code: def assert_shapes_unchanged(target_shaped_dict, possibly_bcast_dict):
      for param, target_param_val in six.iteritems(target_shaped_dict):
          np.testing.assert_array_equal(
              tensorshape_util.as_list(target_param_val.shape),
              tensorshape_util.as_list(
                  possibly_bcast_dict[param].shape
              ),
          )
  
imports: from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gaussian_process
  from tensorflow_probability.python.distributions import gaussian_process_regression_model
  from tensorflow_probability.python.distributions import student_t_process
  from tensorflow_probability.python.distributions import student_t_process_regression_model
  from tensorflow_probability.python.distributions import variational_gaussian_process
  from tensorflow_probability.python.experimental.distributions import marginal_fns
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import hypothesis_testlib
label_desc: Use image node_id 9 for calling a global function with example usage: assert_shapes_unchanged(target_shaped_dict, possibly_bcast_dict) without return types