tensorflow_probability/python/vi/csiszar_divergence.py
def jeffreys(logu, name=None):
  """The Jeffreys Csiszar-function in log-space.

  A Csiszar-function is a member of,

  ```none
  F = { f:R_+ to R : f convex }.
  ```

  The Jeffreys Csiszar-function is:

  ```none
  f(u) = 0.5 ( u log(u) - log(u) )
       = 0.5 kl_forward + 0.5 kl_reverse
       = symmetrized_csiszar_function(kl_reverse)
       = symmetrized_csiszar_function(kl_forward)
  ```

  This Csiszar-function induces a symmetric f-Divergence, i.e.,
  `D_f[p, q] = D_f[q, p]`.

  Warning: this function makes non-log-space calculations and may therefore be
  numerically unstable for `|logu| >> 0`.

  Args:
    logu: `float`-like `Tensor` representing `log(u)` from above.
    name: Python `str` name prefixed to Ops created by this function.

  Returns:
    jeffreys_of_u: `float`-like `Tensor` of the Csiszar-function evaluated
      at `u = exp(logu)`.
  """

  with tf.compat.v1.name_scope(name, "jeffreys", [logu]):
    logu = tf.convert_to_tensor(value=logu, name="logu")
    return 0.5 * tf.math.expm1(logu) * logu
def jeffreys(logu, name=None):
  with tf.compat.v1.name_scope(name, "jeffreys", [logu]):
    logu = tf.convert_to_tensor(value=logu, name="logu")
    return 0.5 * tf.math.expm1(logu) * logu
def jeffreys ( logu , name = None ) : with tf . compat . v1 . name_scope ( name , "jeffreys" , [ logu ] ) : logu = tf . convert_to_tensor ( value = logu , name = "logu" ) return 0.5 * tf . math . expm1 ( logu ) * logu
The Jeffreys Csiszar-function in log-space.

  A Csiszar-function is a member of,

  ```none
  F = { f:R_+ to R : f convex }.
  ```

  The Jeffreys Csiszar-function is:

  ```none
  f(u) = 0.5 ( u log(u) - log(u) )
       = 0.5 kl_forward + 0.5 kl_reverse
       = symmetrized_csiszar_function(kl_reverse)
       = symmetrized_csiszar_function(kl_forward)
  ```

  This Csiszar-function induces a symmetric f-Divergence, i.e.,
  `D_f[p, q] = D_f[q, p]`.

  Warning: this function makes non-log-space calculations and may therefore be
  numerically unstable for `|logu| >> 0`.

  Args:
    logu: `float`-like `Tensor` representing `log(u)` from above.
    name: Python `str` name prefixed to Ops created by this function.

  Returns:
    jeffreys_of_u: `float`-like `Tensor` of the Csiszar-function evaluated
      at `u = exp(logu)`.
The Jeffreys Csiszar - function in log - space .