code: def dummy_input_fn(features, labels):
      """Returns an input_fn that returns feature and labels `Tensors`."""
  
      def _input_fn(params=None):
          del params  # Unused.
  
          input_features = {"x": tf.constant(features, name="x")}
          input_labels = tf.constant(labels, name="y")
          return input_features, input_labels
  
      return _input_fn
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  import struct
  import sys
  from absl import flags
  from absl.testing import parameterized
  from adanet import ensemble
  from adanet import subnetwork
  from adanet import tf_compat
  from adanet.core.architecture import _Architecture
  from adanet.core.candidate import _Candidate
  from adanet.core.ensemble_builder import _EnsembleSpec
  from adanet.core.ensemble_builder import _SubnetworkSpec
  from adanet.core.eval_metrics import _EnsembleMetrics
  from adanet.core.eval_metrics import _IterationMetrics
  from adanet.core.eval_metrics import _SubnetworkMetrics
  import tensorflow.compat.v2
label_desc: Use image node_id 5 for calling a global function with example usage: dummy_input_fn(features, labels) and returns: _input_fn, input_features,  input_labels