code: def make_mlp(num_layers: int):
      """Return a make function for the MultiLayerBNN of the given depth."""
  
      def make_multilayer(
          time_series_xs: Array,
          width: int = 5,
          periods: Sequence[float] = (0.1,),
          num_outputs: int = 1,
      ):
          del num_outputs
          del time_series_xs
          assert len(periods) == 1
          return kernels.MultiLayerBNN(
              num_layers=num_layers,
              width=width,
              period=periods[0],
          )
  
      return make_multilayer
  
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 10 for calling a global function with example usage: make_mlp(num_layers) and returns: make_multilayer, kernels