import sys
import os
sys.path.append("/projects/caffe-ssd/python")
import caffe

net = caffe.NetSpec()
net.data, net.label = caffe.layers.Data(
    name="InputData",
    source="train_lmdb",
    backend = caffe.params.Data.LMDB,
    batch_size=32,
    ntop=2,
    include=dict(phase=caffe.TRAIN),
    transform_param
 
=dict(
        crop_size=227,
        mean_value=[104, 117, 123],
        mirror=True
    )
)
net.myconv = caffe.layers.Convolution(
    net.data,
    kernel_size=3,
    stride=1,
    pad=1,
    num_output=20,
    group=2,
    weight_filler=dict(type='xavier'),
    bias_filler=dict(type='constant',value=0))

net.myrelu 
 
= caffe.layers.ReLU(net.myconv, in_place=True)

print(str(net.to_proto()))

輸出：
layer {
  name: "InputData"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    crop_size: 227
    mean_value: 104.0
    mean_value: 117.0
    mean_value: 123.0
  }
  data_param {
    source: 
 
"train_lmdb"
    batch_size: 32
    backend: LMDB
  }
}
layer {
  name: "myconv"
  type: "Convolution"
  bottom: "data"
  top: "myconv"
  convolution_param {
    num_output: 20
    pad: 1
    kernel_size: 3
    group: 2
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "myrelu"
  type: "ReLU"
  bottom: "myconv"
  top: "myconv"
}