type: "nn"
layers {
  name: "data3D"
  type: "data"
  size: 360
  active_type: ""
  height: 6
  width: 20
  depth: 3
}
layers {
  name: "__batch_norm_0__"
  type: "batch_norm"
  size: 360
  active_type: "relu"
  inputs {
    input_layer_name: "data3D"
    input_parameter_name: "___batch_norm_0__.w0"
    image_conf {
      channels: 1
      img_size: 20
      img_size_y: 6
      img_size_z: 3
    }
  }
  inputs {
    input_layer_name: "data3D"
    input_parameter_name: "___batch_norm_0__.w1"
  }
  inputs {
    input_layer_name: "data3D"
    input_parameter_name: "___batch_norm_0__.w2"
  }
  bias_parameter_name: "___batch_norm_0__.wbias"
  moving_average_fraction: 0.9
  height: 6
  width: 20
  depth: 3
}
parameters {
  name: "___batch_norm_0__.w0"
  size: 1
  initial_mean: 1.0
  initial_std: 0.0
  initial_strategy: 0
  initial_smart: false
}
parameters {
  name: "___batch_norm_0__.w1"
  size: 1
  initial_mean: 0.0
  initial_std: 0.0
  dims: 1
  dims: 1
  initial_strategy: 0
  initial_smart: false
  is_static: true
  is_shared: true
}
parameters {
  name: "___batch_norm_0__.w2"
  size: 1
  initial_mean: 0.0
  initial_std: 0.0
  dims: 1
  dims: 1
  initial_strategy: 0
  initial_smart: false
  is_static: true
  is_shared: true
}
parameters {
  name: "___batch_norm_0__.wbias"
  size: 1
  initial_mean: 0.0
  initial_std: 0.0
  dims: 1
  dims: 1
  initial_strategy: 0
  initial_smart: false
}
input_layer_names: "data3D"
output_layer_names: "__batch_norm_0__"
sub_models {
  name: "root"
  layer_names: "data3D"
  layer_names: "__batch_norm_0__"
  input_layer_names: "data3D"
  output_layer_names: "__batch_norm_0__"
  is_recurrent_layer_group: false
}

