mseMatrix function

Tensor<Scalar> mseMatrix(
  1. Tensor<Matrix> predictions,
  2. Tensor<Matrix> targets
)

Implementation

Tensor<Scalar> mseMatrix(Tensor<Matrix> predictions, Tensor<Matrix> targets) {
  int length = predictions.data.length;
  double sumSquaredError = 0.0;

  for (int i = 0; i < length; i = i + 1) {
    double error = predictions.data[i] - targets.data[i];
    sumSquaredError = sumSquaredError + (error * error);
  }

  Tensor<Scalar> out = Tensor<Scalar>(sumSquaredError / length);

  out.creator = Node(
    [predictions, targets],
        () {
      double factor = 2.0 / length;
      double outGrad = out.grad[0];
      for (int i = 0; i < length; i = i + 1) {
        predictions.grad[i] = predictions.grad[i] +
            outGrad * factor * (predictions.data[i] - targets.data[i]);
      }
    },
    opName: 'mse_matrix',
    cost: 3 * length,
  );
  return out;
}