code: def to_valid_rgb(t, decorrelate=False, sigmoid=True):
      """Transform inner dimension of t to valid rgb colors.
  
      In practice this consists 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.
      """
      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
  
imports: import numpy
  import tensorflow
  from lucid.optvis.param.unit_balls import constrain_L_inf
label_desc: Use image node_id 2 for calling a global function with example usage: to_valid_rgb(t, decorrelate, sigmoid) and returns: tf, unknown