code: def _unflatten_model(components, callable_params):
      model_components = components["model"]
      num_components = len(model_components) + len(callable_params)
  
      # Preserve the order of `model`.
      components_ind = [
          i for i in range(num_components) if i not in callable_params
      ]
      keyed_model = list(zip(components_ind, model_components)) + list(
          callable_params.items()
      )
      return type(model_components)(d[1] for d in sorted(keyed_model))
  
imports: import collections
  import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import joint_distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 6 for calling a global function with example usage: _unflatten_model(components, callable_params) and returns: type