code: def _harmonic_number(x):
      """Compute the harmonic number from its analytic continuation.
  
      Derivation from [here](
      https://en.wikipedia.org/wiki/Digamma_function#Relation_to_harmonic_numbers)
      and [Euler's constant](
      https://en.wikipedia.org/wiki/Euler%E2%80%93Mascheroni_constant).
  
      Args:
        x: input float.
  
      Returns:
        z: The analytic continuation of the harmonic number for the input.
      """
      one = tf.ones([], dtype=x.dtype)
      return tf.math.digamma(x + one) - tf.math.digamma(one)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import kumaraswamy_cdf
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 1 for calling a global function with example usage: _harmonic_number(x) and returns: unknown