code: def testNormalShape(self):
      mu = constant_op.constant([-3.0] * 5)
      sigma = constant_op.constant(11.0)
      normal = normal_lib.Normal(loc=mu, scale=sigma)
  
      self.assertEqual(self.evaluate(normal.batch_shape_tensor()), [5])
      self.assertEqual(
          normal.batch_shape, tensor_shape.TensorShape([5])
      )
      self.assertAllEqual(
          self.evaluate(normal.event_shape_tensor()), []
      )
      self.assertEqual(normal.event_shape, tensor_shape.TensorShape([]))
  
imports: import importlib
  import math
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.ops.distributions import normal
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 29 for calling the NormalTest obj's underlying member method code with example usage: obj.testNormalShape() without return types