docstr: Batch matrix multiplication test.
docstr_tok: ["Batch","matrix","multiplication","test","."]
code: def test_compare_einsum(self):
      """Batch matrix multiplication test."""
  
      np.random.seed(42)
  
      # We're comparing with regular `einsum` so we choose a `min_value`
      # to make underflow impossible.
      a = _random_sparse_tensor([2, 2, 2, 2, 2, 2, 2], min_value=0.1)
      b = _random_sparse_tensor([2, 2, 2, 2, 2, 2, 2], min_value=0.1)
      formula = "abcdcfg,edfcbaa->bd"
      u = tf.math.log(tf.einsum(formula, a, b))
      v = logeinsumexp(formula, tf.math.log(a), tf.math.log(b))
      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 6 for calling the _EinLogSumExpTest obj's underlying member method code with example usage: obj.test_compare_einsum() without return types