class_docstr: Memory-mapped text sequence to sequence dataset. Operates pre-tokenized binarized data files.
class_docstr_tok: ["Memory-mapped","text","sequence","to","sequence","dataset",".","Operates","pre-tokenized","binarized","data","files","."]
code: def _get_examples(self):
      self.src_indexed_dataset = self._get_indexed_dataset(
          self.src_dataset_prefix, data_impl="mmap", skip_warmup=True
      )
      self.tgt_indexed_dataset = self._get_indexed_dataset(
          self.tgt_dataset_prefix, data_impl="mmap", skip_warmup=True
      )
      assert len(self.src_indexed_dataset) == len(
          self.tgt_indexed_dataset
      )
      self._build_samples_mapping()
  
imports: import os
  import numpy
  import torch
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.collections.nlp.data.language_modeling.megatron.dataset_utils import get_indexed_dataset_, get_samples_mapping
  from nemo.collections.nlp.data.language_modeling.text_memmap_dataset import TextMemMapDataset
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling the BinarizedMemmapSequenceToSequenceDataset obj's underlying member method code with example usage: obj._get_examples() without return types