code: def loss(x, label):
      logit = model(x, training=True)
      return objax.functional.loss.cross_entropy_logits_sparse(
          logit, label
      ).mean()
  
file_path: objax/examples/image_classification/cifar10_simple.py
imports: import random
  import numpy
  import tensorflow
  import objax
  from objax.zoo.wide_resnet import WideResNet
label_desc: Use image node_id 1 for calling a global function with example usage: loss(x, label) and returns: objax