code: def testShapes(self):
      for batch_shape in ([], [1], [2, 3, 4]):
          dist = make_relaxed_categorical(batch_shape, 10)
          self.assertAllEqual(
              batch_shape, tensorshape_util.as_list(dist.batch_shape)
          )
          self.assertAllEqual(
              batch_shape, self.evaluate(dist.batch_shape_tensor())
          )
          self.assertAllEqual(
              [10], self.evaluate(dist.event_shape_tensor())
          )
          self.assertAllEqual(
              [10], self.evaluate(dist.event_shape_tensor())
          )
  
      for batch_shape in ([], [1], [2, 3, 4]):
          dist = make_relaxed_categorical(
              batch_shape, tf.constant(10, dtype=tf.int32)
          )
          self.assertAllEqual(
              len(batch_shape), tensorshape_util.rank(dist.batch_shape)
          )
          self.assertAllEqual(
              batch_shape, self.evaluate(dist.batch_shape_tensor())
          )
          self.assertAllEqual(
              [10], self.evaluate(dist.event_shape_tensor())
          )
          self.assertAllEqual(
              [10], self.evaluate(dist.event_shape_tensor())
          )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy.special import gamma
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import relaxed_onehot_categorical
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 7 for calling the RelaxedOneHotCategoricalTest obj's underlying member method code with example usage: obj.testShapes() without return types