code: def accuracy(y_pred, y_true):
      # Predicted class is the index of highest score in prediction vector (i.e. argmax).
      correct_prediction = tf.equal(
          tf.argmax(y_pred, 1), tf.cast(y_true, tf.int64)
      )
      return tf.reduce_mean(
          tf.cast(correct_prediction, tf.float32), axis=-1
      )
  
file_path: MachineLearningNotebooks/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/tf_mnist.py
imports: import numpy
  import argparse
  import os
  import re
  import tensorflow
  import time
  import glob
  from azureml.core import Run
  from utils import load_data
  from tensorflow.keras import Model, layers
label_desc: Use image node_id 2 for calling a global function with example usage: accuracy(y_pred, y_true) and returns: tf