class_docstr: Split the vocabulary into `world_size` chunks and return the
  first and last index of the vocabulary belonging to the `rank`
  partition: Note that indices in [fist, last)
class_docstr_tok: ["Split","the","vocabulary","into","`","world_size","`","chunks","and","return","the","first","and","last","index","of","the","vocabulary","belonging","to","the","`","rank","`","partition",":","Note","that","indices","in","[","fist",",","last",")"]
code: def vocab_range_from_global_vocab_size(
      global_vocab_size: int, rank: int, world_size: int
  ) -> Sequence[int]:
      per_partition_vocab_size = divide(global_vocab_size, world_size)
      return VocabUtility.vocab_range_from_per_partition_vocab_size(
          per_partition_vocab_size, rank, world_size
      )
  
imports: from typing import List, Sequence
  import torch
  from apex.transformer.utils import divide
label_desc: Use image node_id 2 for calling the VocabUtility obj's underlying member method code with example usage: obj.vocab_range_from_global_vocab_size(global_vocab_size, rank, world_size) and returns: VocabUtility