Improves the error essage for throttle_secs=0 case.

User should be aware that the job load might be increased a lot due to this settings.

PiperOrigin-RevId: 209439297

2 files changed, 39 insertions, 1 deletions

diff --git a/tensorflow/python/estimator/training.py b/tensorflow/python/estimator/training.py
index 5c04387b65..e6bd263c80 100644
--- a/tensorflow/python/estimator/training.py
+++ b/tensorflow/python/estimator/training.py
@@ -837,6 +837,13 @@ class _TrainingExecutor(object):
     if difference > 0:
       logging.info('Waiting %f secs before starting next eval run.', difference)
       time.sleep(difference)
+    elif (throttle_secs == 0 and
+          eval_result.status != _EvalStatus.EVALUATED):
+      # Prints a user-actionable warning to avoid unnecessary load on evaluator.
+      logging.warning(
+          'EvalSpec.throttle_secs is set as 0. This might overload the job '
+          'before finding (next) new checkpoint. Please consider to increase '
+          'it.')
 
     return (eval_result, should_early_stop)
 
diff --git a/tensorflow/python/estimator/training_test.py b/tensorflow/python/estimator/training_test.py
index dc106c7d3b..7d46917a6f 100644
--- a/tensorflow/python/estimator/training_test.py
+++ b/tensorflow/python/estimator/training_test.py
@@ -83,6 +83,9 @@ _INVALID_EVAL_LISTENER_MSG = 'must have type `_ContinuousEvalListener`'
 _INVALID_CONFIG_FOR_STD_SERVER_MSG = 'Could not start server; .*TF_CONFIG'
 _INVALID_LOCAL_TASK_WITH_CLUSTER = '`task.type` in TF_CONFIG cannot be `local`'
 _INVALID_TASK_TYPE = '`estimator.config` must have task_type set.'
+_INPROPER_THROTTL_SECS = (
+    'EvalSpec.throttle_secs is set as 0.*Please consider to increase')
+
 # The message should NOT have 'local' word as part of it. As (?!word) is looking
 # ahead, so, the $ (ending) check is required; otherwise, it will match
 # partially and return successuful.
@@ -1281,7 +1284,7 @@ class TrainingExecutorRunEvaluatorTest(test.TestCase):
     ]
 
     eval_spec = training.EvalSpec(
-        input_fn=lambda: 1, start_delay_secs=0, throttle_secs=0)
+        input_fn=lambda: 1, start_delay_secs=0, throttle_secs=2)
 
     executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
     with test.mock.patch.object(logging, 'warning') as mock_log:
@@ -1295,6 +1298,34 @@ class TrainingExecutorRunEvaluatorTest(test.TestCase):
     # successuful evaluation)
     self.assertEqual(2, mock_log.call_count)
 
+  def test_warning_if_throttle_secs_is_zero(self):
+    training_max_step = 200
+    mock_est = test.mock.Mock(spec=estimator_lib.Estimator)
+    mock_est.evaluate.side_effect = [
+        {_GLOBAL_STEP_KEY: training_max_step}
+    ]
+    mock_train_spec = test.mock.Mock(spec=training.TrainSpec)
+    mock_train_spec.max_steps = training_max_step
+
+    self._set_up_mock_est_to_train_and_evaluate_once(mock_est, mock_train_spec)
+
+    # We need to make the first one invalid, so it will check the
+    # throttle_secs=0.
+    mock_est.latest_checkpoint.side_effect = [None, 'path']
+
+    eval_spec = training.EvalSpec(
+        input_fn=lambda: 1, start_delay_secs=0, throttle_secs=0)
+
+    executor = training._TrainingExecutor(mock_est, mock_train_spec, eval_spec)
+    with test.mock.patch.object(logging, 'warning') as mock_log:
+      executor.run_evaluator()
+
+    # First ckpt is invalid.
+    self.assertEqual(2, mock_est.latest_checkpoint.call_count)
+    self.assertEqual(1, mock_est.evaluate.call_count)
+
+    self.assertRegexpMatches(str(mock_log.call_args), _INPROPER_THROTTL_SECS)
+
   def test_continuous_eval_listener_eval_result(self):
     training_max_step = 200
     mock_est = test.mock.Mock(spec=estimator_lib.Estimator)