mse function

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

Implementation

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