dropoutVectorMath function

Tensor<Vector> dropoutVectorMath(Tensor<Vector> input, double rate, bool isTraining)

Implementation

Tensor<Vector> dropoutVectorMath(Tensor<Vector> input, double rate, bool isTraining) {
  if (isTraining == false || rate == 0.0) {
    return input;
  }

  double scale = 1.0 / (1.0 - rate);
  Random random = Random();
  int length = input.data.length;

  Vector outputValue = [];
  List<bool> mask = [];

  for (int i = 0; i < length; i = i + 1) {
    if (random.nextDouble() < rate) {
      outputValue.add(0.0);
      mask.add(false);
    } else {
      outputValue.add(input.data[i] * scale);
      mask.add(true);
    }
  }

  Tensor<Vector> out = Tensor<Vector>(outputValue);

  out.creator = Node(
    [input],
        () {
      for (int i = 0; i < length; i = i + 1) {
        if (mask[i]) {
          input.grad[i] = input.grad[i] + out.grad[i] * scale;
        }
      }
    },
    opName: 'dropout_vector',
    cost: length,
  );

  return out;
}