In Caffe, we can set different learning rate for weight and bias in one layer.
For example:
layer {
    name: "conv2"
    type: "Convolution"
    bottom: "bn_conv2"
    top: "conv2"
    param {
       lr_mult: 1.000000*
    }
   param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}

the learning rate of weight and bias is leaning rate*lr_mult.
In pytorch, is it possible to set different learning rate for weight and bias in  one layer?
How to write the program？