code: def testScalarSlice(self):
      logits = self.evaluate(
          samplers.normal([], seed=test_util.test_seed())
      )
      dist = bernoulli.Bernoulli(logits=logits, validate_args=True)
      self.assertAllEqual([], dist.batch_shape)
      self.assertAllEqual([1], dist[tf.newaxis].batch_shape)
      self.assertAllEqual([], dist[...].batch_shape)
      self.assertAllEqual(
          [1, 1], dist[tf.newaxis, ..., tf.newaxis].batch_shape
      )
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 1 for calling the BernoulliSlicingTest obj's underlying member method code with example usage: obj.testScalarSlice() without return types