code: def kl_reverse(logu, self_normalized=False, name=None):
      """The reverse Kullback-Leibler Csiszar-function in log-space.
  
      A Csiszar-function is a member of,
  
      ```none
      F = { f:R_+ to R : f convex }.
      ```
  
      When `self_normalized = True`, the KL-reverse Csiszar-function is:
  
      ```none
      f(u) = -log(u) + (u - 1)
      ```
  
      When `self_normalized = False` the `(u - 1)` term is omitted.
  
      Observe that as an f-Divergence, this Csiszar-function implies:
  
      ```none
      D_f[p, q] = KL[q, p]
      ```
  
      The KL is "reverse" because in maximum likelihood we think of minimizing `q`
      as in `KL[p, q]`.
  
      Warning: when self_normalized = True` 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.
        self_normalized: Python `bool` indicating whether `f'(u=1)=0`. When
          `f'(u=1)=0` the implied Csiszar f-Divergence remains non-negative even
          when `p, q` are unnormalized measures.
        name: Python `str` name prefixed to Ops created by this function.
  
      Returns:
        kl_reverse_of_u: `float`-like `Tensor` of the Csiszar-function evaluated at
          `u = exp(logu)`.
  
      Raises:
        TypeError: if `self_normalized` is `None` or a `Tensor`.
      """
  
      with tf.name_scope(name or "kl_reverse"):
          return amari_alpha(
              logu, alpha=0.0, self_normalized=self_normalized
          )
  
imports: import enum
  import functools
  import warnings
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python import monte_carlo
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal.reparameterization import FULLY_REPARAMETERIZED
  from tensorflow_probability.python.stats.leave_one_out import log_soomean_exp
  from tensorflow.python.util import deprecation
label_desc: Use image node_id 3 for calling a global function with example usage: kl_reverse(logu, _normalized, name) and returns: amari_alpha