code: def standardize_images(x):
    
    with tf.name_scope("standardize_images", values=[x]):
      x_shape = shape_list(x)
      x = to_float(tf.reshape(x, [-1] + x_shape[-3:]))
      x_mean = tf.reduce_mean(x, axis=[1, 2], keepdims=True)
      x_variance = tf.reduce_mean(
          tf.squared_difference(x, x_mean), axis=[1, 2], keepdims=True)
      num_pixels = to_float(x_shape[-2] * x_shape[-3])
      x = (x - x_mean) / tf.maximum(tf.sqrt(x_variance), tf.rsqrt(num_pixels))
      return tf.reshape(x, x_shape)
docs: Image standardization on batches and videos.