Encoder

name: "Encoder"
input: "data"

input_dim: None
input_dim: 3
input_dim: None
input_dim: None

layer {
    name: "centered"
    type: BiasLayer
    top: "centered"
    bottom: "data"
    param { 
        trainable: False
        b: [-83.0, -111.0, -106.0]
    }
}

layer {
    name: "normalized"
    type: ScaleLayer
    top: "normalized"
    bottom: "centered"
    param { 
        scales: [0.013888888888888888, 0.015384615384615385, 0.014492753623188406]
        trainable: False
    }
}

layer {
    name: "conv0"
    type: Conv2DLayer
    top: "conv0"
    bottom: "normalized"
    param { 
        pad: same
        stride: 1
        filter_size: 5
        nonlinearity: None
        num_filters: 3
    }
}

layer {
    name: "conv1"
    type: Conv2DLayer
    top: "conv1"
    bottom: "conv0"
    param { 
        pad: valid
        stride: 8
        filter_size: 8
        nonlinearity: None
        num_filters: 64
    }
}

layer {
    name: "conv2_1"
    type: Conv2DLayer
    top: "conv2_1"
    bottom: "conv1"
    param { 
        pad: same
        filter_size: 3
        nonlinearity: None
        num_filters: 16
    }
}

layer {
    name: "conv2_2"
    type: Conv2DLayer
    top: "conv2_2"
    bottom: "conv2_1"
    param { 
        filter_size: 1
        nonlinearity: None
        num_filters: 64
    }
}

layer {
    name: "es2"
    type: ElemwiseSumLayer
    top: "es2"
    bottom: "conv1"
    bottom: "conv2_2"
}

layer {
    name: "output"
    type: Conv2DLayer
    top: "output"
    bottom: "es2"
    param { 
        pad: valid
        stride: 2
        filter_size: 2
        nonlinearity: None
        num_filters: 192
    }
}