code: def compute_loss(trainable_variables, non_trainable_variables, x, y):
      y_pred, updated_non_trainable_variables = model.stateless_call(
          trainable_variables, non_trainable_variables, x
      )
      loss_value = loss(y, y_pred)
      return loss_value, updated_non_trainable_variables
  
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 3 for calling a global function with example usage: compute_loss(trainable_variables, non_trainable_variables, x, y) and returns: loss_value,  updated_non_trainable_variables