code: def get_bias(self, i, j, device):
      i_arange = torch.arange(j - i, j, device=device)
      j_arange = torch.arange(j, device=device)
      bias = -torch.abs(
          j_arange.unsqueeze(0).unsqueeze(0)
          - i_arange.unsqueeze(1).unsqueeze(0)
      )
      return bias
  
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 2 for calling the AlibiPositionalBias obj's underlying member method code with example usage: obj.get_bias(i, j, device) and returns: bias