code: def to_valid_rgb(t, decorrelate=False, sigmoid=True):
    
    if decorrelate:
      t = _linear_decorelate_color(t)
    if decorrelate and not sigmoid:
      t += color_mean
    if sigmoid:
      return tf.nn.sigmoid(t)
    else:
      return constrain_L_inf(2*t-1)/2 + 0.5
docs: Transform inner dimension of t to valid rgb colors.
    
    In practice this consistes of two parts: 
    (1) If requested, transform the colors from a decorrelated color space to RGB.
    (2) Constrain the color channels to be in [0,1], either using a sigmoid
        function or clipping.
    
    Args:
      t: input tensor, innermost dimension will be interpreted as colors
        and transformed/constrained.
      decorrelate: should the input tensor's colors be interpreted as coming from
        a whitened space or not?
      sigmoid: should the colors be constrained using sigmoid (if True) or
        clipping (if False).
    
    Returns:
      t with the innermost dimension transformed.