code: def _get_slopes(heads):
      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(heads).is_integer():
          return get_slopes_power_of_2(heads)
      closest_power_of_2 = 2 ** math.floor(math.log2(heads))
  
      return (
          get_slopes_power_of_2(closest_power_of_2)
          + get_slopes_power_of_2(2 * closest_power_of_2)[0::2][
              : heads - closest_power_of_2
          ]
      )
  
file_path: OpenNMT-py/onmt/modules/alibi_position_bias.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the AlibiPositionalBias obj's underlying member method code with example usage: obj._get_slopes(heads) and returns: unknown, unknown, get_slopes_power_of_2