code: def test_creates_batch_model_from_multiple_series(self):
      model = default_model.build_default_model(
          self._build_test_series(
              shape=[48, 3], freq=pd.DateOffset(hours=1)
          )
      )
      self.assertAllEqual(model.batch_shape, [3])
  
imports: import pandas
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.optimizer.convergence_criteria import successive_gradients_are_uncorrelated
  from tensorflow_probability.python.sts import default_model
  from tensorflow_probability.python.sts import fitting
  from tensorflow_probability.python.sts import regularization
  from tensorflow_probability.python.sts.components import local_linear_trend
  from tensorflow_probability.python.sts.components import seasonal
  from tensorflow_probability.python.sts.components import semilocal_linear_trend
  from tensorflow_probability.python.sts.components import sum
  from tensorflow_probability.python.sts.forecast import forecast
  from tensorflow_probability.python.vi import optimization
label_desc: Use image node_id 4 for calling the DefaultModelTests obj's underlying member method code with example usage: obj.test_creates_batch_model_from_multiple_series() without return types