diff --git a/tensorflow/python/distribute/multi_worker_util.py b/tensorflow/python/distribute/multi_worker_util.py
index c804ed9b8bc..4d89b2fab08 100644
--- a/tensorflow/python/distribute/multi_worker_util.py
+++ b/tensorflow/python/distribute/multi_worker_util.py
@@ -53,7 +53,10 @@ def _validate_cluster_spec(cluster_spec, task_type, task_id):
   It checks:
   0) None of `cluster_spec`, `task_type`, and `task_id` is `None`.
   1) task type is one of "chief", "worker" or "evaluator".
-  2) whether there is such a task type as `task_type` in the `cluster_spec`.
+  2) whether there is such a task type as `task_type` in the `cluster_spec`. The
+     only exception is `evaluator`. In other words, it is still a valid
+     configuration when `task_type` is `evaluator` but it doesn't appear in
+     `cluster_spec`. This is to be compatible with `TF_CONFIG` in Estimator.
   3) whether there is at most one "chief" job.
   4) whether there is at most one "evaluator" job.
   5) whether the `task_id` is smaller than the number of tasks for that
@@ -76,7 +79,7 @@ def _validate_cluster_spec(cluster_spec, task_type, task_id):
         "Unrecognized task_type: %r, valid task types are: \"chief\", "
         "\"worker\", \"evaluator\" and \"ps\"." % task_type)
 
-  if task_type and task_type not in cluster_spec:
+  if task_type and task_type not in cluster_spec and task_type != "evaluator":
     raise ValueError("`task_type` %r not found in cluster_spec." % task_type)
 
   if len(cluster_spec.get("chief", [])) > 1:
@@ -85,7 +88,8 @@ def _validate_cluster_spec(cluster_spec, task_type, task_id):
   if len(cluster_spec.get("evaluator", [])) > 1:
     raise ValueError("There must be at most one 'evaluator' job.")
 
-  if task_id >= len(cluster_spec[task_type]):
+  # The `evaluator` job is allowed to be missing in `cluster_spec`.
+  if task_type in cluster_spec and task_id >= len(cluster_spec[task_type]):
     raise ValueError(
         "The `task_id` %d exceeds the maximum id of %s." % (task_id, task_type))
 
diff --git a/tensorflow/python/distribute/multi_worker_util_test.py b/tensorflow/python/distribute/multi_worker_util_test.py
index dbe57b24e08..6a51e71ded7 100644
--- a/tensorflow/python/distribute/multi_worker_util_test.py
+++ b/tensorflow/python/distribute/multi_worker_util_test.py
@@ -237,5 +237,30 @@ class CollectiveLeaderTest(test.TestCase):
         multi_worker_util.collective_leader(cluster_spec, None, 0), "")
 
 
+# Most of the validation logic is tested by above tests except for some.
+class ClusterSpecValidationTest(test.TestCase):
+
+  def testEvaluatorNotInCluster(self):
+    cluster_spec = {
+        "chief": ["127.0.0.1:1234"],
+        "worker": ["127.0.0.1:8964", "127.0.0.1:2333"],
+        "ps": ["127.0.0.1:1926", "127.0.0.1:3141"]
+    }
+    multi_worker_util._validate_cluster_spec(cluster_spec, "chief", 0)
+    multi_worker_util._validate_cluster_spec(cluster_spec, "worker", 0)
+    multi_worker_util._validate_cluster_spec(cluster_spec, "ps", 0)
+    multi_worker_util._validate_cluster_spec(cluster_spec, "evaluator", 0)
+
+  def testWorkerNotInCluster(self):
+    cluster_spec = {
+        "chief": ["127.0.0.1:1234"],
+        "ps": ["127.0.0.1:1926", "127.0.0.1:3141"]
+    }
+    multi_worker_util._validate_cluster_spec(cluster_spec, "evaluator", 0)
+    with self.assertRaisesRegexp(
+        ValueError, "`task_type` 'worker' not found in cluster_spec."):
+      multi_worker_util._validate_cluster_spec(cluster_spec, "worker", 0)
+
+
 if __name__ == "__main__":
   test.main()