mse function

Tensor<Scalar> mse(Tensor<Vector> predictions, Tensor<Vector> targets)

Implementation

Tensor<Scalar> mse(Tensor<Vector> predictions, Tensor<Vector> targets) {
  int N = predictions.data.length;
  double sumSquaredError = 0.0;
  for (int i = 0; i < N; i = i + 1) {
    double error = predictions.data[i] - targets.data[i];
    sumSquaredError = sumSquaredError + (error * error);
  }
  Tensor<Scalar> out = Tensor<Scalar>(sumSquaredError / N);
  out.creator = Node(
    [predictions, targets],
        () {
      for (int i = 0; i < N; i = i + 1) {
        predictions.grad[i] = predictions.grad[i] +
            out.grad[0] * (2.0 * (predictions.data[i] - targets.data[i])) / N;
      }
    },
    opName: 'mse_vector',
    cost: 3 * N,
  );
  return out;
}