Add whitelist support in uid of RunConfig.

Change: 154794859

tensorflow/contrib/learn/python/learn/estimators/run_config.py

@@ -31,6 +31,17 @@ from tensorflow.python.estimator import run_config as core_run_config
 from tensorflow.python.training import server_lib
 
 
+_DEFAULT_UID_WHITE_LIST = [
+    'tf_random_seed',
+    'save_summary_steps',
+    'save_checkpoints_steps',
+    'save_checkpoints_secs',
+    'session_config',
+    'keep_checkpoint_max',
+    'keep_checkpoint_every_n_hours',
+]
+
+
 class Environment(object):
   # For running general distributed training.
   CLOUD = 'cloud'
@@ -312,18 +323,29 @@ class RunConfig(ClusterConfig, core_run_config.RunConfig):
     return new_copy
 
   @experimental
-  def uid(self):
+  def uid(self, whitelist=None):
     """Generates a 'Unique Identifier' based on all internal fields.
 
     Caller should use the uid string to check `RunConfig` instance integrity
     in one session use, but should not rely on the implementation details, which
     is subject to change.
 
+    Args:
+      whitelist: A list of the string names of the properties uid should not
+        include. If `None`, defaults to `_DEFAULT_UID_WHITE_LIST`, which
+        includes most properites user allowes to change.
+
     Returns:
       A uid string.
     """
-    # TODO(b/33295821): Allows user to specify a whitelist.
+    if whitelist is None:
+      whitelist = _DEFAULT_UID_WHITE_LIST
+
     state = {k: v for k, v in self.__dict__.items() if not k.startswith('__')}
+    # Pop out the keys in whitelist.
+    for k in whitelist:
+      state.pop('_' + k, None)
+
     ordered_state = collections.OrderedDict(
         sorted(state.items(), key=lambda t: t[0]))
     # For class instance without __repr__, some special cares are required.

tensorflow/contrib/learn/python/learn/estimators/run_config_test.py

@@ -257,6 +257,51 @@ class RunConfigTest(test.TestCase):
     self.assertNotEqual(expected_uid, new_config.uid())
     self.assertEqual(ANOTHER_TEST_DIR, new_config.model_dir)
 
+  def test_uid_for_whitelist(self):
+    whitelist = ["model_dir"]
+    config = run_config_lib.RunConfig(
+        tf_random_seed=RANDOM_SEED, model_dir=TEST_DIR)
+
+    expected_uid = config.uid(whitelist)
+    self.assertEqual(expected_uid, config.uid(whitelist))
+
+    new_config = config.replace(model_dir=ANOTHER_TEST_DIR)
+    self.assertEqual(TEST_DIR, config.model_dir)
+    self.assertEqual(expected_uid, new_config.uid(whitelist))
+    self.assertEqual(ANOTHER_TEST_DIR, new_config.model_dir)
+
+  def test_uid_for_default_whitelist(self):
+    config = run_config_lib.RunConfig(
+        tf_random_seed=11,
+        save_summary_steps=12,
+        save_checkpoints_steps=13,
+        save_checkpoints_secs=14,
+        session_config=15,
+        keep_checkpoint_max=16,
+        keep_checkpoint_every_n_hours=17)
+    self.assertEqual(11, config.tf_random_seed)
+    self.assertEqual(12, config.save_summary_steps)
+    self.assertEqual(13, config.save_checkpoints_steps)
+    self.assertEqual(14, config.save_checkpoints_secs)
+    self.assertEqual(15, config.session_config)
+    self.assertEqual(16, config.keep_checkpoint_max)
+    self.assertEqual(17, config.keep_checkpoint_every_n_hours)
+
+    new_config = run_config_lib.RunConfig(
+        tf_random_seed=21,
+        save_summary_steps=22,
+        save_checkpoints_steps=23,
+        save_checkpoints_secs=24,
+        session_config=25,
+        keep_checkpoint_max=26,
+        keep_checkpoint_every_n_hours=27)
+    self.assertEqual(config.uid(), new_config.uid())
+    # model_dir is not on the default whitelist.
+    self.assertNotEqual(config.uid(whitelist=[]),
+                        new_config.uid(whitelist=[]))
+    new_config = new_config.replace(model_dir=ANOTHER_TEST_DIR)
+    self.assertNotEqual(config.uid(), new_config.uid())
+
   def test_uid_for_deepcopy(self):
     tf_config = {
         "cluster": {

tensorflow/contrib/learn/python/learn/learn_runner_test.py

@@ -293,8 +293,7 @@ class LearnRunnerRunWithRunConfigTest(test.TestCase):
     def _experiment_fn(run_config, hparams):
       del run_config, hparams  # unused.
       # Explicitly use a new run_config.
-      new_config = run_config_lib.RunConfig(
-          model_dir=_MODIR_DIR, save_checkpoints_steps=123)
+      new_config = run_config_lib.RunConfig(model_dir=_MODIR_DIR + "/123")
 
       return TestExperiment(config=new_config)