code: def testNormalShapeWithPlaceholders(self):
      mu = array_ops.placeholder(dtype=dtypes.float32)
      sigma = array_ops.placeholder(dtype=dtypes.float32)
      normal = normal_lib.Normal(loc=mu, scale=sigma)
  
      with self.cached_session() as sess:
          # get_batch_shape should return an "<unknown>" tensor.
          self.assertEqual(
              normal.batch_shape, tensor_shape.TensorShape(None)
          )
          self.assertEqual(normal.event_shape, ())
          self.assertAllEqual(
              self.evaluate(normal.event_shape_tensor()), []
          )
          self.assertAllEqual(
              sess.run(
                  normal.batch_shape_tensor(),
                  feed_dict={mu: 5.0, sigma: [1.0, 2.0]},
              ),
              [2],
          )
  
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 30 for calling the NormalTest obj's underlying member method code with example usage: obj.testNormalShapeWithPlaceholders() without return types