code: def eval_input_fn(features, labels, batch_size):
      """An input function for evaluation or prediction"""
      features = dict(features)
      if labels is None:
          # No labels, use only features.
          inputs = features
      else:
          inputs = (features, labels)
  
      # Convert the inputs to a Dataset.
      dataset = tf.data.Dataset.from_tensor_slices(inputs)
  
      # Batch the examples
      assert batch_size is not None, "batch_size must not be None"
      dataset = dataset.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 4 for calling a global function with example usage: eval_input_fn(features, labels, batch_size) and returns: dataset