code: def make_sum_of_shallow(
      time_series_xs: Array,
      width: int = 5,
      periods: Sequence[float] = (0.1,),
      num_outputs: int = 1,
  ) -> bnn.BNN:
      """Return a sum of depth 0 and 1 trees."""
      stumps = bnn_tree.list_of_all(
          time_series_xs, 0, width, periods=periods
      )
      depth1 = bnn_tree.list_of_all(
          time_series_xs, 1, width, periods=periods, include_sums=False
      )
  
      return operators.WeightedSum(
          bnns=tuple(stumps + depth1), num_outputs=num_outputs
      )
  
file_path: probability/tensorflow_probability/python/experimental/autobnn/models.py
imports: import functools
  from typing import Sequence
  import jax.numpy
  from tensorflow_probability.python.experimental.autobnn import bnn
  from tensorflow_probability.python.experimental.autobnn import bnn_tree
  from tensorflow_probability.python.experimental.autobnn import kernels
  from tensorflow_probability.python.experimental.autobnn import likelihoods
  from tensorflow_probability.python.experimental.autobnn import operators
label_desc: Use image node_id 7 for calling a global function with example usage: make_sum_of_shallow(time_series_xs, width, periods, num_outputs) and returns: operators