message: Update evaluation_test to not rely on Keras metrics.
diff: @@ -26,10 +26,10 @@ from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  -from tensorflow.python.keras import metrics as metrics_module
  from tensorflow.python.layers import layers
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  +from tensorflow.python.ops import metrics as metrics_module
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops.losses import losses
  @@ -117,19 +117,18 @@ class EvaluateOnceTest(test.TestCase):
  logits = logistic_classifier(inputs)
  predictions = math_ops.round(logits)
  - accuracy = metrics_module.Accuracy()
  - update_op = accuracy.update_state(labels, predictions)
  + accuracy, update_op = metrics_module.accuracy(labels, predictions)
  checkpoint_path = saver.latest_checkpoint(checkpoint_dir)
  final_ops_values = evaluation._evaluate_once(
  checkpoint_path=checkpoint_path,
  eval_ops=update_op,
  - final_ops={'accuracy': (accuracy.result(), update_op)},
  + final_ops={'accuracy': (accuracy, update_op)},
  hooks=[
  evaluation._StopAfterNEvalsHook(1),
  ])
  - self.assertTrue(final_ops_values['accuracy'] > .99)
  + self.assertGreater(final_ops_values['accuracy'], .99)
  def testEvaluateWithFiniteInputs(self):
  checkpoint_dir = os.path.join(self.get_temp_dir(),
  @@ -150,8 +149,7 @@ class EvaluateOnceTest(test.TestCase):
  logits = logistic_classifier(inputs)
  predictions = math_ops.round(logits)
  - accuracy = metrics_module.Accuracy()
  - update_op = accuracy.update_state(labels, predictions)
  + accuracy, update_op = metrics_module.accuracy(labels, predictions)
  checkpoint_path = saver.latest_checkpoint(checkpoint_dir)
  @@ -159,7 +157,7 @@ class EvaluateOnceTest(test.TestCase):
  checkpoint_path=checkpoint_path,
  eval_ops=update_op,
  final_ops={
  - 'accuracy': (accuracy.result(), update_op),
  + 'accuracy': (accuracy, update_op),
  'eval_steps': evaluation._get_or_create_eval_step()
  },
  hooks=[
  