code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--data", type=str, help="prefix to data files"
      )
      parser.add_argument(
          "--dataset-impl",
          type=str,
          default="infer",
          choices=["lazy", "cached", "mmap", "infer"],
      )
      parser.add_argument(
          "--count",
          type=int,
          default=10,
          help="Number of samples/documents to print",
      )
  
      group = parser.add_argument_group(title="tokenizer")
      group.add_argument(
          "--tokenizer-type",
          type=str,
          required=True,
          choices=["BertWordPieceLowerCase", "GPT2BPETokenizer"],
          help="What type of tokenizer to use.",
      )
      group.add_argument(
          "--vocab-file",
          type=str,
          default=None,
          help="Path to the vocab file",
      )
      group.add_argument(
          "--merge-file",
          type=str,
          default=None,
          help="Path to the BPE merge file (if necessary).",
      )
  
      parser.add_argument(
          "--epochs",
          type=int,
          default=5,
          help="Number of epochs to plan for",
      )
      parser.add_argument(
          "--max-num-samples",
          type=int,
          default=None,
          help="Maximum number of samples to plan for",
      )
      parser.add_argument(
          "--masked-lm-prob",
          type=float,
          default=0.15,
          help="probability of masking tokens",
      )
      parser.add_argument(
          "--seq-length",
          type=int,
          default=512,
          help="maximum sequence length",
      )
      parser.add_argument(
          "--short-seq-prob",
          type=float,
          default=0.1,
          help="probability of creating a short sequence",
      )
      parser.add_argument(
          "--seed", type=int, default=1234, help="random seed"
      )
      args = parser.parse_args()
      args.rank = 0
      args.make_vocab_size_divisible_by = 128
      args.tensor_model_parallel_size = 1
  
      if args.dataset_impl == "infer":
          args.dataset_impl = indexed_dataset.infer_dataset_impl(
              args.data
          )
  
      #    test_albert_dataset(args)
      test_indexed_dataset_get(args)
  
file_path: ColossalAI/examples/tutorial/sequence_parallel/data/datasets/test/test_indexed_dataset.py
imports: import argparse
  import os
  import sys
  from megatron.data import indexed_dataset
  from megatron.tokenizer import build_tokenizer
label_desc: Use image node_id 3 for calling a global function with example usage: main() without return types