class_docstr: DatasetBuilder for wiki_auto dataset.
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
  
      if self.builder_config.name == "manual":
          features = tfds.features.FeaturesDict(
              {
                  "alignment_label": tfds.features.ClassLabel(
                      names=["notAligned", "aligned", "partialAligned"]
                  ),
                  "normal_sentence_id": tfds.features.Text(),
                  "simple_sentence_id": tfds.features.Text(),
                  "normal_sentence": tfds.features.Text(),
                  "simple_sentence": tfds.features.Text(),
                  "GLEU-score": np.float64,
              }
          )
      elif (
          self.builder_config.name == "auto_acl"
          or self.builder_config.name == "auto_full_no_split"
          or self.builder_config.name == "auto_full_with_split"
      ):
          features = tfds.features.FeaturesDict(
              {
                  "normal_sentence": tfds.features.Text(),
                  "simple_sentence": tfds.features.Text(),
              }
          )
      else:
          features = tfds.features.FeaturesDict(
              {
                  "example_id": tfds.features.Text(),
                  "normal": {
                      "normal_article_id": np.int32,
                      "normal_article_title": tfds.features.Text(),
                      "normal_article_url": tfds.features.Text(),
                      "normal_article_content": tfds.features.Sequence(
                          {
                              "normal_sentence_id": tfds.features.Text(),
                              "normal_sentence": tfds.features.Text(),
                          }
                      ),
                  },
                  "simple": {
                      "simple_article_id": np.int32,
                      "simple_article_title": tfds.features.Text(),
                      "simple_article_url": tfds.features.Text(),
                      "simple_article_content": tfds.features.Sequence(
                          {
                              "simple_sentence_id": tfds.features.Text(),
                              "simple_sentence": tfds.features.Text(),
                          }
                      ),
                  },
                  "paragraph_alignment": tfds.features.Sequence(
                      {
                          "normal_paragraph_id": tfds.features.Text(),
                          "simple_paragraph_id": tfds.features.Text(),
                      }
                  ),
                  "sentence_alignment": tfds.features.Sequence(
                      {
                          "normal_sentence_id": tfds.features.Text(),
                          "simple_sentence_id": tfds.features.Text(),
                      }
                  ),
              }
          )
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=features,
          supervised_keys=None,
          homepage="https://github.com/chaojiang06/wiki-auto",
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/text_simplification/wiki_auto/wiki_auto.py
imports: import json
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the WikiAuto obj's underlying member method code with example usage: obj._info() and returns: tfds