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: Print some statistics on the corpus. Only the master process.
docstr_tok: ["Print","some","statistics","on","the","corpus",".","Only","the","master","process","."]
code: def print_statistics(self):
      """
      Print some statistics on the corpus. Only the master process.
      """
      if not self.params.is_master:
          return
      logger.info(f"{len(self)} sequences")
  
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 8 for calling the LmSeqsDataset obj's underlying member method code with example usage: obj.print_statistics() without return types