name: "autocolorize"

layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape: {
      dim: 1
      dim: 1
      dim: 514
      dim: 514
    }
  }
}

layer {
  bottom: "data"
  top: "conv1_1"
  name: "conv1_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv1_1"
  type: "ReLU"
  bottom: "conv1_1"
  top: "conv1_1"
}
layer {
  bottom: "conv1_1"
  top: "conv1_2"
  name: "conv1_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv1_2"
  type: "ReLU"
  bottom: "conv1_2"
  top: "conv1_2"
}
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"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv2_1"
  type: "ReLU"
  bottom: "conv2_1"
  top: "conv2_1"
}
layer {
  bottom: "conv2_1"
  top: "conv2_2"
  name: "conv2_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv2_2"
  type: "ReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
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"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv3_1"
  type: "ReLU"
  bottom: "conv3_1"
  top: "conv3_1"
}
layer {
  bottom: "conv3_1"
  top: "conv3_2"
  name: "conv3_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv3_2"
  type: "ReLU"
  bottom: "conv3_2"
  top: "conv3_2"
}
layer {
  bottom: "conv3_2"
  top: "conv3_3"
  name: "conv3_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv3_3"
  type: "ReLU"
  bottom: "conv3_3"
  top: "conv3_3"
}
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"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv4_1"
  type: "ReLU"
  bottom: "conv4_1"
  top: "conv4_1"
}
layer {
  bottom: "conv4_1"
  top: "conv4_2"
  name: "conv4_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv4_2"
  type: "ReLU"
  bottom: "conv4_2"
  top: "conv4_2"
}
layer {
  bottom: "conv4_2"
  top: "conv4_3"
  name: "conv4_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv4_3"
  type: "ReLU"
  bottom: "conv4_3"
  top: "conv4_3"
}
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"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv5_1"
  type: "ReLU"
  bottom: "conv5_1"
  top: "conv5_1"
}
layer {
  bottom: "conv5_1"
  top: "conv5_2"
  name: "conv5_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv5_2"
  type: "ReLU"
  bottom: "conv5_2"
  top: "conv5_2"
}
layer {
  bottom: "conv5_2"
  top: "conv5_3"
  name: "conv5_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu_conv5_3"
  type: "ReLU"
  bottom: "conv5_3"
  top: "conv5_3"
}
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"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 4096
    pad: 3
    kernel_size: 7
  }
}
layer {
  name: "relu_fc6"
  type: "ReLU"
  bottom: "fc6"
  top: "fc6"
}
layer {
  name: "dropout_fc6"
  type: "Dropout"
  bottom: "fc6"
  top: "fc6"
  dropout_param {
    dropout_ratio: 0.5
  }
}

layer {
  bottom: "fc6"
  top: "fc7"
  name: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 4096
    pad: 0
    kernel_size: 1
  }
}
layer {
  name: "relu_fc7"
  type: "ReLU"
  bottom: "fc7"
  top: "fc7"
}
layer {
  name: "dropout_fc7"
  type: "Dropout"
  bottom: "fc7"
  top: "fc7"
  dropout_param {
    dropout_ratio: 0.5
  }
}

layer {
  name: "data_full", type: "Pooling"
  bottom: "data" top: "data_full"
  pooling_param {
    kernel_size: 4 stride: 4
    pool: AVE
    pad: 0
  }
}

layer {
  name: "conv1_1_full", type: "Pooling"
  bottom: "conv1_1" top: "conv1_1_full"
  pooling_param {
    kernel_size: 4 stride: 4
    pool: AVE
    pad: 0
  }
}

layer {
  name: "conv1_2_full", type: "Pooling"
  bottom: "conv1_2" top: "conv1_2_full"
  pooling_param {
    kernel_size: 4 stride: 4
    pool: AVE
    pad: 0
  }
}

layer {
  name: "conv2_1_full", type: "Pooling"
  bottom: "conv2_1" top: "conv2_1_full"
  pooling_param {
    kernel_size: 2 stride: 2
    pool: AVE
    pad: 0
  }
}

layer {
  name: "conv2_2_full", type: "Pooling"
  bottom: "conv2_2" top: "conv2_2_full"
  pooling_param {
    kernel_size: 2 stride: 2
    pool: AVE
    pad: 0
  }
}

# conv4_1 upsampling
layer {
  name: "conv4_1_reshaped" type: "Reshape"
  bottom: "conv4_1" top: "conv4_1_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv4_1_full_reshaped", type: "Deconvolution"
  bottom: "conv4_1_reshaped" top: "conv4_1_full_reshaped"
  convolution_param {
    kernel_size: 4 stride: 2
    num_output: 1 group: 1
    pad: 1
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv4_1_full" type: "Reshape"
  bottom: "conv4_1_full_reshaped" top: "conv4_1_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# conv4_2 upsampling
layer {
  name: "conv4_2_reshaped" type: "Reshape"
  bottom: "conv4_2" top: "conv4_2_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv4_2_full_reshaped", type: "Deconvolution"
  bottom: "conv4_2_reshaped" top: "conv4_2_full_reshaped"
  convolution_param {
    kernel_size: 4 stride: 2
    num_output: 1 group: 1
    pad: 1
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv4_2_full" type: "Reshape"
  bottom: "conv4_2_full_reshaped" top: "conv4_2_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# conv4_3 upsampling
layer {
  name: "conv4_3_reshaped" type: "Reshape"
  bottom: "conv4_3" top: "conv4_3_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv4_3_full_reshaped", type: "Deconvolution"
  bottom: "conv4_3_reshaped" top: "conv4_3_full_reshaped"
  convolution_param {
    kernel_size: 4 stride: 2
    num_output: 1 group: 1
    pad: 1
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv4_3_full" type: "Reshape"
  bottom: "conv4_3_full_reshaped" top: "conv4_3_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# conv5_1 upsampling
layer {
  name: "conv5_1_reshaped" type: "Reshape"
  bottom: "conv5_1" top: "conv5_1_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv5_1_full_reshaped", type: "Deconvolution"
  bottom: "conv5_1_reshaped" top: "conv5_1_full_reshaped"
  convolution_param {
    kernel_size: 8 stride: 4
    num_output: 1 group: 1
    pad: 2
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv5_1_full" type: "Reshape"
  bottom: "conv5_1_full_reshaped" top: "conv5_1_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# conv5_2 upsampling
layer {
  name: "conv5_2_reshaped" type: "Reshape"
  bottom: "conv5_2" top: "conv5_2_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv5_2_full_reshaped", type: "Deconvolution"
  bottom: "conv5_2_reshaped" top: "conv5_2_full_reshaped"
  convolution_param {
    kernel_size: 8 stride: 4
    num_output: 1 group: 1
    pad: 2
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv5_2_full" type: "Reshape"
  bottom: "conv5_2_full_reshaped" top: "conv5_2_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# conv5_3 upsampling
layer {
  name: "conv5_3_reshaped" type: "Reshape"
  bottom: "conv5_3" top: "conv5_3_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "conv5_3_full_reshaped", type: "Deconvolution"
  bottom: "conv5_3_reshaped" top: "conv5_3_full_reshaped"
  convolution_param {
    kernel_size: 8 stride: 4
    num_output: 1 group: 1
    pad: 2
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "conv5_3_full" type: "Reshape"
  bottom: "conv5_3_full_reshaped" top: "conv5_3_full"
  reshape_param {
    shape { dim: -1 dim: 512 }
    axis: 0
    num_axes: 2
  }
}

# fc6 upsampling
layer {
  name: "fc6_reshaped" type: "Reshape"
  bottom: "fc6" top: "fc6_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "fc6_full_reshaped", type: "Deconvolution"
  bottom: "fc6_reshaped" top: "fc6_full_reshaped"
  convolution_param {
    kernel_size: 16 stride: 8
    num_output: 1 group: 1
    pad: 4
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "fc6_full" type: "Reshape"
  bottom: "fc6_full_reshaped" top: "fc6_full"
  reshape_param {
    shape { dim: -1 dim: 4096 }
    axis: 0
    num_axes: 2
  }
}

# fc7 upsampling
layer {
  name: "fc7_reshaped" type: "Reshape"
  bottom: "fc7" top: "fc7_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "fc7_full_reshaped", type: "Deconvolution"
  bottom: "fc7_reshaped" top: "fc7_full_reshaped"
  convolution_param {
    kernel_size: 16 stride: 8
    num_output: 1 group: 1
    pad: 4
    weight_filler: { type: "bilinear" } bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "fc7_full" type: "Reshape"
  bottom: "fc7_full_reshaped" top: "fc7_full"
  reshape_param {
    shape { dim: -1 dim: 4096 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "dense_hypercolumn"
  type: "Concat"
  bottom: "data_full"
  bottom: "conv1_1_full"
  bottom: "conv1_2_full"
  bottom: "conv2_1_full"
  bottom: "conv2_2_full"
  bottom: "conv3_1"
  bottom: "conv3_2"
  bottom: "conv3_3"
  bottom: "conv4_1_full"
  bottom: "conv4_2_full"
  bottom: "conv4_3_full"
  bottom: "conv5_1_full"
  bottom: "conv5_2_full"
  bottom: "conv5_3_full"
  bottom: "fc6_full"
  bottom: "fc7_full"
  top: "dense_hypercolumn"
  concat_param {
    axis: 1
  }
}

layer {
  bottom: "dense_hypercolumn"
  top: "h_fc1"
  name: "h_fc1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
  }
}
layer {
  name: "relu_h_fc1"
  type: "ReLU"
  bottom: "h_fc1"
  top: "h_fc1"
}

layer {
  bottom: "h_fc1"
  top: "prediction_h"
  name: "prediction_h"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
  }
}
layer {
  bottom: "h_fc1"
  top: "prediction_c"
  name: "prediction_c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  type: "Convolution"
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
  }
}

layer {
  name: "prediction_h_softmax"
  type: "Softmax"
  bottom: "prediction_h"
  top: "prediction_h_softmax"
}
layer {
  name: "prediction_c_softmax"
  type: "Softmax"
  bottom: "prediction_c"
  top: "prediction_c_softmax"
}

# prediction_h upsample
layer {
  name: "prediction_h_softmax_reshaped" type: "Reshape"
  bottom: "prediction_h_softmax" top: "prediction_h_softmax_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "prediction_h_full_reshaped"
  type: "Deconvolution"
  bottom: "prediction_h_softmax_reshaped"
  top: "prediction_h_full_reshaped"
  convolution_param {
    kernel_size: 8 stride: 4
    num_output: 1 group: 1
    pad: 2
    weight_filler: { type: "bilinear" }
    bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "prediction_h_full" type: "Reshape"
  bottom: "prediction_h_full_reshaped" top: "prediction_h_full"
  reshape_param {
    shape { dim: -1 dim: 32 }
    axis: 0
    num_axes: 2
  }
}

# prediction_c upsample
layer {
  name: "prediction_c_softmax_reshaped" type: "Reshape"
  bottom: "prediction_c_softmax" top: "prediction_c_softmax_reshaped"
  reshape_param {
    shape { dim: -1 dim: 1 }
    axis: 0
    num_axes: 2
  }
}

layer {
  name: "prediction_c_full_reshaped"
  type: "Deconvolution"
  bottom: "prediction_c_softmax_reshaped"
  top: "prediction_c_full_reshaped"
  convolution_param {
    kernel_size: 8 stride: 4
    num_output: 1 group: 1
    pad: 2
    weight_filler: { type: "bilinear" }
    bias_term: false
  }
  param { lr_mult: 0 decay_mult: 0 }
}

layer {
  name: "prediction_c_full" type: "Reshape"
  bottom: "prediction_c_full_reshaped" top: "prediction_c_full"
  reshape_param {
    shape { dim: -1 dim: 32 }
    axis: 0
    num_axes: 2
  }
}