class_docstr: Imagenette TFDS dataset.
  
  See https://www.tensorflow.org/datasets/catalog/imagenette for details.
  Images are at low quality and by default load 100 examples from the validation
  set though this can be changed through the `split` parameter, as per TFDS
  documentation.
code: def spec(self) -> lit_types.Spec:
      return {
          "image": lit_types.ImageBytes(),
      }
  
file_path: lit/lit_nlp/examples/datasets/imagenette.py
imports: from lit_nlp.api import dataset
  from lit_nlp.api import types
  from lit_nlp.lib import image_utils
  from PIL import Image
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the ImagenetteDataset obj's underlying member method code with example usage: obj.spec() and returns: dict