class_docstr: `FeatureConnector` for translations with fixed languages per example.
  Here for compatiblity with tfds.
  
  Args:
      languages (`dict`):
          A dictionary for each example mapping string language codes to string translations.
  
  Example:
  
  ```python
  >>> # At construction time:
  >>> datasets.features.Translation(languages=['en', 'fr', 'de'])
  >>> # During data generation:
  >>> yield {
  ...         'en': 'the cat',
  ...         'fr': 'le chat',
  ...         'de': 'die katze'
  ... }
  ```
class_docstr_tok: ["`","FeatureConnector","`","for","translations","with","fixed","languages","per","example",".","Here","for","compatiblity","with","tfds",".","Args",":","languages","(","`","dict","`",")",":","A","dictionary","for","each","example","mapping","string","language","codes","to","string","translations",".","Example",":","``","`","python",">",">",">","#","At","construction","time",":",">",">",">","datasets.features.Translation","(","languages=","[","'en","'",",","'fr","'",",","'de","'","]",")",">",">",">","#","During","data","generation",":",">",">",">","yield","{","...","'en","'",":","'the","cat","'",",","...","'fr","'",":","'le","chat","'",",","...","'de","'",":","'die","katze'","...","}","``","`"]
docstr: Flatten the Translation feature into a dictionary.
docstr_tok: ["Flatten","the","Translation","feature","into","a","dictionary","."]
code: def flatten(self) -> Union["FeatureType", Dict[str, "FeatureType"]]:
      """Flatten the Translation feature into a dictionary."""
      from .features import Value
  
      return {k: Value("string") for k in sorted(self.languages)}
  
file_path: datasets/src/datasets/features/translation.py
imports: from dataclasses import dataclass, field
  from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
  import pyarrow
label_desc: Use image node_id 2 for calling the Translation obj's underlying member method code with example usage: obj.flatten() and returns: unknown