现在我正在逐层编写权重填充器，类似于

layer {  name: "Convolution1"  type: "Convolution"  bottom: "data"  top: "Convolution1"  convolution_param {    num_output: 20    kernel_size: 5    weight_filler {      type: "xavier"    }  }}

我如何设置全局的权重填充器类型？谢谢。

回答：

目前似乎没有其他方法可以做到。在caffe.proto文件中，NetParameter的定义如下，其中没有类似default_weight_filler的选项。

message NetParameter {  optional string name = 1; // consider giving the network a name  // DEPRECATED. See InputParameter. The input blobs to the network.  repeated string input = 3;  // DEPRECATED. See InputParameter. The shape of the input blobs.  repeated BlobShape input_shape = 8;  // 4D input dimensions -- deprecated.  Use "input_shape" instead.  // If specified, for each input blob there should be four  // values specifying the num, channels, height and width of the input blob.  // Thus, there should be a total of (4 * #input) numbers.  repeated int32 input_dim = 4;  // Whether the network will force every layer to carry out backward operation.  // If set False, then whether to carry out backward is determined  // automatically according to the net structure and learning rates.  optional bool force_backward = 5 [default = false];  // The current "state" of the network, including the phase, level, and stage.  // Some layers may be included/excluded depending on this state and the states  // specified in the layers' include and exclude fields.  optional NetState state = 6;  // Print debugging information about results while running Net::Forward,  // Net::Backward, and Net::Update.  optional bool debug_info = 7 [default = false];  // The layers that make up the net.  Each of their configurations, including  // connectivity and behavior, is specified as a LayerParameter.  repeated LayerParameter layer = 100;  // ID 100 so layers are printed last.  // DEPRECATED: use 'layer' instead.  repeated V1LayerParameter layers = 2;}