code: def _log_combinations(n, k):
      """Computes log(Gamma(n+1) / (Gamma(k+1) * Gamma(n-k+1))."""
      return -special.lbeta(k + 1, n - k + 1) - tf.math.log(n + 1)
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  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 reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 1 for calling a global function with example usage: _log_combinations(n, k) and returns: unknown