code: def _fake_adanet_losses_0(input_fn):
      _, labels = input_fn()
      return [
          tf.reduce_sum(labels),
          tf.reduce_sum(labels * 2),
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from adanet import tf_compat
  from adanet.core.evaluator import Evaluator
  import adanet.core.testing_utils
  import numpy
  import tensorflow.compat.v2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 1 for calling a global function with example usage: _fake_adanet_losses_0(input_fn) and returns: list