code: def loss(params, batch):
      inputs, targets = batch
      preds = predict(params, inputs)
      return -jnp.mean(jnp.sum(preds * targets, axis=1))
  
file_path: jax/examples/mnist_classifier.py
imports: import time
  import itertools
  import numpy.random
  import jax.numpy
  from jax import jit, grad, random
  from jax.example_libraries import optimizers
  from jax.example_libraries import stax
  from jax.example_libraries.stax import Dense, Relu, LogSoftmax
  from examples import datasets
label_desc: Use image node_id 1 for calling a global function with example usage: loss(params, batch) and returns: unknown