Splits testLargeCase in metric_ops_test into a dedicated file for slow-running tests and re-enables it as a 'large' test.

PiperOrigin-RevId: 200440883

3 files changed, 90 insertions, 28 deletions

diff --git a/tensorflow/contrib/metrics/BUILD b/tensorflow/contrib/metrics/BUILD
index 4f2c82ca23..3f81c9ccea 100644
--- a/tensorflow/contrib/metrics/BUILD
+++ b/tensorflow/contrib/metrics/BUILD
@@ -97,3 +97,27 @@ py_test(
         "//third_party/py/numpy",
     ],
 )
+
+py_test(
+    name = "metric_ops_large_test",
+    size = "large",
+    srcs = ["python/ops/metric_ops_large_test.py"],
+    srcs_version = "PY2AND3",
+    tags = ["noasan"],  # times out b/63678675
+    deps = [
+        ":metrics_py",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:data_flow_ops",
+        "//tensorflow/python:errors",
+        "//tensorflow/python:framework",
+        "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:framework_test_lib",
+        "//tensorflow/python:math_ops",
+        "//tensorflow/python:platform_test",
+        "//tensorflow/python:random_ops",
+        "//tensorflow/python:sparse_tensor",
+        "//tensorflow/python:variables",
+        "//third_party/py/numpy",
+    ],
+)
diff --git a/tensorflow/contrib/metrics/python/ops/metric_ops_large_test.py b/tensorflow/contrib/metrics/python/ops/metric_ops_large_test.py
new file mode 100644
index 0000000000..7acfc383eb
--- /dev/null
+++ b/tensorflow/contrib/metrics/python/ops/metric_ops_large_test.py
@@ -0,0 +1,66 @@
+# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Large tests for metric_ops."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+from six.moves import xrange  # pylint: disable=redefined-builtin
+from tensorflow.contrib.metrics.python.ops import metric_ops
+from tensorflow.python.framework import dtypes as dtypes_lib
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import random_ops
+from tensorflow.python.ops import variables
+from tensorflow.python.platform import test
+
+
+class StreamingPrecisionRecallAtEqualThresholdsLargeTest(test.TestCase):
+
+  def setUp(self):
+    np.random.seed(1)
+    ops.reset_default_graph()
+
+  def testLargeCase(self):
+    shape = [32, 512, 256, 1]
+    predictions = random_ops.random_uniform(
+        shape, 0.0, 1.0, dtype=dtypes_lib.float32)
+    labels = math_ops.greater(random_ops.random_uniform(shape, 0.0, 1.0), 0.5)
+
+    result, update_op = metric_ops.precision_recall_at_equal_thresholds(
+        labels=labels, predictions=predictions, num_thresholds=201)
+    # Run many updates, enough to cause highly inaccurate values if the
+    # code used float32 for accumulation.
+    num_updates = 71
+
+    with self.test_session() as sess:
+      sess.run(variables.local_variables_initializer())
+      for _ in xrange(num_updates):
+        sess.run(update_op)
+
+      prdata = sess.run(result)
+
+      # Since we use random values, we won't know the tp/fp/tn/fn values, but
+      # tp and fp at threshold 0 should be the total number of positive and
+      # negative labels, hence their sum should be total number of pixels.
+      expected_value = 1.0 * np.product(shape) * num_updates
+      got_value = prdata.tp[0] + prdata.fp[0]
+      # They should be at least within 1.
+      self.assertNear(got_value, expected_value, 1.0)
+
+if __name__ == '__main__':
+  test.main()
diff --git a/tensorflow/contrib/metrics/python/ops/metric_ops_test.py b/tensorflow/contrib/metrics/python/ops/metric_ops_test.py
index b13f08a37d..db4b530ce7 100644
--- a/tensorflow/contrib/metrics/python/ops/metric_ops_test.py
+++ b/tensorflow/contrib/metrics/python/ops/metric_ops_test.py
@@ -2391,34 +2391,6 @@ class StreamingPrecisionRecallAtEqualThresholdsTest(test.TestCase):
       for _ in range(3):
         self._testResultsEqual(initial_result, result)
 
-  def testLargeCase(self):
-    self.skipTest("Test consistently timing out")
-    shape = [32, 512, 256, 1]
-    predictions = random_ops.random_uniform(
-        shape, 0.0, 1.0, dtype=dtypes_lib.float32)
-    labels = math_ops.greater(random_ops.random_uniform(shape, 0.0, 1.0), 0.5)
-
-    result, update_op = metric_ops.precision_recall_at_equal_thresholds(
-        labels=labels, predictions=predictions, num_thresholds=201)
-    # Run many updates, enough to cause highly inaccurate values if the
-    # code used float32 for accumulation.
-    num_updates = 71
-
-    with self.test_session() as sess:
-      sess.run(variables.local_variables_initializer())
-      for _ in xrange(num_updates):
-        sess.run(update_op)
-
-      prdata = sess.run(result)
-
-      # Since we use random values, we won't know the tp/fp/tn/fn values, but
-      # tp and fp at threshold 0 should be the total number of positive and
-      # negative labels, hence their sum should be total number of pixels.
-      expected_value = 1.0 * np.product(shape) * num_updates
-      got_value = prdata.tp[0] + prdata.fp[0]
-      # They should be at least within 1.
-      self.assertNear(got_value, expected_value, 1.0)
-
   def _testCase(self,
                 predictions,
                 labels,