Caffe中卷积层的输出是不同的

Question

1. 我用两个输入的caffe编写了一个类似暹罗语的网络。具有第一输入的卷积层的输出总是相同的，而第二输出每次都改变。输入层和卷积层如下：

layer {
  name: "input"
  type: "Input"
  top: "data1"
  top: "data2"
  input_param {
    shape {dim: 1
           dim: 1
           dim: 28
           dim: 28
    }
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data1"
  top: "conv1_1"
  convolution_param {
    num_output: 20
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data2"
  top: "conv1_2"
  convolution_param {
    num_output: 20
    kernel_size: 5
    bias_term: false
    weight_filler {
      type: "xavier"
    }
  }
}

1. 我可以用python层构建卷积层吗？如果是的话，如何