examples/nerf.py
def huber(x, y, scaling=0.1):
    """
    A helper function for evaluating the smooth L1 (huber) loss
    between the rendered silhouettes and colors.
    """
    diff_sq = (x - y) ** 2
    loss = ((1 + diff_sq / (scaling ** 2)).clamp(1e-4).sqrt() - 1) * float(scaling)
    return loss

    A helper function for evaluating the smooth L1 (huber) loss
    between the rendered silhouettes and colors.
    
A helper function for evaluating the smooth L1 (huber) loss
between the rendered silhouettes and colors.
A helper function for evaluating the smooth L1 ( huber ) loss between the rendered silhouettes and colors .
def huber(x, y, scaling=0.1):
    diff_sq = (x - y) ** 2
    loss = ((1 + diff_sq / (scaling ** 2)).clamp(1e-4).sqrt() - 1) * float(scaling)
    return loss
def huber ( x , y , scaling = 0.1 ) : diff_sq = ( x - y ) ** 2 loss = ( ( 1 + diff_sq / ( scaling ** 2 ) ) . clamp ( 1e-4 ) . sqrt ( ) - 1 ) * float ( scaling ) return loss
A helper function for evaluating the smooth L1 (huber) loss
between the rendered silhouettes and colors.
A helper function for evaluating the smooth L1 ( huber ) loss between the rendered silhouettes and colors .
"""
    A helper function for evaluating the smooth L1 (huber) loss
    between the rendered silhouettes and colors.
    """
x
y
scaling