tensorflow_probability/python/distributions/lkj.py
def _log_normalization(self, name='log_normalization'):
    """Returns the log normalization of an LKJ distribution.

    Args:
      name: Python `str` name prefixed to Ops created by this function.

    Returns:
      log_z: A Tensor of the same shape and dtype as `concentration`, containing
        the corresponding log normalizers.
    """
    # The formula is from D. Lewandowski et al [1], p. 1999, from the
    # proof that eqs 16 and 17 are equivalent.
    with tf.name_scope(name or 'log_normalization_lkj'):
      logpi = np.log(np.pi)
      ans = tf.zeros_like(self.concentration)
      for k in range(1, self.dimension):
        ans += logpi * (k / 2.)
        ans += tf.math.lgamma(self.concentration +
                              (self.dimension - 1 - k) / 2.)
        ans -= tf.math.lgamma(self.concentration + (self.dimension - 1) / 2.)
      return ans
def _log_normalization(self, name='log_normalization'):
    """Returns the log normalization of an LKJ distribution.

    Args:
      name: Python `str` name prefixed to Ops created by this function.

    Returns:
      log_z: A Tensor of the same shape and dtype as `concentration`, containing
        the corresponding log normalizers.
    """
    # The formula is from D. Lewandowski et al [1], p. 1999, from the
    # proof that eqs 16 and 17 are equivalent.
    with tf.name_scope(name or 'log_normalization_lkj'):
      logpi = np.log(np.pi)
      ans = tf.zeros_like(self.concentration)
      for k in range(1, self.dimension):
        ans += logpi * (k / 2.)
        ans += tf.math.lgamma(self.concentration +
                              (self.dimension - 1 - k) / 2.)
        ans -= tf.math.lgamma(self.concentration + (self.dimension - 1) / 2.)
      return ans
Returns the log normalization of an LKJ distribution.

    Args:
      name: Python `str` name prefixed to Ops created by this function.

    Returns:
      log_z: A Tensor of the same shape and dtype as `concentration`, containing
        the corresponding log normalizers.