code: def test_single_param_slice_broadcast_batch(self):
      if not tf.executing_eagerly():
          return
      sliced = slicing._slice_single_param(
          tf.zeros([4, 3, 1]),  # batch = [4, 3], event = [1]
          param_event_ndims=1,
          slices=make_slices[..., tf.newaxis, 2:, tf.newaxis],
          batch_shape=tf.constant([7, 4, 3]),
      )
      self.assertAllEqual(
          list(
              tf.zeros([1, 4, 3])[..., tf.newaxis, 2:, tf.newaxis].shape
          )
          + [1],
          self.evaluate(sliced).shape,
      )
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import split
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import slicing
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 13 for calling the SlicingTest obj's underlying member method code with example usage: obj.test_single_param_slice_broadcast_batch() without return types