code: def make_linear_plus_periodic(
      time_series_xs: Array,
      width: int = 5,
      periods: Sequence[float] = (0.1,),
      num_outputs: int = 1,
  ) -> bnn.BNN:
      """Returns Combo model, consisting of linear and periodic leafs.
  
      Args:
        time_series_xs: The x-values of the training data.
        width: Width of the leaf BNNs.
        periods: Periods for the PeriodicBNN kernel.
        num_outputs: Number of outputs on the BNN.
      """
      del num_outputs
      del time_series_xs
      leaves = [
          kernels.PeriodicBNN(width=width, period=p) for p in periods
      ]
      leaves.append(kernels.LinearBNN(width=width))
      return operators.Add(bnns=tuple(leaves))
  
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 4 for calling a global function with example usage: make_linear_plus_periodic(time_series_xs, width, periods, num_outputs) and returns: operators