code: def create_make_unique(inputs):
      """Replaces the lower bits of each element with iota."""
      if inputs.shape.ndims != 2:
          raise ValueError(
              "Input of top_k_with_unique must be rank-2 "
              "but got: %s" % inputs.shape
          )
  
      height = inputs.shape[0]
      width = inputs.shape[1]
      zeros = tf.zeros([height, width], dtype=tf.int32)
  
      log2_ceiling = int(math.ceil(math.log(int(width), 2)))
      next_power_of_two = 1 << log2_ceiling
      count_mask = ~(next_power_of_two - 1)
      count_mask_r0 = tf.constant(count_mask)
      count_mask_r2 = tf.fill([height, width], count_mask_r0)
  
      smallest_normal = 1 << 23
      smallest_normal_r0 = tf.constant(smallest_normal, dtype=tf.int32)
      smallest_normal_r2 = tf.fill([height, width], smallest_normal_r0)
  
      low_bit_mask = ~(1 << 31)
      low_bit_mask_r0 = tf.constant(low_bit_mask, dtype=tf.int32)
      low_bit_mask_r2 = tf.fill([height, width], low_bit_mask_r0)
  
      iota = tf.tile(
          tf.expand_dims(tf.range(width, dtype=tf.int32), 0),
          [height, 1],
      )
  
      input_r2 = tf.bitcast(inputs, tf.int32)
      abs_r2 = tf.bitwise.bitwise_and(input_r2, low_bit_mask_r2)
      if_zero_r2 = tf.equal(abs_r2, zeros)
      smallest_normal_preserving_sign_r2 = tf.bitwise.bitwise_or(
          input_r2, smallest_normal_r2
      )
      input_no_zeros_r2 = tf.where(
          if_zero_r2, smallest_normal_preserving_sign_r2, input_r2
      )
  
      and_r2 = tf.bitwise.bitwise_and(input_no_zeros_r2, count_mask_r2)
      or_r2 = tf.bitwise.bitwise_or(and_r2, iota)
      return tf.bitcast(or_r2, tf.float32)
  
file_path: delta/delta/layers/utils_tf.py
imports: import math
  import numpy
  import tensorflow
  from tensorflow.python.util import nest
label_desc: Use image node_id 8 for calling a global function with example usage: create_make_unique(inputs) and returns: tf