code: def compute_loss_and_updates(
      self,
      trainable_variables,
      non_trainable_variables,
      x,
      y,
      training=False,
  ):
      y_pred, non_trainable_variables = self.stateless_call(
          trainable_variables,
          non_trainable_variables,
          x,
          training=training,
      )
      loss = self.loss_fn(y, y_pred)
      return loss, (y_pred, non_trainable_variables)
  
file_path: keras/guides/custom_train_step_in_jax.py
imports: import os
  import jax
  import keras
  import numpy
label_desc: Use image node_id 2 for calling the CustomModel obj's underlying member method code with example usage: obj.compute_loss_and_updates(trainable_variables, non_trainable_variables, x, y, training) and returns: loss,  y_pred,  non_trainable_variables