class_docstr: Custom Dataset wrapping language modeling sequences.
  
  Each sample will be retrieved by indexing the list of token_ids and their corresponding lengths.
  
  Input:
  ------
      params: `NameSpace` parameters
      data: `List[np.array[int]]
docstr: Some sanity checks
docstr_tok: ["Some","sanity","checks"]
code: def check(self):
      """
      Some sanity checks
      """
      assert len(self.token_ids) == len(self.lengths)
      assert all(
          self.lengths[i] == len(self.token_ids[i])
          for i in range(len(self.lengths))
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/distillation/lm_seqs_dataset.py
imports: import numpy
  import torch
  from torch.utils.data import Dataset
  from utils import logger
label_desc: Use image node_id 4 for calling the LmSeqsDataset obj's underlying member method code with example usage: obj.check() without return types