code: def _export_output_tensors(export_outputs):
      """Returns a dict of `Tensor`, tuple of `Tensor`, or dict of `Tensor`."""
  
      outputs = {}
      for key, export_output in export_outputs.items():
          if isinstance(
              export_output, tf.estimator.export.ClassificationOutput
          ):
              result = ()
              if export_output.classes is not None:
                  result += (
                      tf.strings.to_number(export_output.classes),
                  )
              if export_output.scores is not None:
                  result += (export_output.scores,)
              outputs[key] = result
          elif isinstance(
              export_output, tf.estimator.export.RegressionOutput
          ):
              outputs[key] = export_output.value
          elif isinstance(
              export_output, tf.estimator.export.PredictOutput
          ):
              outputs[key] = export_output.outputs
      return outputs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  from absl.testing import parameterized
  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.iteration import _Iteration
  from adanet.core.iteration import _IterationBuilder
  from adanet.core.iteration import _TrainManager
  from adanet.core.summary import _ScopedSummary
  from adanet.core.summary import _TPUScopedSummary
  import adanet.core.testing_utils
  from adanet.ensemble import Candidate
  from adanet.subnetwork import Builder
  from adanet.subnetwork import Report
  from adanet.subnetwork import Subnetwork
  from adanet.subnetwork import TrainOpSpec
  import tensorflow.compat.v2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import test_util
  from tensorflow_estimator.python.estimator.head import binary_class_head
  from tensorflow_estimator.python.estimator.head import regression_head
label_desc: Use image node_id 2 for calling a global function with example usage: _export_output_tensors(export_outputs) and returns: outputs