code: def test_sum_vs_mean(self):
      logx_ = np.float32([[0.0, -1000, -1, 1]])
      logx = tf.constant(logx_)
      [means, sums] = self.evaluate(
          [
              leave_one_out.log_loomean_exp(logx, axis=1),
              leave_one_out.log_loosum_exp(logx, axis=1),
          ]
      )
      self.assertEqual((1, 4), means[0].shape)
      self.assertEqual((1,), means[1].shape)
      self.assertEqual((1, 4), sums[0].shape)
      self.assertEqual((1,), sums[1].shape)
      self.assertAllClose(
          means,
          [sums[0] - np.log(3.0), sums[1] - np.log(4.0)],
          atol=0.0,
          rtol=1e-5,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.stats import leave_one_out
label_desc: Use image node_id 1 for calling the LogLooMeanTest obj's underlying member method code with example usage: obj.test_sum_vs_mean() without return types