code: def blend(image1, image2, factor):
      """Blend image1 and image2 using 'factor'.
  
      A value of factor 0.0 means only image1 is used.
      A value of 1.0 means only image2 is used.  A value between 0.0 and
      1.0 means we linearly interpolate the pixel values between the two
      images.  A value greater than 1.0 "extrapolates" the difference
      between the two pixel values, and we clip the results to values
      between 0 and 255.
  
      Args:
        image1: An image Tensor.
        image2: An image Tensor.
        factor: A floating point value above 0.0.
  
      Returns:
        A blended image Tensor.
      """
      image1 = tf.cast(image1, tf.float32)
      image2 = tf.cast(image2, tf.float32)
      return tf.saturate_cast(
          image1 + factor * (image2 - image1), tf.uint8
      )
  
imports: import math
  import tensorflow
  import tensorflow_addons
label_desc: Use image node_id 1 for calling a global function with example usage: blend(image1, image2, factor) and returns: tf