code: def create_src_lengths_mask(batch_size, src_lengths):
      max_srclen = src_lengths.max()
      src_indices = (
          torch.arange(0, max_srclen).unsqueeze(0).type_as(src_lengths)
      )
      src_indices = src_indices.expand(batch_size, max_srclen)
      src_lengths = src_lengths.unsqueeze(dim=1).expand(
          batch_size, max_srclen
      )
      # returns [batch_size, max_seq_len]
      return (src_indices < src_lengths).int().detach()
  
file_path: translate/pytorch_translate/research/attention/multihead_attention.py
imports: import math
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 1 for calling a global function with example usage: create_src_lengths_mask(batch_size, src_lengths) and returns: unknown