class_docstr: "Configuration for UCF101 split and possible video rescaling.
docstr: The parameters specifying how the dataset will be processed.
  
  The dataset comes with three separate splits. You can specify which split
  you want in `split_number`. If `width` and `height` are set, the videos
  will be rescaled to have those heights and widths (using ffmpeg).
  
  Args:
    split_number: The split number, one of (1, 2, 3)
    width: An integer with the width or None.
    height: An integer with the height or None.
    **kwargs: Passed on to the constructor of `BuilderConfig`.
code: def __init__(
      self, *, split_number, width=None, height=None, **kwargs
  ):
      """The parameters specifying how the dataset will be processed.
  
      The dataset comes with three separate splits. You can specify which split
      you want in `split_number`. If `width` and `height` are set, the videos
      will be rescaled to have those heights and widths (using ffmpeg).
  
      Args:
        split_number: The split number, one of (1, 2, 3)
        width: An integer with the width or None.
        height: An integer with the height or None.
        **kwargs: Passed on to the constructor of `BuilderConfig`.
      """
      super(Ucf101Config, self).__init__(
          version=tfds.core.Version("2.0.0"),
          release_notes={
              "2.0.0": "New split API (https://tensorflow.org/datasets/splits)",
          },
          **kwargs,
      )
      if (width is None) ^ (height is None):
          raise ValueError(
              "Either both dimensions should be set, or none of them"
          )
      self.width = width
      self.height = height
      if split_number not in (1, 2, 3):
          raise ValueError(
              "Unknown split number {}, should be 1, 2 or 3".format(
                  split_number
              )
          )
      self.split_number = split_number
  
file_path: datasets/tensorflow_datasets/video/ucf101.py
imports: import os
  from absl import logging
  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 Ucf101Config object from inherited base classes: tfds.core with example: obj = Ucf101Config()