code: def make_model():
      input = keras.Input(shape=[28, 28, 1])
      y = make_backbone()(input)
      y = keras.layers.Flatten()(y)
      y = keras.layers.Dense(200, activation="relu")(y)
      y = keras.layers.Dropout(0.4)(y)
      y = keras.layers.Dense(10, activation="softmax")(y)
      model = keras.Model(inputs=input, outputs=y)
      return model
  
file_path: keras/examples/demo_jax_distributed.py
imports: import os, pprint, collections
  import jax
  import jax.numpy
  import tensorflow
  import keras
  import numpy
  from tqdm import tqdm
  from jax.experimental import mesh_utils
  from jax.sharding import Mesh
  from jax.sharding import NamedSharding
  from jax.sharding import PartitionSpec
label_desc: Use image node_id 2 for calling a global function with example usage: make_model() and returns: model