class_docstr: Class to keep track of information on a sub-dataset of WMT.
docstr: Sub-dataset of WMT.
  
  Args:
    name: `string`, a unique dataset identifier.
    target: `string`, the target language code.
    sources: `set<string>`, the set of source language codes.
    url: `string` or `(string, string)`, URL(s) or URL template(s) specifying
      where to download the raw data from. If two strings are provided, the
      first is used for the source language and the second for the target.
      Template strings can either contain '{src}' placeholders that will be
      filled in with the source language code, '{0}' and '{1}' placeholders
      that will be filled in with the source and target language codes in
      alphabetical order, or all 3.
    path: `string` or `(string, string)`, path(s) or path template(s)
      specifing the path to the raw data relative to the root of the
      downloaded archive. If two strings are provided, the dataset is assumed
      to be made up of parallel text files, the first being the source and the
      second the target. If one string is provided, both languages are assumed
      to be stored within the same file and the extension is used to determine
      how to parse it. Template strings should be formatted the same as in
      `url`.
    manual_dl_files: `<list>(string)` (optional), the list of files that must
      be manually downloaded to the data directory.
code: def __init__(
      self, name, target, sources, url, path, manual_dl_files=None
  ):
      """Sub-dataset of WMT.
  
      Args:
        name: `string`, a unique dataset identifier.
        target: `string`, the target language code.
        sources: `set<string>`, the set of source language codes.
        url: `string` or `(string, string)`, URL(s) or URL template(s) specifying
          where to download the raw data from. If two strings are provided, the
          first is used for the source language and the second for the target.
          Template strings can either contain '{src}' placeholders that will be
          filled in with the source language code, '{0}' and '{1}' placeholders
          that will be filled in with the source and target language codes in
          alphabetical order, or all 3.
        path: `string` or `(string, string)`, path(s) or path template(s)
          specifing the path to the raw data relative to the root of the
          downloaded archive. If two strings are provided, the dataset is assumed
          to be made up of parallel text files, the first being the source and the
          second the target. If one string is provided, both languages are assumed
          to be stored within the same file and the extension is used to determine
          how to parse it. Template strings should be formatted the same as in
          `url`.
        manual_dl_files: `<list>(string)` (optional), the list of files that must
          be manually downloaded to the data directory.
      """
      self._paths = (path,) if isinstance(path, str) else path
      self._urls = (url,) if isinstance(url, str) else url
      self._manual_dl_files = manual_dl_files if manual_dl_files else []
      self.name = name
      self.target = target
      self.sources = set(sources)
  
imports: import codecs
  import functools
  import gzip
  import itertools
  import os
  import re
  from typing import List
  from xml.etree import ElementTree
  from absl import logging
  from etils import epath
  from tensorflow_datasets.core.utils import tree_utils
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 to create a new SubDataset object from inherited base classes: object with example: obj = SubDataset(name, target, sources, url, path, manual_dl_files)