code: def test_parameters_as_kwargs(self, mock_warning):
      dist = normal.Normal(loc=tf.zeros([2]), scale=tf.ones([5, 1]))
      self.assertAllEqual(
          batch_shape_lib.inferred_batch_shape_tensor(dist), [5, 2]
      )
      self.assertAllEqual(
          batch_shape_lib.inferred_batch_shape_tensor(
              dist, loc=tf.zeros([5])
          ),
          [5, 5],
      )
      self.assertAllEqual(
          batch_shape_lib.inferred_batch_shape_tensor(
              dist, scale=tf.zeros([5]), loc=tf.zeros([1, 1])
          ),
          [1, 5],
      )
  
      # Check that passing an unrecognized argument raises a warning.
      self.assertEqual(0, mock_warning.call_count)
      batch_shape_lib.inferred_batch_shape_tensor(dist, df=3.0)
      self.assertEqual(1, mock_warning.call_count)
  
imports: from absl import logging
  from absl.testing import parameterized
  import mock
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import batch_shape_lib
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import test_util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling the ParametersAsKwargsTest obj's underlying member method code with example usage: obj.test_parameters_as_kwargs(mock_warning) without return types