docstr: Args:
      iso_lang_map
      min_len: Minimum text length in *chars* for a given example to be included.
  
  Returns:
      Sequence of (text, lang) examples.
docstr_tok: ["Args",":","iso_lang_map","min_len",":","Minimum","text","length","in","*","chars","*","for","a","given","example","to","be","included",".","Returns",":","Sequence","of","(","text",",","lang",")","examples","."]
code: def load(
      self,
      iso_lang_map: Dict[str, str],
      min_len: int = 25,
  ) -> List[Tuple[str, str]]:
      """
      Args:
          iso_lang_map
          min_len: Minimum text length in *chars* for a given example to be included.
  
      Returns:
          Sequence of (text, lang) examples.
      """
      rows = tio.read_csv(
          self.data_dir.joinpath("sentences.csv"),
          fieldnames=["sent_id", "iso-639-3", "text"],
          delimiter="\t",
          quoting=1,
      )
      data = [
          (row["text"], iso_lang_map[row["iso-639-3"]])
          for row in rows
          if row["iso-639-3"] in iso_lang_map
          and itertoolz.count(
              char for char in row["text"] if char.isalnum()
          )
          >= min_len
      ]
      LOGGER.info("loaded TatoebaDataset data:\n%s ...", data[:3])
      return data
  
imports: from __future__ import annotations
  import logging
  import operator
  import pathlib
  import random
  import re
  from typing import Dict, Iterable, List, Optional, Set, Tuple
  from cytoolz import itertoolz
  import textacy
  import textacy.utils
  from textacy import io
label_desc: Use image node_id 3 for calling the TatoebaDataset obj's underlying member method code with example usage: obj.load(iso_lang_map, min_len) and returns: data