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问题描述
现在我像
layer {
name: "Convolution1"
type: "Convolution"
bottom: "data"
top: "Convolution1"
convolution_param {
num_output: 20
kernel_size: 5
weight_filler {
type: "xavier"
}
}
}
如何设置全局重量填充物类型?谢谢.
How can I set a global weight filler type? Thanks.
推荐答案
似乎目前没有其他方法可以使用.在 caffe.proto
文件中,NetParameter
的定义如下,其中没有default_weight_filler
之类的选项.
It seems currently there's no other way of doing it. In the caffe.proto
file, the NetParameter
is defined as follows, where there's no such option as default_weight_filler
or so.
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;
}
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