class_docstr: A dataset that provides helpers for batching.
class_docstr_tok: ["A","dataset","that","provides","helpers","for","batching","."]
docstr: Return the number of tokens for a set of positions defined by indices.
  This value is used to enforce ``--max-tokens`` during batching.
docstr_tok: ["Return","the","number","of","tokens","for","a","set","of","positions","defined","by","indices",".","This","value","is","used","to","enforce","``","--","max-tokens","``","during","batching","."]
code: def num_tokens_vec(self, indices):
      """Return the number of tokens for a set of positions defined by indices.
      This value is used to enforce ``--max-tokens`` during batching."""
      raise NotImplementedError
  
imports: import logging
  import numpy
  import torch.utils.data
  from fairseq.data import data_utils
label_desc: Use image node_id 5 for calling the FairseqDataset obj's underlying member method code with example usage: obj.num_tokens_vec(indices) without return types