code: def train_input_fn(features, labels, batch_size):
      """An input function for training"""
      # Convert the inputs to a Dataset.
      dataset = tf.data.Dataset.from_tensor_slices(
          (dict(features), labels)
      )
  
      # Shuffle, repeat, and batch the examples.
      dataset = dataset.shuffle(1000).repeat().batch(batch_size)
  
      # Return the dataset.
      return dataset
  
file_path: auptimizer/Examples/tf_iris_diff_opt/iris_data.py
imports: import pandas
  import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: train_input_fn(features, labels, batch_size) and returns: dataset