code: def load_num_sequence_text(
      path: Union[Path, str], loader_type: str = "csv_int"
  ) -> Dict[str, List[Union[float, int]]]:
      """Read a text file indicating sequences of number
  
      Examples:
          key1 1 2 3
          key2 34 5 6
  
          >>> d = load_num_sequence_text('text')
          >>> np.testing.assert_array_equal(d["key1"], np.array([1, 2, 3]))
      """
      assert check_argument_types()
      if loader_type == "text_int":
          delimiter = " "
          dtype = int
      elif loader_type == "text_float":
          delimiter = " "
          dtype = float
      elif loader_type == "csv_int":
          delimiter = ","
          dtype = int
      elif loader_type == "csv_float":
          delimiter = ","
          dtype = float
      else:
          raise ValueError(f"Not supported loader_type={loader_type}")
  
      # path looks like:
      #   utta 1,0
      #   uttb 3,4,5
      # -> return {'utta': np.ndarray([1, 0]),
      #            'uttb': np.ndarray([3, 4, 5])}
      d = read_2columns_text(path)
  
      # Using for-loop instead of dict-comprehension for debuggability
      retval = {}
      for k, v in d.items():
          try:
              retval[k] = [dtype(i) for i in v.split(delimiter)]
          except TypeError:
              logging.error(
                  f'Error happened with path="{path}", id="{k}", value="{v}"'
              )
              raise
      return retval
  
file_path: espnet/espnet2/fileio/read_text.py
imports: import collections.abc
  import logging
  from mmap import mmap
  from pathlib import Path
  from random import randint
  from typing import Dict, List, Optional, Tuple, Union
  from typeguard import check_argument_types
label_desc: Use image node_id 3 for calling a global function with example usage: load_num_sequence_text(path, loader_type) and returns: retval