Class Version

tensorflow_datasets/core/utils/version.py:127–241

Dataset version MAJOR.MINOR.PATCH.

class Version:
  """Dataset version MAJOR.MINOR.PATCH."""

  _DEFAULT_EXPERIMENTS = {
      Experiment.DUMMY: False,
  }

  def __init__(
      self,
      version: VersionOrStr,
      experiments=None,
      tfds_version_to_prepare=None,
  ):
    """Version init.

    Args:
      version: string. Eg: "1.2.3".
      experiments: dict of experiments. See Experiment.
      tfds_version_to_prepare: string, defaults to None. If set, indicates that
        current version of TFDS cannot be used to `download_and_prepare` the
        dataset, but that TFDS at version {tfds_version_to_prepare} should be
        used instead.
    """
    if isinstance(version, Version):
      version_str = str(version)
      experiments = experiments or version._experiments
      tfds_version_to_prepare = (
          tfds_version_to_prepare or version.tfds_version_to_prepare
      )
    else:
      version_str = version
    self._experiments = self._DEFAULT_EXPERIMENTS.copy()
    self.tfds_version_to_prepare = tfds_version_to_prepare
    if experiments:
      if isinstance(experiments, str):
        raise ValueError(
            f"Invalid Version('{version}', '{experiments}'). Description is "
            "deprecated. RELEASE_NOTES should be used instead."
        )
      self._experiments.update(experiments)
    self.major, self.minor, self.patch = _str_to_version(version_str)

  def implements(self, experiment):
    """Returns True if version implements given experiment."""
    return self._experiments[experiment]

  def __str__(self):
    return "{}.{}.{}".format(*self.tuple)

  def __repr__(self) -> str:
    return f"{type(self).__name__}('{str(self)}')"

  @property
  def tuple(self):
    return self.major, self.minor, self.patch

  def _validate_operand(self, other):
    if isinstance(other, str):