code: def get_slopes(n):
      def get_slopes_power_of_2(n):
          start = 2 ** (-(2 ** -(math.log2(n) - 3)))
          ratio = start
          return [start * ratio**i for i in range(n)]
  
      if math.log2(n).is_integer():
          slopes = get_slopes_power_of_2(n)
      else:
          closest_power_of_2 = 2 ** math.floor(math.log2(n))
          slopes = (
              get_slopes_power_of_2(closest_power_of_2)
              + get_slopes(2 * closest_power_of_2)[0::2][
                  : n - closest_power_of_2
              ]
          )
  
      return slopes
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/position_embedding/alibi_relative_position_embedding.py
imports: import math
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: get_slopes(n) and returns: slopes, unknown