class_docstr: DatasetBuilder for grounded_scan dataset.
class_docstr_tok: ["DatasetBuilder","for","grounded_scan","dataset","."]
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      position_feature = tfds.features.FeaturesDict(
          {"row": np.int32, "column": np.int32}
      )
      object_feature = tfds.features.FeaturesDict(
          {
              "vector": tfds.features.Text(),
              "position": position_feature,
              "object": tfds.features.FeaturesDict(
                  {
                      "shape": tfds.features.Text(),
                      "color": tfds.features.Text(),
                      "size": np.int32,
                  }
              ),
          }
      )
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(
              {
                  "situation": tfds.features.FeaturesDict(
                      {
                          "grid_size": np.int32,
                          "agent_position": position_feature,
                          "agent_direction": np.int32,
                          "target_object": object_feature,
                          "distance_to_target": np.int32,
                          "direction_to_target": tfds.features.Text(),
                          "placed_objects": tfds.features.Sequence(
                              object_feature
                          ),
                      }
                  ),
                  "target_commands": tfds.features.Sequence(
                      tfds.features.Text()
                  ),
                  "command": tfds.features.Sequence(
                      tfds.features.Text()
                  ),
                  "meaning": tfds.features.Sequence(
                      tfds.features.Text()
                  ),
                  "verb_in_command": tfds.features.Text(),
                  "manner": tfds.features.Text(),
                  "referred_target": tfds.features.Text(),
              }
          ),
          supervised_keys=None,
          homepage="https://github.com/LauraRuis/groundedSCAN",
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/vision_language/grounded_scan/grounded_scan.py
imports: from __future__ import annotations
  import json
  import os
  from typing import List
  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 GroundedScan obj's underlying member method code with example usage: obj._info() and returns: tfds