class_docstr: So2SAT remote sensing dataset.
class_docstr_tok: ["So2SAT","remote","sensing","dataset","."]
code: def _info(self):
      if self.builder_config.selection == "rgb":
          features = tfds.features.FeaturesDict(
              {
                  "image": tfds.features.Image(shape=[32, 32, 3]),
                  "label": tfds.features.ClassLabel(names=_LABELS),
                  "sample_id": tfds.features.Tensor(
                      shape=(), dtype=np.int64
                  ),
              }
          )
          supervised_keys = ("image", "label")
      elif self.builder_config.selection == "all":
          features = tfds.features.FeaturesDict(
              {
                  "sentinel1": tfds.features.Tensor(
                      shape=[32, 32, 8], dtype=np.float32
                  ),
                  "sentinel2": tfds.features.Tensor(
                      shape=[32, 32, 10], dtype=np.float32
                  ),
                  "label": tfds.features.ClassLabel(names=_LABELS),
                  "sample_id": tfds.features.Tensor(
                      shape=(), dtype=np.int64
                  ),
              }
          )
          supervised_keys = None
      return self.dataset_info_from_configs(
          features=features,
          supervised_keys=supervised_keys,
          homepage="http://doi.org/10.14459/2018MP1454690",
      )
  
file_path: datasets/tensorflow_datasets/datasets/so2sat/so2sat_dataset_builder.py
imports: import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Builder obj's underlying member method code with example usage: obj._info() and returns: self