code: def __init__(self):
      super(NeuralNet, self).__init__()
      # First hidden layer.
      self.h1 = layers.Dense(n_h1, activation=tf.nn.relu)
      # Second hidden layer.
      self.h2 = layers.Dense(n_h2, activation=tf.nn.relu)
      self.out = layers.Dense(n_outputs)
  
file_path: MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/tensorflow/hyperparameter-tune-and-warm-start-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 1 to create a new NeuralNet object from inherited base classes: Model with example: obj = NeuralNet()