tensorflow_probability/python/distributions/gaussian_process.py
def _get_index_points(self, index_points=None):
    """Return `index_points` if not None, else `self._index_points`.

    Args:
      index_points: if given, this is what is returned; else,
      `self._index_points`

    Returns:
      index_points: the given arg, if not None, else the class member
      `self._index_points`.

    Rases:
      ValueError: if `index_points` and `self._index_points` are both `None`.
    """
    if self._index_points is None and index_points is None:
      raise ValueError(
          'This GaussianProcess instance was not instantiated with a value for '
          'index_points. One must therefore be provided when calling sample, '
          'log_prob, and other such methods. In particular, one can\'t compute '
          'KL divergences to/from an instance of `GaussianProccess` with '
          'unspecified `index_points` directly. Instead, use the '
          '`get_marginal_distribution` function, which takes `index_points` as '
          'an argument and returns a `Normal` or '
          '`MultivariateNormalLinearOperator` instance, whose KL can be '
          'computed.')
    return index_points if index_points is not None else self._index_points
def _get_index_points(self, index_points=None):
    """Return `index_points` if not None, else `self._index_points`.

    Args:
      index_points: if given, this is what is returned; else,
      `self._index_points`

    Returns:
      index_points: the given arg, if not None, else the class member
      `self._index_points`.

    Rases:
      ValueError: if `index_points` and `self._index_points` are both `None`.
    """
    if self._index_points is None and index_points is None:
      raise ValueError(
          'This GaussianProcess instance was not instantiated with a value for '
          'index_points. One must therefore be provided when calling sample, '
          'log_prob, and other such methods. In particular, one can\'t compute '
          'KL divergences to/from an instance of `GaussianProccess` with '
          'unspecified `index_points` directly. Instead, use the '
          '`get_marginal_distribution` function, which takes `index_points` as '
          'an argument and returns a `Normal` or '
          '`MultivariateNormalLinearOperator` instance, whose KL can be '
          'computed.')
    return index_points if index_points is not None else self._index_points
Return `index_points` if not None, else `self._index_points`.

    Args:
      index_points: if given, this is what is returned; else,
      `self._index_points`

    Returns:
      index_points: the given arg, if not None, else the class member
      `self._index_points`.

    Rases:
      ValueError: if `index_points` and `self._index_points` are both `None`.