code: def _log_unnormalized_prob_logits(logits, counts, total_count):
      """Log unnormalized probability from logits."""
      logits = tf.convert_to_tensor(logits)
      # softplus(x) = log(1 + exp(x))
      # sigmoid(x) = 1 / (1 + exp(-x)) = exp(x) / (exp(x) + 1)
      # log(probs) = log(sigmoid(logits))
      #            = -log(1 + exp(-logits))
      #            = -softplus(-logits)
      # log1p(-probs) = log(1 - sigmoid(logits))
      #               = log(1 - 1 / (1 + exp(-logits)))
      #               = log((1 + exp(-logits) - 1) / (1 + exp(-logits)))
      #               = log(exp(-logits) / (1 + exp(-logits)))
      #               = log(sigmoid(-logits))
      #               = -softplus(logits)  # by log(sigmoid(x)) = -softplus(-x))
      return -tf.math.multiply_no_nan(
          tf.math.softplus(-logits), counts
      ) - tf.math.multiply_no_nan(
          tf.math.softplus(logits), total_count - counts
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import batched_rejection_sampler
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  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.internal import tensorshape_util
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 8 for calling a global function with example usage: _log_unnormalized_prob_logits(logits, counts, total_count) and returns: unknown