code: def accuracy(params, inputs, targets):
      target_class = np.argmax(targets, axis=1)
      predicted_class = np.argmax(
          neural_net_predict(params, inputs), axis=1
      )
      return np.mean(predicted_class == target_class)
  
file_path: autograd/examples/neural_net.py
imports: from __future__ import absolute_import, division
  from __future__ import print_function
  import autograd.numpy
  import autograd.numpy.random
  from autograd.scipy.special import logsumexp
  from autograd import grad
  from autograd.misc.flatten import flatten
  from autograd.misc.optimizers import adam
  from data import load_mnist
label_desc: Use image node_id 5 for calling a global function with example usage: accuracy(params, inputs, targets) and returns: np