code: def call(self, x, is_training=False):
      x = self.h1(x)
      x = self.h2(x)
      x = self.out(x)
      if not is_training:
          # Apply softmax when not training.
          x = tf.nn.softmax(x)
      return x
  
file_path: MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/tensorflow/train-hyperparameter-tune-deploy-with-tensorflow/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 the NeuralNet obj's underlying member method code with example usage: obj.call(x, is_training) and returns: x