class_docstr: BuilderConfig for CelebaHQ.
class_docstr_tok: ["BuilderConfig","for","CelebaHQ","."]
docstr: BuilderConfig for SQUAD.
  
  Args:
    resolution: Resolution of the image. Values supported: powers of 2 up to
      1024.
    **kwargs: keyword arguments forwarded to super.
docstr_tok: ["BuilderConfig","for","SQUAD",".","Args",":","resolution",":","Resolution","of","the","image",".","Values","supported",":","powers","of","2","up","to","1024",".","*","*","kwargs",":","keyword","arguments","forwarded","to","super","."]
code: def __init__(self, *, resolution, **kwargs):
      """BuilderConfig for SQUAD.
  
      Args:
        resolution: Resolution of the image. Values supported: powers of 2 up to
          1024.
        **kwargs: keyword arguments forwarded to super.
      """
      v2 = tfds.core.Version("2.0.0")
      super(CelebaHQConfig, self).__init__(
          name="%d" % resolution,
          description="CelebaHQ images in %d x %d resolution"
          % (resolution, resolution),
          version=v2,
          release_notes={
              "2.0.0": "New split API (https://tensorflow.org/datasets/splits)",
          },
          **kwargs,
      )
      self.resolution = resolution
      self.file_name = "data%dx%d.tar" % (resolution, resolution)
  
file_path: datasets/tensorflow_datasets/datasets/celeb_a_hq/celeb_a_hq_dataset_builder.py
imports: import os
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 to create a new CelebaHQConfig object from inherited base classes: tfds.core with example: obj = CelebaHQConfig()