在Caffe中定義一個神經網絡結構可以通過編寫一個.prototxt文件來實現。該文件包含了神經網絡的層和其連接關系。

以下是一個簡單的示例，定義一個包含兩個卷積層和一個全連接層的神經網絡結構：

name: "SimpleNet"
layer {
  name: "data"
  type: "Data"
  top: "data"
  data_param {
    source: "path/to/your/data"
    backend: LMDB
    batch_size: 64
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 32
    kernel_size: 5
    stride: 1
    pad: 2
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv1"
  top: "conv2"
  convolution_param {
    num_output: 64
    kernel_size: 5
    stride: 1
    pad: 2
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "conv2"
  top: "fc1"
  inner_product_param {
    num_output: 10
  }
}
layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "fc1"
  bottom: "label"
  top: "accuracy"
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "fc1"
  bottom: "label"
  top: "loss"
}

這個示例中定義了一個包含一個數據層、兩個卷積層、一個全連接層和一個Softmax損失層的簡單神經網絡結構。你可以根據自己的需求修改層的類型、參數和連接關系來定義不同的神經網絡結構。