class_docstr: "Configuration for RoboNet video rescaling.
class_docstr_tok: ["``","Configuration","for","RoboNet","video","rescaling","."]
docstr: The parameters specifying how the dataset will be processed.
  
  The dataset comes with two versions, 1080p and 480p video. Set
  full_resolution to True to load the 1080p version and to False to load the
  480p version.
  
  Args:
    full_resolution: bool, whether to load the 1080p version.
    **kwargs: Passed on to the constructor of `BuilderConfig`.
docstr_tok: ["The","parameters","specifying","how","the","dataset","will","be","processed",".","The","dataset","comes","with","two","versions",",","1080p","and","480p","video",".","Set","full_resolution","to","True","to","load","the","1080p","version","and","to","False","to","load","the","480p","version",".","Args",":","full_resolution",":","bool",",","whether","to","load","the","1080p","version",".","*","*","kwargs",":","Passed","on","to","the","constructor","of","`","BuilderConfig","`","."]
code: def __init__(self, *, full_resolution=False, **kwargs):
      """The parameters specifying how the dataset will be processed.
  
      The dataset comes with two versions, 1080p and 480p video. Set
      full_resolution to True to load the 1080p version and to False to load the
      480p version.
  
      Args:
        full_resolution: bool, whether to load the 1080p version.
        **kwargs: Passed on to the constructor of `BuilderConfig`.
      """
      super(DavisConfig, self).__init__(**kwargs)
      self.full_resolution = full_resolution
  
file_path: datasets/tensorflow_datasets/video/davis/davis.py
imports: from __future__ import annotations
  import numpy
  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 DavisConfig object from inherited base classes: tfds.core with example: obj = DavisConfig()