code: def test_batch_sum(self):
      np.random.seed(42)
  
      a = _random_sparse_tensor([100, 100])
      u = tf.reduce_logsumexp(tf.math.log(a), axis=-1)
      v = logeinsumexp("ij->i", tf.math.log(a))
  
      self.assertAllClose(u, v)
  
imports: import hypothesis
  from hypothesis.extra import numpy
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.marginalize.logeinsumexp import _binary_einslogsumexp
  from tensorflow_probability.python.experimental.marginalize.logeinsumexp import logeinsumexp
  from tensorflow_probability.python.internal import test_util
  import tensorflow_probability.python.internal.hypothesis_testlib
label_desc: Use image node_id 2 for calling the _EinLogSumExpTest obj's underlying member method code with example usage: obj.test_batch_sum() without return types