Automated g4 rollback of changelist 198087342

PiperOrigin-RevId: 198117552

3 files changed, 9 insertions, 70 deletions

diff --git a/tensorflow/contrib/boosted_trees/estimator_batch/estimator.py b/tensorflow/contrib/boosted_trees/estimator_batch/estimator.py
index c8d401bfa6..89d0d611d2 100644
--- a/tensorflow/contrib/boosted_trees/estimator_batch/estimator.py
+++ b/tensorflow/contrib/boosted_trees/estimator_batch/estimator.py
@@ -41,8 +41,7 @@ class GradientBoostedDecisionTreeClassifier(estimator.Estimator):
                feature_engineering_fn=None,
                logits_modifier_function=None,
                center_bias=True,
-               use_core_libs=False,
-               output_leaf_index=False):
+               use_core_libs=False):
     """Initializes a GradientBoostedDecisionTreeClassifier estimator instance.
 
     Args:
@@ -67,14 +66,6 @@ class GradientBoostedDecisionTreeClassifier(estimator.Estimator):
         the bias.
       use_core_libs: Whether feature columns and loss are from the core (as
         opposed to contrib) version of tensorflow.
-      output_leaf_index: whether to output leaf indices along with predictions
-        during inference. The leaf node indexes are available in predictions
-        dict by the key 'leaf_index'. For example,
-        result_dict = classifier.predict(...)
-        for example_prediction_result in result_dict:
-          # access leaf index list by example_prediction_result["leaf_index"]
-          # which contains one leaf index per tree
-
     Raises:
       ValueError: If learner_config is not valid.
     """
@@ -83,9 +74,7 @@ class GradientBoostedDecisionTreeClassifier(estimator.Estimator):
       # supports second order derivative.
       def loss_fn(labels, logits, weights=None):
         result = losses.per_example_maxent_loss(
-            labels=labels,
-            logits=logits,
-            weights=weights,
+            labels=labels, logits=logits, weights=weights,
             num_classes=n_classes)
         return math_ops.reduce_mean(result[0])
     else:
@@ -113,7 +102,6 @@ class GradientBoostedDecisionTreeClassifier(estimator.Estimator):
             'center_bias': center_bias,
             'logits_modifier_function': logits_modifier_function,
             'use_core_libs': use_core_libs,
-            'output_leaf_index': output_leaf_index,
         },
         model_dir=model_dir,
         config=config,
@@ -136,8 +124,7 @@ class GradientBoostedDecisionTreeRegressor(estimator.Estimator):
                feature_engineering_fn=None,
                logits_modifier_function=None,
                center_bias=True,
-               use_core_libs=False,
-               output_leaf_index=False):
+               use_core_libs=False):
     """Initializes a GradientBoostedDecisionTreeRegressor estimator instance.
 
     Args:
@@ -164,13 +151,6 @@ class GradientBoostedDecisionTreeRegressor(estimator.Estimator):
         the bias.
       use_core_libs: Whether feature columns and loss are from the core (as
         opposed to contrib) version of tensorflow.
-      output_leaf_index: whether to output leaf indices along with predictions
-        during inference. The leaf node indexes are available in predictions
-        dict by the key 'leaf_index'. For example,
-        result_dict = classifier.predict(...)
-        for example_prediction_result in result_dict:
-          # access leaf index list by example_prediction_result["leaf_index"]
-          # which contains one leaf index per tree
     """
     head = head_lib.regression_head(
         label_name=label_name,
@@ -193,7 +173,6 @@ class GradientBoostedDecisionTreeRegressor(estimator.Estimator):
             'logits_modifier_function': logits_modifier_function,
             'center_bias': center_bias,
             'use_core_libs': use_core_libs,
-            'output_leaf_index': False,
         },
         model_dir=model_dir,
         config=config,
@@ -218,8 +197,7 @@ class GradientBoostedDecisionTreeEstimator(estimator.Estimator):
                feature_engineering_fn=None,
                logits_modifier_function=None,
                center_bias=True,
-               use_core_libs=False,
-               output_leaf_index=False):
+               use_core_libs=False):
     """Initializes a GradientBoostedDecisionTreeEstimator estimator instance.
 
     Args:
@@ -242,13 +220,6 @@ class GradientBoostedDecisionTreeEstimator(estimator.Estimator):
         the bias.
       use_core_libs: Whether feature columns and loss are from the core (as
         opposed to contrib) version of tensorflow.
-      output_leaf_index: whether to output leaf indices along with predictions
-        during inference. The leaf node indexes are available in predictions
-        dict by the key 'leaf_index'. For example,
-        result_dict = classifier.predict(...)
-        for example_prediction_result in result_dict:
-          # access leaf index list by example_prediction_result["leaf_index"]
-          # which contains one leaf index per tree
     """
     super(GradientBoostedDecisionTreeEstimator, self).__init__(
         model_fn=model.model_builder,
@@ -262,7 +233,6 @@ class GradientBoostedDecisionTreeEstimator(estimator.Estimator):
             'logits_modifier_function': logits_modifier_function,
             'center_bias': center_bias,
             'use_core_libs': use_core_libs,
-            'output_leaf_index': False,
         },
         model_dir=model_dir,
         config=config,
diff --git a/tensorflow/contrib/boosted_trees/estimator_batch/estimator_test.py b/tensorflow/contrib/boosted_trees/estimator_batch/estimator_test.py
index fe91e5293f..0d58317bd5 100644
--- a/tensorflow/contrib/boosted_trees/estimator_batch/estimator_test.py
+++ b/tensorflow/contrib/boosted_trees/estimator_batch/estimator_test.py
@@ -62,34 +62,12 @@ class BoostedTreeEstimatorTest(test_util.TensorFlowTestCase):
         examples_per_layer=3,
         model_dir=model_dir,
         config=config,
-        feature_columns=[contrib_feature_column.real_valued_column("x")],
-        output_leaf_index=False)
+        feature_columns=[contrib_feature_column.real_valued_column("x")])
 
     classifier.fit(input_fn=_train_input_fn, steps=15)
     classifier.evaluate(input_fn=_eval_input_fn, steps=1)
     classifier.export(self._export_dir_base)
 
-  def testThatLeafIndexIsInPredictions(self):
-    learner_config = learner_pb2.LearnerConfig()
-    learner_config.num_classes = 2
-    learner_config.constraints.max_tree_depth = 1
-    model_dir = tempfile.mkdtemp()
-    config = run_config.RunConfig()
-
-    classifier = estimator.GradientBoostedDecisionTreeClassifier(
-        learner_config=learner_config,
-        num_trees=1,
-        examples_per_layer=3,
-        model_dir=model_dir,
-        config=config,
-        feature_columns=[contrib_feature_column.real_valued_column("x")],
-        output_leaf_index=True)
-
-    classifier.fit(input_fn=_train_input_fn, steps=15)
-    result_dict = classifier.predict(input_fn=_eval_input_fn)
-    for prediction_item in result_dict:
-      self.assertTrue("leaf_index" in prediction_item)
-
   def testFitAndEvaluateDontThrowExceptionWithCoreForEstimator(self):
     learner_config = learner_pb2.LearnerConfig()
     learner_config.num_classes = 2
@@ -109,8 +87,7 @@ class BoostedTreeEstimatorTest(test_util.TensorFlowTestCase):
         model_dir=model_dir,
         config=config,
         feature_columns=[core_feature_column.numeric_column("x")],
-        use_core_libs=True,
-        output_leaf_index=False)
+        use_core_libs=True)
 
     model.fit(input_fn=_train_input_fn, steps=15)
     model.evaluate(input_fn=_eval_input_fn, steps=1)
@@ -130,8 +107,7 @@ class BoostedTreeEstimatorTest(test_util.TensorFlowTestCase):
         model_dir=model_dir,
         config=config,
         feature_columns=[core_feature_column.numeric_column("x")],
-        use_core_libs=True,
-        output_leaf_index=False)
+        use_core_libs=True)
 
     classifier.fit(input_fn=_train_input_fn, steps=15)
     classifier.evaluate(input_fn=_eval_input_fn, steps=1)
@@ -151,8 +127,7 @@ class BoostedTreeEstimatorTest(test_util.TensorFlowTestCase):
         model_dir=model_dir,
         config=config,
         feature_columns=[core_feature_column.numeric_column("x")],
-        use_core_libs=True,
-        output_leaf_index=False)
+        use_core_libs=True)
 
     regressor.fit(input_fn=_train_input_fn, steps=15)
     regressor.evaluate(input_fn=_eval_input_fn, steps=1)
diff --git a/tensorflow/contrib/boosted_trees/estimator_batch/model.py b/tensorflow/contrib/boosted_trees/estimator_batch/model.py
index 1ee8911989..15ab6d8145 100644
--- a/tensorflow/contrib/boosted_trees/estimator_batch/model.py
+++ b/tensorflow/contrib/boosted_trees/estimator_batch/model.py
@@ -63,8 +63,6 @@ def model_builder(features, labels, mode, params, config):
   num_trees = params["num_trees"]
   use_core_libs = params["use_core_libs"]
   logits_modifier_function = params["logits_modifier_function"]
-  output_leaf_index = params["output_leaf_index"]
-
   if features is None:
     raise ValueError("At least one feature must be specified.")
 
@@ -98,8 +96,7 @@ def model_builder(features, labels, mode, params, config):
       feature_columns=feature_columns,
       logits_dimension=head.logits_dimension,
       features=training_features,
-      use_core_columns=use_core_libs,
-      output_leaf_index=output_leaf_index)
+      use_core_columns=use_core_libs)
   with ops.name_scope("gbdt", "gbdt_optimizer"):
     predictions_dict = gbdt_model.predict(mode)
     logits = predictions_dict["predictions"]
@@ -130,9 +127,6 @@ def model_builder(features, labels, mode, params, config):
         labels=labels,
         train_op_fn=_train_op_fn,
         logits=logits)
-  if output_leaf_index and gbdt_batch.LEAF_INDEX in predictions_dict:
-    model_fn_ops.predictions[gbdt_batch.LEAF_INDEX] = predictions_dict[
-        gbdt_batch.LEAF_INDEX]
   if num_trees:
     if center_bias:
       num_trees += 1