name: "vgg_1/8"layer {  name: "data"  type: "AnnotatedData"  top: "data"  top: "label"  include {    phase: TRAIN  }  transform_param {    mirror: true    mean_value: 104.0    mean_value: 117.0    mean_value: 123.0    resize_param {      prob: 1.0      resize_mode: WARP      height: 352      width: 704      interp_mode: LINEAR      interp_mode: AREA      interp_mode: NEAREST      interp_mode: CUBIC      interp_mode: LANCZOS4    }    emit_constraint {      emit_type: CENTER    }    distort_param {      brightness_prob: 0.5      brightness_delta: 32.0      contrast_prob: 0.5      contrast_lower: 0.5      contrast_upper: 1.5      hue_prob: 0.5      hue_delta: 18.0      saturation_prob: 0.5      saturation_lower: 0.5      saturation_upper: 1.5      random_order_prob: 0.0    }    expand_param {      prob: 0.5      max_expand_ratio: 4.0    }  }  data_param {    source:"examples/cityscapes/cityscapes_train_lmdb"    batch_size: 1    backend: LMDB  }  annotated_data_param {    batch_sampler {      max_sample: 1      max_trials: 1    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        min_jaccard_overlap: 0.10000000149      }      max_sample: 1      max_trials: 50    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        min_jaccard_overlap: 0.300000011921      }      max_sample: 1      max_trials: 50    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        min_jaccard_overlap: 0.5      }      max_sample: 1      max_trials: 50    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        min_jaccard_overlap: 0.699999988079      }      max_sample: 1      max_trials: 50    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        min_jaccard_overlap: 0.899999976158      }      max_sample: 1      max_trials: 50    }    batch_sampler {      sampler {        min_scale: 0.300000011921        max_scale: 1.0        min_aspect_ratio: 0.5        max_aspect_ratio: 2.0      }      sample_constraint {        max_jaccard_overlap: 1.0      }      max_sample: 1      max_trials: 50    }    label_map_file: "data/cityscapes/labelmap_cityscapes.prototxt"  }}layer {  name: "conv1_1"  type: "Convolution"  bottom: "data"  top: "conv1_1"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 8    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu1_1"  type: "ReLU"  bottom: "conv1_1"  top: "conv1_1"}layer {  name: "conv1_2"  type: "Convolution"  bottom: "conv1_1"  top: "conv1_2"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 8    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}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"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 16    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu2_1"  type: "ReLU"  bottom: "conv2_1"  top: "conv2_1"}layer {  name: "conv2_2"  type: "Convolution"  bottom: "conv2_1"  top: "conv2_2"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 16    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}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"  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    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu3_1"  type: "ReLU"  bottom: "conv3_1"  top: "conv3_1"}layer {  name: "conv3_2"  type: "Convolution"  bottom: "conv3_1"  top: "conv3_2"  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    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu3_2"  type: "ReLU"  bottom: "conv3_2"  top: "conv3_2"}layer {  name: "conv3_3"  type: "Convolution"  bottom: "conv3_2"  top: "conv3_3"  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    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}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"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu4_1"  type: "ReLU"  bottom: "conv4_1"  top: "conv4_1"}layer {  name: "conv4_2"  type: "Convolution"  bottom: "conv4_1"  top: "conv4_2"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu4_2"  type: "ReLU"  bottom: "conv4_2"  top: "conv4_2"}layer {  name: "conv4_3"  type: "Convolution"  bottom: "conv4_2"  top: "conv4_3"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}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"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu5_1"  type: "ReLU"  bottom: "conv5_1"  top: "conv5_1"}layer {  name: "conv5_2"  type: "Convolution"  bottom: "conv5_1"  top: "conv5_2"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu5_2"  type: "ReLU"  bottom: "conv5_2"  top: "conv5_2"}layer {  name: "conv5_3"  type: "Convolution"  bottom: "conv5_2"  top: "conv5_3"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}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"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 128    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu6"  type: "ReLU"  bottom: "fc6"  top: "fc6"}layer {  name: "fc7"  type: "Convolution"  bottom: "fc6"  top: "fc7"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 128    kernel_size: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu7"  type: "ReLU"  bottom: "fc7"  top: "fc7"}layer {  name: "conv6_1"  type: "Convolution"  bottom: "fc7"  top: "conv6_1"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 32    pad: 0    kernel_size: 1    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv6_1_relu"  type: "ReLU"  bottom: "conv6_1"  top: "conv6_1"}layer {  name: "conv6_2"  type: "Convolution"  bottom: "conv6_1"  top: "conv6_2"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    stride: 2    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv6_2_relu"  type: "ReLU"  bottom: "conv6_2"  top: "conv6_2"}layer {  name: "conv4_3_norm_mbox_loc"  type: "Convolution"  bottom: "conv4_3"  top: "conv4_3_norm_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv4_3_norm_mbox_loc_perm"  type: "Permute"  bottom: "conv4_3_norm_mbox_loc"  top: "conv4_3_norm_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv4_3_norm_mbox_loc_flat"  type: "Flatten"  bottom: "conv4_3_norm_mbox_loc_perm"  top: "conv4_3_norm_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "conv4_3_norm_mbox_conf"  type: "Convolution"  bottom: "conv4_3"  top: "conv4_3_norm_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 6    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv4_3_norm_mbox_conf_perm"  type: "Permute"  bottom: "conv4_3_norm_mbox_conf"  top: "conv4_3_norm_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv4_3_norm_mbox_conf_flat"  type: "Flatten"  bottom: "conv4_3_norm_mbox_conf_perm"  top: "conv4_3_norm_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "conv4_3_norm_mbox_priorbox"  type: "PriorBox"  bottom: "conv4_3"  bottom: "data"  top: "conv4_3_norm_mbox_priorbox"  prior_box_param {    min_size: 16.0    aspect_ratio: 2.0    flip: true    clip: false    variance: 0.10000000149    variance: 0.10000000149    variance: 0.20000000298    variance: 0.20000000298    step: 8.0    offset: 0.5  }}layer {  name: "conv5_3_norm_mbox_loc"  type: "Convolution"  bottom: "conv5_3"  top: "conv5_3_norm_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv5_3_norm_mbox_loc_perm"  type: "Permute"  bottom: "conv5_3_norm_mbox_loc"  top: "conv5_3_norm_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv5_3_norm_mbox_loc_flat"  type: "Flatten"  bottom: "conv5_3_norm_mbox_loc_perm"  top: "conv5_3_norm_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "conv5_3_norm_mbox_conf"  type: "Convolution"  bottom: "conv5_3"  top: "conv5_3_norm_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 6    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv5_3_norm_mbox_conf_perm"  type: "Permute"  bottom: "conv5_3_norm_mbox_conf"  top: "conv5_3_norm_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv5_3_norm_mbox_conf_flat"  type: "Flatten"  bottom: "conv5_3_norm_mbox_conf_perm"  top: "conv5_3_norm_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "conv5_3_norm_mbox_priorbox"  type: "PriorBox"  bottom: "conv5_3"  bottom: "data"  top: "conv5_3_norm_mbox_priorbox"  prior_box_param {    min_size: 32.0    aspect_ratio: 2.0    flip: true    clip: false    variance: 0.10000000149    variance: 0.10000000149    variance: 0.20000000298    variance: 0.20000000298    step: 16.0    offset: 0.5  }}layer {  name: "fc7_mbox_loc"  type: "Convolution"  bottom: "fc7"  top: "fc7_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "fc7_mbox_loc_perm"  type: "Permute"  bottom: "fc7_mbox_loc"  top: "fc7_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "fc7_mbox_loc_flat"  type: "Flatten"  bottom: "fc7_mbox_loc_perm"  top: "fc7_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "fc7_mbox_conf"  type: "Convolution"  bottom: "fc7"  top: "fc7_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 6    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "fc7_mbox_conf_perm"  type: "Permute"  bottom: "fc7_mbox_conf"  top: "fc7_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "fc7_mbox_conf_flat"  type: "Flatten"  bottom: "fc7_mbox_conf_perm"  top: "fc7_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "fc7_mbox_priorbox"  type: "PriorBox"  bottom: "fc7"  bottom: "data"  top: "fc7_mbox_priorbox"  prior_box_param {    min_size: 64.0    aspect_ratio: 2.0    flip: true    clip: false    variance: 0.10000000149    variance: 0.10000000149    variance: 0.20000000298    variance: 0.20000000298    step: 32.0    offset: 0.5  }}layer {  name: "conv6_2_mbox_loc"  type: "Convolution"  bottom: "conv6_2"  top: "conv6_2_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv6_2_mbox_loc_perm"  type: "Permute"  bottom: "conv6_2_mbox_loc"  top: "conv6_2_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv6_2_mbox_loc_flat"  type: "Flatten"  bottom: "conv6_2_mbox_loc_perm"  top: "conv6_2_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "conv6_2_mbox_conf"  type: "Convolution"  bottom: "conv6_2"  top: "conv6_2_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 6    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "conv6_2_mbox_conf_perm"  type: "Permute"  bottom: "conv6_2_mbox_conf"  top: "conv6_2_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "conv6_2_mbox_conf_flat"  type: "Flatten"  bottom: "conv6_2_mbox_conf_perm"  top: "conv6_2_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "conv6_2_mbox_priorbox"  type: "PriorBox"  bottom: "conv6_2"  bottom: "data"  top: "conv6_2_mbox_priorbox"  prior_box_param {    min_size: 128.0    aspect_ratio: 2.0    flip: true    clip: false    variance: 0.10000000149    variance: 0.10000000149    variance: 0.20000000298    variance: 0.20000000298    step: 64.0    offset: 0.5  }}layer {  name: "arm_loc"  type: "Concat"  bottom: "conv4_3_norm_mbox_loc_flat"  bottom: "conv5_3_norm_mbox_loc_flat"  bottom: "fc7_mbox_loc_flat"  bottom: "conv6_2_mbox_loc_flat"  top: "arm_loc"  concat_param {    axis: 1  }}layer {  name: "arm_conf"  type: "Concat"  bottom: "conv4_3_norm_mbox_conf_flat"  bottom: "conv5_3_norm_mbox_conf_flat"  bottom: "fc7_mbox_conf_flat"  bottom: "conv6_2_mbox_conf_flat"  top: "arm_conf"  concat_param {    axis: 1  }}layer {  name: "arm_priorbox"  type: "Concat"  bottom: "conv4_3_norm_mbox_priorbox"  bottom: "conv5_3_norm_mbox_priorbox"  bottom: "fc7_mbox_priorbox"  bottom: "conv6_2_mbox_priorbox"  top: "arm_priorbox"  concat_param {    axis: 2  }}layer {  name: "P3_mbox_loc_p"  type: "Convolution"  bottom: "conv4_3"  top: "P3_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P3_mbox_loc_perm"  type: "Permute"  bottom: "P3_mbox_loc"  top: "P3_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P3_mbox_loc_flat"  type: "Flatten"  bottom: "P3_mbox_loc_perm"  top: "P3_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "P3_mbox_conf_p"  type: "Convolution"  bottom: "conv4_3"  top: "P3_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P3_mbox_conf_perm"  type: "Permute"  bottom: "P3_mbox_conf"  top: "P3_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P3_mbox_conf_flat"  type: "Flatten"  bottom: "P3_mbox_conf_perm"  top: "P3_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "P4_mbox_loc_p"  type: "Convolution"  bottom: "conv5_3"  top: "P4_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P4_mbox_loc_perm"  type: "Permute"  bottom: "P4_mbox_loc"  top: "P4_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P4_mbox_loc_flat"  type: "Flatten"  bottom: "P4_mbox_loc_perm"  top: "P4_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "P4_mbox_conf_p"  type: "Convolution"  bottom: "conv5_3"  top: "P4_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P4_mbox_conf_perm"  type: "Permute"  bottom: "P4_mbox_conf"  top: "P4_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P4_mbox_conf_flat"  type: "Flatten"  bottom: "P4_mbox_conf_perm"  top: "P4_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "P5_mbox_loc_p"  type: "Convolution"  bottom: "fc7"  top: "P5_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P5_mbox_loc_perm"  type: "Permute"  bottom: "P5_mbox_loc"  top: "P5_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P5_mbox_loc_flat"  type: "Flatten"  bottom: "P5_mbox_loc_perm"  top: "P5_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "P5_mbox_conf_p"  type: "Convolution"  bottom: "fc7"  top: "P5_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P5_mbox_conf_perm"  type: "Permute"  bottom: "P5_mbox_conf"  top: "P5_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P5_mbox_conf_flat"  type: "Flatten"  bottom: "P5_mbox_conf_perm"  top: "P5_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "P6_mbox_loc_p"  type: "Convolution"  bottom: "conv6_2"  top: "P6_mbox_loc"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P6_mbox_loc_perm"  type: "Permute"  bottom: "P6_mbox_loc"  top: "P6_mbox_loc_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P6_mbox_loc_flat"  type: "Flatten"  bottom: "P6_mbox_loc_perm"  top: "P6_mbox_loc_flat"  flatten_param {    axis: 1  }}layer {  name: "P6_mbox_conf_p"  type: "Convolution"  bottom: "conv6_2"  top: "P6_mbox_conf"  param {    lr_mult: 1.0    decay_mult: 1.0  }  param {    lr_mult: 2.0    decay_mult: 0.0  }  convolution_param {    num_output: 12    pad: 1    kernel_size: 3    stride: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "P6_mbox_conf_perm"  type: "Permute"  bottom: "P6_mbox_conf"  top: "P6_mbox_conf_perm"  permute_param {    order: 0    order: 2    order: 3    order: 1  }}layer {  name: "P6_mbox_conf_flat"  type: "Flatten"  bottom: "P6_mbox_conf_perm"  top: "P6_mbox_conf_flat"  flatten_param {    axis: 1  }}layer {  name: "odm_loc"  type: "Concat"  bottom: "P3_mbox_loc_flat"  bottom: "P4_mbox_loc_flat"  bottom: "P5_mbox_loc_flat"  bottom: "P6_mbox_loc_flat"  top: "odm_loc"  concat_param {    axis: 1  }}layer {  name: "odm_conf"  type: "Concat"  bottom: "P3_mbox_conf_flat"  bottom: "P4_mbox_conf_flat"  bottom: "P5_mbox_conf_flat"  bottom: "P6_mbox_conf_flat"  top: "odm_conf"  concat_param {    axis: 1  }}layer {  name: "arm_loss"  type: "MultiBoxLoss"  bottom: "arm_loc"  bottom: "arm_conf"  bottom: "arm_priorbox"  bottom: "label"  top: "arm_loss"  include {    phase: TRAIN  }  propagate_down: true  propagate_down: true  propagate_down: false  propagate_down: false  loss_param {    normalization: VALID  }  multibox_loss_param {    loc_loss_type: SMOOTH_L1    conf_loss_type: SOFTMAX    loc_weight: 1.0    num_classes: 2    share_location: true    match_type: PER_PREDICTION    overlap_threshold: 0.5    use_prior_for_matching: true    background_label_id: 0    use_difficult_gt: true    neg_pos_ratio: 3.0    neg_overlap: 0.5    code_type: CENTER_SIZE    ignore_cross_boundary_bbox: false    mining_type: MAX_NEGATIVE    objectness_score: 0.00999999977648  }}layer {  name: "arm_conf_reshape"  type: "Reshape"  bottom: "arm_conf"  top: "arm_conf_reshape"  reshape_param {    shape {      dim: 0      dim: -1      dim: 2    }  }}layer {  name: "arm_conf_softmax"  type: "Softmax"  bottom: "arm_conf_reshape"  top: "arm_conf_softmax"  softmax_param {    axis: 2  }}layer {  name: "arm_conf_flatten"  type: "Flatten"  bottom: "arm_conf_softmax"  top: "arm_conf_flatten"  flatten_param {    axis: 1  }}layer {  name: "odm_loss"  type: "MultiBoxLoss"  bottom: "odm_loc"  bottom: "odm_conf"  bottom: "arm_priorbox"  bottom: "label"  bottom: "arm_conf_flatten"  bottom: "arm_loc"  top: "odm_loss"  include {    phase: TRAIN  }  propagate_down: true  propagate_down: true  propagate_down: false  propagate_down: false  propagate_down: false  propagate_down: false  loss_param {    normalization: VALID  }  multibox_loss_param {    loc_loss_type: SMOOTH_L1    conf_loss_type: SOFTMAX    loc_weight: 1.0    num_classes: 4    share_location: true    match_type: PER_PREDICTION    overlap_threshold: 0.5    use_prior_for_matching: true    background_label_id: 0    use_difficult_gt: true    neg_pos_ratio: 3.0    neg_overlap: 0.5    code_type: CENTER_SIZE    ignore_cross_boundary_bbox: false    mining_type: MAX_NEGATIVE    objectness_score: 0.00999999977648  }}layer {  name: "conv1_1_t"  type: "Convolution"  bottom: "data"  top: "conv1_1_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu1_1_t"  type: "ReLU"  bottom: "conv1_1_t"  top: "conv1_1_t"}layer {  name: "conv1_2_t"  type: "Convolution"  bottom: "conv1_1_t"  top: "conv1_2_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 64    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu1_2_t"  type: "ReLU"  bottom: "conv1_2_t"  top: "conv1_2_t"}layer {  name: "pool1_t"  type: "Pooling"  bottom: "conv1_2_t"  top: "pool1_t"  pooling_param {    pool: MAX    kernel_size: 2    stride: 2  }}layer {  name: "conv2_1_t"  type: "Convolution"  bottom: "pool1_t"  top: "conv2_1_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 128    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu2_1_t"  type: "ReLU"  bottom: "conv2_1_t"  top: "conv2_1_t"}layer {  name: "conv2_2_t"  type: "Convolution"  bottom: "conv2_1_t"  top: "conv2_2_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 128    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu2_2_t"  type: "ReLU"  bottom: "conv2_2_t"  top: "conv2_2_t"}layer {  name: "pool2_t"  type: "Pooling"  bottom: "conv2_2_t"  top: "pool2_t"  pooling_param {    pool: MAX    kernel_size: 2    stride: 2  }}layer {  name: "conv3_1_t"  type: "Convolution"  bottom: "pool2_t"  top: "conv3_1_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 256    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu3_1_t"  type: "ReLU"  bottom: "conv3_1_t"  top: "conv3_1_t"}layer {  name: "conv3_2_t"  type: "Convolution"  bottom: "conv3_1_t"  top: "conv3_2_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 256    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu3_2_t"  type: "ReLU"  bottom: "conv3_2_t"  top: "conv3_2_t"}layer {  name: "conv3_3_t"  type: "Convolution"  bottom: "conv3_2_t"  top: "conv3_3_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 256    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu3_3_t"  type: "ReLU"  bottom: "conv3_3_t"  top: "conv3_3_t"}layer {  name: "pool3_t"  type: "Pooling"  bottom: "conv3_3_t"  top: "pool3_t"  pooling_param {    pool: MAX    kernel_size: 2    stride: 2  }}layer {  name: "conv4_1_t"  type: "Convolution"  bottom: "pool3_t"  top: "conv4_1_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu4_1_t"  type: "ReLU"  bottom: "conv4_1_t"  top: "conv4_1_t"}layer {  name: "conv4_2_t"  type: "Convolution"  bottom: "conv4_1_t"  top: "conv4_2_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu4_2_t"  type: "ReLU"  bottom: "conv4_2_t"  top: "conv4_2_t"}layer {  name: "conv4_3_t"  type: "Convolution"  bottom: "conv4_2_t"  top: "conv4_3_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }  }}layer {  name: "relu4_3_t"  type: "ReLU"  bottom: "conv4_3_t"  top: "conv4_3_t"}layer {  name: "pool4_t"  type: "Pooling"  bottom: "conv4_3_t"  top: "pool4_t"  pooling_param {    pool: MAX    kernel_size: 2    stride: 2  }}layer {  name: "conv5_1_t"  type: "Convolution"  bottom: "pool4_t"  top: "conv5_1_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }    dilation: 1  }}layer {  name: "relu5_1_t"  type: "ReLU"  bottom: "conv5_1_t"  top: "conv5_1_t"}layer {  name: "conv5_2_t"  type: "Convolution"  bottom: "conv5_1_t"  top: "conv5_2_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }    dilation: 1  }}layer {  name: "relu5_2_t"  type: "ReLU"  bottom: "conv5_2_t"  top: "conv5_2_t"}layer {  name: "conv5_3_t"  type: "Convolution"  bottom: "conv5_2_t"  top: "conv5_3_t"  param {    lr_mult: 0    decay_mult: 0  }  param {    lr_mult: 0    decay_mult: 0  }  convolution_param {    num_output: 512    pad: 1    kernel_size: 3    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0.0    }    dilation: 1  }}layer {  name: "relu5_3_t"  type: "ReLU"  bottom: "conv5_3_t"  top: "conv5_3_t"}layer {  name: "conv5_3_m"  type: "Convolution"  bottom: "conv5_3"  top: "conv5_3_m"  propagate_down: true  param {    lr_mult: 1    decay_mult: 1  }  param {    lr_mult: 2    decay_mult: 0  }  convolution_param {    num_output: 512    kernel_size: 1    weight_filler {      type: "xavier"    }    bias_filler {      type: "constant"      value: 0    }  }  }layer {  name: "relu5_3_m"  type: "ReLU"  bottom: "conv5_3_m"  top: "conv5_3_m"}layer {  name: "roi_pool_t"  type: "ROIPooling"  bottom: "conv5_3_t"  bottom: "label"  top: "pool_t"  roi_pooling_param {    pooled_w: 7    pooled_h: 7  }  propagate_down: false  propagate_down: false}layer {  name: "roi_pool_s"  type: "ROIPooling"  bottom: "conv5_3_m"  bottom: "label"  top: "pool_s"  roi_pooling_param {    pooled_w: 7    pooled_h: 7  }  propagate_down: true  propagate_down: false}layer {  name: "mimic_loss"  type: "EuclideanLoss"  bottom: "pool_t"  bottom: "pool_s"  top: "mimic_loss"  propagate_down: false  propagate_down: true  loss_weight: 10  include {    phase: TRAIN  }}