  top: "Deconvolution_15"
+  param {
+    lr_mult: 0.10000000149
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 4
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 10
+    kernel_size: 10
+    kernel_size: 10
+    group: 4
+    stride: 8
+    stride: 8
+    stride: 8
+    weight_filler {
+      type: "bilinear_3D"
+    }
+  }
+}
+layer {
+  name: "BatchNorm29"
+  type: "BatchNorm"
+  bottom: "Concat_14"
+  top: "BatchNorm29"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale29"
+  type: "Scale"
+  bottom: "BatchNorm29"
+  top: "BatchNorm29"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU29"
+  type: "ReLU"
+  bottom: "BatchNorm29"
+  top: "BatchNorm29"
+}
+layer {
+  name: "Convolution27"
+  type: "Convolution"
+  bottom: "BatchNorm29"
+  top: "Convolution27"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 60
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm30"
+  type: "BatchNorm"
+  bottom: "Convolution27"
+  top: "BatchNorm30"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale30"
+  type: "Scale"
+  bottom: "BatchNorm30"
+  top: "BatchNorm30"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU30"
+  type: "ReLU"
+  bottom: "BatchNorm30"
+  top: "BatchNorm30"
+}
+layer {
+  name: "Conv_down_15"
+  type: "Convolution"
+  bottom: "BatchNorm30"
+  top: "Conv_down_15"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 60
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 2
+    kernel_size: 2
+    kernel_size: 2
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm31"
+  type: "BatchNorm"
+  bottom: "Conv_down_15"
+  top: "BatchNorm31"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale31"
+  type: "Scale"
+  bottom: "BatchNorm31"
+  top: "BatchNorm31"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU31"
+  type: "ReLU"
+  bottom: "BatchNorm31"
+  top: "BatchNorm31"
+}
+layer {
+  name: "Convolution28"
+  type: "Convolution"
+  bottom: "BatchNorm31"
+  top: "Convolution28"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm32"
+  type: "BatchNorm"
+  bottom: "Convolution28"
+  top: "BatchNorm32"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale32"
+  type: "Scale"
+  bottom: "BatchNorm32"
+  top: "BatchNorm32"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU32"
+  type: "ReLU"
+  bottom: "BatchNorm32"
+  top: "BatchNorm32"
+}
+layer {
+  name: "Convolution29"
+  type: "Convolution"
+  bottom: "BatchNorm32"
+  top: "Convolution29"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout13"
+  type: "Dropout"
+  bottom: "Convolution29"
+  top: "Dropout13"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_19"
+  type: "Concat"
+  bottom: "Conv_down_15"
+  bottom: "Dropout13"
+  top: "Concat_19"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm33"
+  type: "BatchNorm"
+  bottom: "Concat_19"
+  top: "BatchNorm33"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale33"
+  type: "Scale"
+  bottom: "BatchNorm33"
+  top: "BatchNorm33"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU33"
+  type: "ReLU"
+  bottom: "BatchNorm33"
+  top: "BatchNorm33"
+}
+layer {
+  name: "Convolution30"
+  type: "Convolution"
+  bottom: "BatchNorm33"
+  top: "Convolution30"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm34"
+  type: "BatchNorm"
+  bottom: "Convolution30"
+  top: "BatchNorm34"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale34"
+  type: "Scale"
+  bottom: "BatchNorm34"
+  top: "BatchNorm34"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU34"
+  type: "ReLU"
+  bottom: "BatchNorm34"
+  top: "BatchNorm34"
+}
+layer {
+  name: "Convolution31"
+  type: "Convolution"
+  bottom: "BatchNorm34"
+  top: "Convolution31"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout14"
+  type: "Dropout"
+  bottom: "Convolution31"
+  top: "Dropout14"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_20"
+  type: "Concat"
+  bottom: "Concat_19"
+  bottom: "Dropout14"
+  top: "Concat_20"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm35"
+  type: "BatchNorm"
+  bottom: "Concat_20"
+  top: "BatchNorm35"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale35"
+  type: "Scale"
+  bottom: "BatchNorm35"
+  top: "BatchNorm35"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU35"
+  type: "ReLU"
+  bottom: "BatchNorm35"
+  top: "BatchNorm35"
+}
+layer {
+  name: "Convolution32"
+  type: "Convolution"
+  bottom: "BatchNorm35"
+  top: "Convolution32"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm36"
+  type: "BatchNorm"
+  bottom: "Convolution32"
+  top: "BatchNorm36"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale36"
+  type: "Scale"
+  bottom: "BatchNorm36"
+  top: "BatchNorm36"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU36"
+  type: "ReLU"
+  bottom: "BatchNorm36"
+  top: "BatchNorm36"
+}
+layer {
+  name: "Convolution33"
+  type: "Convolution"
+  bottom: "BatchNorm36"
+  top: "Convolution33"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout15"
+  type: "Dropout"
+  bottom: "Convolution33"
+  top: "Dropout15"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_21"
+  type: "Concat"
+  bottom: "Concat_20"
+  bottom: "Dropout15"
+  top: "Concat_21"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm37"
+  type: "BatchNorm"
+  bottom: "Concat_21"
+  top: "BatchNorm37"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale37"
+  type: "Scale"
+  bottom: "BatchNorm37"
+  top: "BatchNorm37"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU37"
+  type: "ReLU"
+  bottom: "BatchNorm37"
+  top: "BatchNorm37"
+}
+layer {
+  name: "Convolution34"
+  type: "Convolution"
+  bottom: "BatchNorm37"
+  top: "Convolution34"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 64
+    bias_term: false
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "BatchNorm38"
+  type: "BatchNorm"
+  bottom: "Convolution34"
+  top: "BatchNorm38"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "Scale38"
+  type: "Scale"
+  bottom: "BatchNorm38"
+  top: "BatchNorm38"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "ReLU38"
+  type: "ReLU"
+  bottom: "BatchNorm38"
+  top: "BatchNorm38"
+}
+layer {
+  name: "Convolution35"
+  type: "Convolution"
+  bottom: "BatchNorm38"
+  top: "Convolution35"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 16
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 3
+    kernel_size: 3
+    kernel_size: 3
+    stride: 1
+    stride: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "Dropout16"
+  type: "Dropout"
+  bottom: "Convolution35"
+  top: "Dropout16"
+  dropout_param {
+    dropout_ratio: 0.20000000298
+  }
+}
+layer {
+  name: "Concat_22"
+  type: "Concat"
+  bottom: "Concat_21"
+  bottom: "Dropout16"
+  top: "Concat_22"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Deconvolution_20"
+  type: "Deconvolution"
+  bottom: "Concat_22"
+  top: "Deconvolution_20"
+  param {
+    lr_mult: 0.10000000149
+    decay_mult: 1.0
+  }
+  convolution_param {
+    num_output: 4
+    bias_term: false
+    pad: 1
+    pad: 1
+    pad: 1
+    kernel_size: 18
+    kernel_size: 18
+    kernel_size: 18
+    group: 4
+    stride: 16
+    stride: 16
+    stride: 16
+    weight_filler {
+      type: "bilinear_3D"
+    }
+  }
+}
+layer {
+  name: "Concat1"
+  type: "Concat"
+  bottom: "conv1c"
+  bottom: "Deconvolution_5"
+  bottom: "Deconvolution_10"
+  bottom: "Deconvolution_15"
+  bottom: "Deconvolution_20"
+  top: "Concat1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "bnorm_concat"
+  type: "BatchNorm"
+  bottom: "Concat1"
+  top: "bnorm_concat"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  batch_norm_param {
+    use_global_stats: true
+  }
+}
+layer {
+  name: "scale_concat"
+  type: "Scale"
+  bottom: "bnorm_concat"
+  top: "bnorm_concat"
+  scale_param {
+    filler {
+      value: 1.0
+    }
+    bias_term: true
+    bias_filler {
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "relu_concat"
+  type: "ReLU"
+  bottom: "bnorm_concat"
+  top: "bnorm_concat"
+}
+layer {
+  name: "Convolution36"
+  type: "Convolution"
+  bottom: "bnorm_concat"
+  top: "Convolution36"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 4
+    pad: 0
+    pad: 0
+    pad: 0
+    kernel_size: 1
+    kernel_size: 1
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    axis: 1
+  }
+}
+layer {
+  name: "softmax"
+  type: "Softmax"
+  bottom: "Convolution36"
+  top: "softmax"
+}
+