code: def inverse_tukey_hh(x, hl, hr):
      """Compute the inverse of the Tukey HH function.
  
      The Tukey HH function transforms a standard Gaussian distribution into the
      Tukey HH distribution and it's defined as:
  
      x = u * exp(hl * u ^ 2) for u < 0 and x = u * exp(hr * u ^ 2) for u >= 0.
  
      Given the values of x, this function computes the corresponding values of u.
  
      Args:
        x: The input `Tensor`.
        hl: The "left" parameter of the distribution. It must have the same dtype
          and shape of x (or a broadcastable shape) or be a scalar.
        hr: The "right" parameter of the distribution. It must have the same dtype
          and shape of x (or a broadcastable shape) or be a scalar.
  
      Returns:
        The inverse of the Tukey HH function.
      """
  
      def one_side(x, h):
          h_x_square = tf.multiply(h, tf.square(x))
          return tf.where(
              # Prevents the 0 / 0 form for small values of x..
              tf.less(h_x_square, 1.0e-7),
              x,  # The error is < 1e-14 for this case.
              tf.sqrt(tf.divide(lambert_w(h_x_square), h)),
          )
  
      return tf.where(
          tf.less(x, 0.0), -one_side(-x, hl), one_side(x, hr)
      )
  
file_path: transform/tensorflow_transform/gaussianization.py
imports: import numpy
  import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: inverse_tukey_hh(x, hl, hr) and returns: tf, tf