def huber(y_true, y_pred, d):
if not isinstance(y_true, R.Tensor):
y_true = R.Tensor(y_true)
if not isinstance(y_pred, R.Tensor):
y_pred = R.Tensor(y_pred)
d = R.Scalar(d)
x = R.sub(y_true, y_pred)
if R.abs(x) <= d:
return R.elemul(R.Scalar(d), R.elemul(x, x))
if R.abs(x) > d:
return R.add(R.elemul(R.Scalar(d), R.mul(d, d)), R.elemul(d, R.sub(R.abs(x), d)))
def mean_absolute_error(y_true, y_pred):
"""
Mean Absolute Error
"""
if not isinstance(y_true, R.Tensor):
y_true = R.Tensor(y_true)
if not isinstance(y_pred, R.Tensor):
y_pred = R.Tensor(y_pred)
return R.mean(R.abs(R.sub(y_pred, y_true)))