class_docstr: Generic text translation dataset created from manual directory.
  
  The directory content should be as followed:
  
  ```
  path/to/my_data/
    lang1.train.txt
    lang2.train.txt
    lang1.test.txt
    lang2.test.txt
    ...
  ```
  
  Each files should have one example per line. Line order should match between
  files.
  
  To use it:
  
  ```
  builder = tfds.TranslateFolder(root_dir='path/to/my_data/')
  print(builder.info)  # Splits, num examples,... are automatically calculated
  ds = builder.as_dataset(split='train', shuffle_files=True)
  ```
  
  Note: All examples from all splits are loaded in memory in `__init__`.
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code: def _info(self) -> dataset_info.DatasetInfo:
      return dataset_info.DatasetInfo(
          builder=self,
          description="Generic text translation dataset.",
          features=features_lib.FeaturesDict(
              {lang: features_lib.Text() for lang in self._languages}
          ),
      )
  
imports: from __future__ import annotations
  import collections
  import os
  from typing import Dict, List, Tuple
  from etils import epath
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core.utils import version
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 2 for calling the TranslateFolder obj's underlying member method code with example usage: obj._info() and returns: dataset_info