code: def _spec_metric_fn(self, features, labels, predictions, loss):
      actual = [features, labels, predictions, loss]
      expected = [
          self._features,
          self._labels,
          self._estimator_spec.predictions,
          self._estimator_spec.loss,
      ]
      self._assert_tensors_equal(actual, expected)
      return {"metric_1": tf_compat.v1.metrics.mean(tf.constant(1.0))}
  
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.architecture import _Architecture
  from adanet.core.eval_metrics import _call_eval_metrics
  import adanet.core.testing_utils
  import tensorflow.compat.v2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 4 for calling the MetricsTest obj's underlying member method code with example usage: obj._spec_metric_fn(features, labels, predictions, loss) and returns: dict