Automated rollback of commit 56d4fc8ff67f48294ae5cb0a7f9ff3d954463aa3

PiperOrigin-RevId: 212847619

1 files changed, 21 insertions, 72 deletions

diff --git a/tensorflow/python/estimator/model_fn.py b/tensorflow/python/estimator/model_fn.py
index 728de65559..439cc2e3a4 100644
--- a/tensorflow/python/estimator/model_fn.py
+++ b/tensorflow/python/estimator/model_fn.py
@@ -33,7 +33,6 @@ from tensorflow.python.saved_model import tag_constants
 from tensorflow.python.training import monitored_session
 from tensorflow.python.training import session_run_hook
 from tensorflow.python.util import nest
-from tensorflow.python.util.collections import tf_namedtuple
 from tensorflow.python.util.tf_export import estimator_export
 
 
@@ -63,65 +62,14 @@ EXPORT_TAG_MAP = {
     ModeKeys.EVAL: [tag_constants.EVAL],
 }
 
-# pylint: disable=line-too-long
-
-_EstimatorSpecNamedTuple = tf_namedtuple('EstimatorSpec', [   # pylint: disable=invalid-name
-    ('mode',
-     'A `ModeKeys`. Specifies if this is training, evaluation or prediction.'
-    ),
-    ('predictions', 'Predictions `Tensor` or dict of `Tensor`.'),
-    ('loss',
-     'Training loss `Tensor`. Must be either scalar, or with shape `[1]`.'),
-    ('train_op', 'Op to run one training step.'),
-    ('eval_metric_ops',
-     """Dict of metric results keyed by name.
-
-     The values of the dict are the results of calling a metric function,
-     namely a `(metric_tensor, update_op)` tuple.
-
-     `metric_tensor` should be evaluated without any impact on state
-     (typically is a pure computation results based on variables.).
-     For example, it should not trigger the `update_op` or requires any
-     input fetching."""
-    ),
-    ('export_outputs',
-     """Describes the output signatures to be exported to `SavedModel`.
-
-     A dict `{name: output}` where:
-
-       * `name` is An arbitrary name for this output.
-       * `output` is an `ExportOutput` object such as `ClassificationOutput`,
-         `RegressionOutput`, or `PredictOutput`.
-
-     Single-headed models only need to specify one entry in this dictionary.
-     Multi-headed models should specify one entry for each head, one of
-     which must be named using
-     `signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY`. If no entry is
-     provided, a default `PredictOutput` mapping to `predictions` will be
-     created."""
-    ),
-    ('training_chief_hooks',
-     'Iterable of `tf.train.SessionRunHook` objects to run on the chief worker during training.'
-    ),
-    ('training_hooks',
-     'Iterable of `tf.train.SessionRunHook` objects to run on all workers during training.'
-    ),
-    ('scaffold',
-     'A `tf.train.Scaffold` object that can be used to set initialization, saver, and more to be used in training.'
-    ),
-    ('evaluation_hooks',
-     'Iterable of `tf.train.SessionRunHook` objects to run during evaluation.'
-    ),
-    ('prediction_hooks',
-     'Iterable of `tf.train.SessionRunHook` objects to run during predictions.'
-    ),
-])
-
-# pylint: enable=line-too-long
-
 
 @estimator_export('estimator.EstimatorSpec')
-class EstimatorSpec(_EstimatorSpecNamedTuple):
+class EstimatorSpec(
+    collections.namedtuple('EstimatorSpec', [
+        'mode', 'predictions', 'loss', 'train_op', 'eval_metric_ops',
+        'export_outputs', 'training_chief_hooks', 'training_hooks', 'scaffold',
+        'evaluation_hooks', 'prediction_hooks'
+    ])):
   """Ops and objects returned from a `model_fn` and passed to an `Estimator`.
 
   `EstimatorSpec` fully defines the model to be run by an `Estimator`.
@@ -208,22 +156,23 @@ class EstimatorSpec(_EstimatorSpecNamedTuple):
         A dict `{name: output}` where:
         * name: An arbitrary name for this output.
         * output: an `ExportOutput` object such as `ClassificationOutput`,
-          `RegressionOutput`, or `PredictOutput`. Single-headed models only need
-          to specify one entry in this dictionary. Multi-headed models should
-          specify one entry for each head, one of which must be named using
-          `signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY`. If no entry
-          is provided, a default `PredictOutput` mapping to `predictions` will
-          be created.
-      training_chief_hooks: Iterable of `tf.train.SessionRunHook` objects to run
-        on the chief worker during training.
-      training_hooks: Iterable of `tf.train.SessionRunHook` objects to run on
-        all workers during training.
+            `RegressionOutput`, or `PredictOutput`.
+        Single-headed models only need to specify one entry in this dictionary.
+        Multi-headed models should specify one entry for each head, one of
+        which must be named using
+        signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY.
+        If no entry is provided, a default `PredictOutput` mapping to
+        `predictions` will be created.
+      training_chief_hooks: Iterable of `tf.train.SessionRunHook` objects to
+        run on the chief worker during training.
+      training_hooks: Iterable of `tf.train.SessionRunHook` objects to run
+        on all workers during training.
       scaffold: A `tf.train.Scaffold` object that can be used to set
         initialization, saver, and more to be used in training.
-      evaluation_hooks: Iterable of `tf.train.SessionRunHook` objects to run
-        during evaluation.
-      prediction_hooks: Iterable of `tf.train.SessionRunHook` objects to run
-        during predictions.
+      evaluation_hooks: Iterable of `tf.train.SessionRunHook` objects to
+        run during evaluation.
+      prediction_hooks: Iterable of `tf.train.SessionRunHook` objects to
+        run during predictions.
 
     Returns:
       A validated `EstimatorSpec` object.