TMDSEVM572X: Does caffe-jacinto and TIDL support sharing weights?

####################################layer1 ##############################


layer {
    bottom: "data/layer1"
    top: "conv1/layer1"
    name: "conv1/layer1"
    type: "Convolution"
    param {
        name: "layer/conv1_w"
        lr_mult: 1
        decay_mult: 1
    }
    param {
        name: "layer/conv1_b"
        lr_mult: 2
        decay_mult: 0
    }
    convolution_param {
        num_output: 64
        kernel_size: 7
        pad: 3
        stride: 2
        weight_filler {
            type: "xavier"
        }
    }
}


######################################layer2#############################


layer {
    bottom: "data/layer2"
    top: "conv1/layer2"
    name: "conv1/layer2"
    type: "Convolution"
    param {
        name: "layer/conv1_w"
        lr_mult: 1
        decay_mult: 1
    }
    param {
        name: "layer/conv1_b"
        lr_mult: 2
        decay_mult: 0
    }
    convolution_param {
        num_output: 64
        kernel_size: 7
        pad: 3
        stride: 2
        weight_filler {
      type: "xavier"
    }
    }
}



#######################################layer3###############################


layer {
    bottom: "data/layer3"
    top: "conv1/layer3"
    name: "conv1/layer3"
    type: "Convolution"
    param {
        name: "layer/conv1_w"
        lr_mult: 1
        decay_mult: 1
    }
    param {
        name: "layer/conv1_b"
        lr_mult: 2
        decay_mult: 0
    }
    convolution_param {
        num_output: 64
        kernel_size: 7
        pad: 3
        stride: 2
        weight_filler {
      type: "xavier"
    }
    }
}