code: def compute_batch_loss_acc(model, X, y, training: bool):
      """Compute the loss AND accuracy for the supplied batch; computations runs in
      sequence.
  
      """
      logits = model(X, training=training)
      loss = compute_loss(y, logits)
      acc = compute_accuracy(y, logits)
  
      # Return a pair of two numbers - average loss and accuracy for the given
      # batch.
      return loss, acc
  
imports: from __future__ import division, print_function
  import getpass
  from typing import Dict, Optional
  import fs
  import tensorflow
  import tensorflow_datasets
  import tqdm
  import uv
  import uv.tensorflow.reporter
  import uv.util
  from absl import app
  from uv.fs.reporter import FSReporter
  from uv.mlflow.reporter import MLFlowReporter
  from trainer import cli
label_desc: Use image node_id 6 for calling a global function with example usage: compute_batch_loss_acc(model, X, y, training) and returns: loss,  acc