class_docstr: DatasetBuilder for controlled_noisy_web_labels dataset.
class_docstr_tok: ["DatasetBuilder","for","controlled_noisy_web_labels","dataset","."]
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      features = {}
      features["image"] = tfds.features.Image()
      features["label"] = tfds.features.ClassLabel(
          num_classes=self.builder_config.num_classes
      )
      features["is_clean"] = tfds.features.Tensor(
          shape=(), dtype=np.bool_
      )
      features["id"] = tfds.features.Text()
  
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(features),
          # If there's a common (input, target) tuple from the
          # features, specify them here. They'll be used if
          # `as_supervised=True` in `builder.as_dataset`.
          supervised_keys=(
              "image",
              "label",
          ),  # Set to `None` to disable
          homepage=(
              "https://google.github.io/controlled-noisy-web-labels/index.html"
          ),
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/image_classification/controlled_noisy_web_labels/controlled_noisy_web_labels.py
imports: import csv
  import dataclasses
  import io
  import json
  import os
  from etils import epath
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 4 for calling the ControlledNoisyWebLabels obj's underlying member method code with example usage: obj._info() and returns: tfds