fnn_model.proto

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syntax = "proto2";
 
message Vector {
  repeated double columns = 1;
}
 
message Matrix {
  repeated Vector rows = 1;
}
 
message Layer {
  enum ActivationFunc {
    RELU = 0;
    TANH = 1;
    SIGMOID = 2;
    SOFTMAX = 3;
  }
  optional int32 layer_input_dim = 1;
  optional int32 layer_output_dim = 2;
  optional Matrix layer_input_weight =
      3;  // weight matrix of |input_dim| x |output_dim|
  optional Vector layer_bias = 4;  // vector of bias, size of |output_dim|
  optional ActivationFunc layer_activation_func = 5;
}
 
message FnnModel {
  optional int32 dim_input = 1;
  optional Vector samples_mean = 2;
  optional Vector samples_std = 3;
  optional int32 num_layer = 4;
  repeated Layer layer =
      5;  // num_layer must equal to first layer layer_input_dim
  optional int32 dim_output =
      6;  // dim_ouput must equal to last layer layer_output_dim
}