code: def modified_gan(logu, self_normalized=False, name=None):
      """The Modified-GAN 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 modified-GAN (Generative/Adversarial
      Network) Csiszar-function is:
  
      ```none
      f(u) = log(1 + u) - log(u) + 0.5 (u - 1)
      ```
  
      When `self_normalized = False` the `0.5 (u - 1)` is omitted.
  
      The unmodified GAN Csiszar-function is identical to Jensen-Shannon (with
      `self_normalized = False`).
  
      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.
        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:
        chi_square_of_u: `float`-like `Tensor` of the Csiszar-function evaluated
          at `u = exp(logu)`.
      """
  
      with tf.name_scope(name or "chi_square"):
          logu = tf.convert_to_tensor(logu, name="logu")
          y = tf.nn.softplus(logu) - logu
          if self_normalized:
              y += 0.5 * tf.math.expm1(logu)
          return y
  
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 15 for calling a global function with example usage: modified_gan(logu, _normalized, name) and returns: y