Noobie question: multiple copies of same parameter in a net?

[Aardvark Zebra]

Just started learning about Caffe, and I was browsing the LeNet definition.
--
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 20
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
--

Why are there 2 "lr_mult" parameters? What do they mean? Does the order matter?

Thanks!

[Bartosz Ludwiczuk]

Each layer learns two types of parameter:

 - weights of kernel

- biases (sometimes know as an activation level of neuron)

First is for weights of kernel, the second one is for biases.