Automated g4 rollback of changelist 201011811

PiperOrigin-RevId: 201033171

1 files changed, 12 insertions, 13 deletions

diff --git a/tensorflow/contrib/slim/python/slim/evaluation_test.py b/tensorflow/contrib/slim/python/slim/evaluation_test.py
index 3d0308aaf3..94fc12ca81 100644
--- a/tensorflow/contrib/slim/python/slim/evaluation_test.py
+++ b/tensorflow/contrib/slim/python/slim/evaluation_test.py
@@ -26,6 +26,7 @@ import time
 import numpy as np
 
 from tensorflow.contrib.framework.python.ops import variables as variables_lib
+from tensorflow.contrib.metrics.python.ops import metric_ops
 from tensorflow.contrib.slim.python.slim import evaluation
 from tensorflow.contrib.training.python.training import evaluation as evaluation_lib
 from tensorflow.core.protobuf import saver_pb2
@@ -36,7 +37,6 @@ from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import errors
 from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import math_ops
-from tensorflow.python.ops import metrics
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import flags
 from tensorflow.python.platform import gfile
@@ -89,8 +89,8 @@ class EvaluationTest(test.TestCase):
     self._predictions, self._scale = TestModel(self._inputs)
 
   def testFinalOpsOnEvaluationLoop(self):
-    value_op, update_op = metrics.accuracy(
-        labels=self._labels, predictions=self._predictions)
+    value_op, update_op = metric_ops.streaming_accuracy(self._predictions,
+                                                        self._labels)
     init_op = control_flow_ops.group(variables.global_variables_initializer(),
                                      variables.local_variables_initializer())
     # Create checkpoint and log directories:
@@ -136,10 +136,9 @@ class EvaluationTest(test.TestCase):
     self.assertTrue(obj.hook_was_run)
 
   def _create_names_to_metrics(self, predictions, labels):
-    accuracy0, update_op0 = metrics.accuracy(
-        labels=labels, predictions=predictions)
-    accuracy1, update_op1 = metrics.accuracy(
-        labels=labels, predictions=predictions + 1)
+    accuracy0, update_op0 = metric_ops.streaming_accuracy(predictions, labels)
+    accuracy1, update_op1 = metric_ops.streaming_accuracy(predictions + 1,
+                                                          labels)
 
     names_to_values = {'Accuracy': accuracy0, 'Another_accuracy': accuracy1}
     names_to_updates = {'Accuracy': update_op0, 'Another_accuracy': update_op1}
@@ -199,8 +198,8 @@ class EvaluationTest(test.TestCase):
     predictions_limited = input.limit_epochs(self._predictions, num_epochs=1)
     labels_limited = input.limit_epochs(self._labels, num_epochs=1)
 
-    value_op, update_op = metrics.accuracy(
-        labels=labels_limited, predictions=predictions_limited)
+    value_op, update_op = metric_ops.streaming_accuracy(
+        predictions_limited, labels_limited)
 
     init_op = control_flow_ops.group(variables.global_variables_initializer(),
                                      variables.local_variables_initializer())
@@ -261,8 +260,8 @@ class SingleEvaluationTest(test.TestCase):
     self._prepareCheckpoint(checkpoint_path)
 
     # Next, determine the metric to evaluate:
-    value_op, update_op = metrics.accuracy(
-        labels=self._labels, predictions=self._predictions)
+    value_op, update_op = metric_ops.streaming_accuracy(self._predictions,
+                                                        self._labels)
 
     # Run the evaluation and verify the results:
     accuracy_value = evaluation.evaluate_once(
@@ -277,8 +276,8 @@ class SingleEvaluationTest(test.TestCase):
     self._prepareCheckpoint(checkpoint_path)
 
     # Next, determine the metric to evaluate:
-    value_op, update_op = metrics.accuracy(
-        labels=self._labels, predictions=self._predictions)
+    value_op, update_op = metric_ops.streaming_accuracy(self._predictions,
+                                                        self._labels)
 
     dumping_root = os.path.join(self.get_temp_dir(), 'tfdbg_dump_dir')
     dumping_hook = hooks.DumpingDebugHook(dumping_root, log_usage=False)