def eqalize_lr_bias(b, lr_multiplier=1):
    """
    Equalize learning rates for bias in a layer.
    Args: 
        b: bias. shape: [fmaps_out]
        lr_multiplier: learning rate multiplier
    Returns:
        scaled bias
    """
    gain = lr_multiplier
    b *= gain
    return b