code: def chi_square(logu, name=None):
      """The chi-Square Csiszar-function in log-space.
  
      A Csiszar-function is a member of,
  
      ```none
      F = { f:R_+ to R : f convex }.
      ```
  
      The Chi-square Csiszar-function is:
  
      ```none
      f(u) = u**2 - 1
      ```
  
      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:
        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")
          return tf.math.expm1(2.0 * logu)
  
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 14 for calling a global function with example usage: chi_square(logu, name) and returns: tf