code: def testShapesBroadcast(self):
      low = np.zeros(shape=(2, 3), dtype=self._dtype)
      high = np.ones(shape=(1, 3), dtype=self._dtype)
      peak = self._dtype(0.5)
      tri = triangular.Triangular(
          low=low, high=high, peak=peak, validate_args=True
      )
      self.assertAllEqual([], self.evaluate(tri.event_shape_tensor()))
      self.assertAllEqual(
          [2, 3], self.evaluate(tri.batch_shape_tensor())
      )
      self.assertEqual(tf.TensorShape([]), tri.event_shape)
      self.assertEqual(tf.TensorShape([2, 3]), tri.batch_shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the _TriangularTest obj's underlying member method code with example usage: obj.testShapesBroadcast() without return types