src/lstm/series.cpp
int Series::InitWeights(float range, TRand *randomizer) {
  num_weights_ = 0;
  tprintf("Num outputs,weights in Series:\n");
  for (auto &i : stack_) {
    int weights = i->InitWeights(range, randomizer);
    tprintf("  %s:%d, %d\n", i->spec().c_str(), i->NumOutputs(), weights);
    num_weights_ += weights;
  }
  tprintf("Total weights = %d\n", num_weights_);
  return num_weights_;
}
// Sets up the network for training. Initializes weights using weights of
// scale `range` picked according to the random number generator `randomizer`.
// Note that series has its own implementation just for debug purposes.
Sets up the network for training. Initializes weights using weights of
scale `range` picked according to the random number generator `randomizer`.
Note that series has its own implementation just for debug purposes.
Sets up the network for training . Initializes weights using weights of scale ` range ` picked according to the random number generator ` randomizer ` . Note that series has its own implementation just for debug purposes .
int Series::InitWeights(float range, TRand *randomizer) {
  num_weights_ = 0;
  tprintf("Num outputs,weights in Series:\n");
  for (auto &i : stack_) {
    int weights = i->InitWeights(range, randomizer);
    tprintf("  %s:%d, %d\n", i->spec().c_str(), i->NumOutputs(), weights);
    num_weights_ += weights;
  }
  tprintf("Total weights = %d\n", num_weights_);
  return num_weights_;
}
int Series :: InitWeights ( float range , TRand * randomizer ) { num_weights_ = 0 ; tprintf ( " \n " ) ; for ( auto & i : stack_ ) { int weights = i -> InitWeights ( range , randomizer ) ; tprintf ( " \n " , i -> spec ( ) . c_str ( ) , i -> NumOutputs ( ) , weights ) ; num_weights_ += weights ; } tprintf ( " \n " , num_weights_ ) ; return num_weights_ ; }
Sets up the network for training.
Sets up the network for training .