(pred: Tensor, target: Tensor, beta: float = 1.0)
return loss
r"""Smooth L1 Loss

    Args:
        pred (Tensor):
            the predictions
        target (Tensor):
            the assigned targets with the same shape as pred
        beta (int):
            the parameter of smooth l1 loss.

    Returns:
        the calculated smooth l1 loss.
r"""Smooth L1 Loss
r Smooth L1 Loss
def smooth_l1_loss(pred: Tensor, target: Tensor, beta: float = 1.0) -> Tensor:
    r"""Smooth L1 Loss

    Args:
        pred (Tensor):
            the predictions
        target (Tensor):
            the assigned targets with the same shape as pred
        beta (int):
            the parameter of smooth l1 loss.

    Returns:
        the calculated smooth l1 loss.
    """
    x = pred - target
    abs_x = F.abs(x)
    if beta < 1e-5:
        loss = abs_x
    else:
        in_loss = 0.5 * x ** 2 / beta
        out_loss = abs_x - 0.5 * beta
        loss = F.where(abs_x < beta, in_loss, out_loss)
    return loss
def smooth_l1_loss ( pred : Tensor , target : Tensor , beta : float = 1.0 ) -> Tensor : x = pred - target abs_x = F . abs ( x ) if beta < 1e-5 : loss = abs_x else : in_loss = 0.5 * x ** 2 / beta out_loss = abs_x - 0.5 * beta loss = F . where ( abs_x < beta , in_loss , out_loss ) return loss