Move tf.Keras object identifiers into constants.py.

PiperOrigin-RevId: 345257730
Change-Id: I0961d32f28300fe06cac6fa16928fec119baf779

tensorflow/python/keras/protobuf/saved_metadata.proto

@@ -22,9 +22,9 @@ message SavedObject {
   string node_path = 3;
 
   // Identifier to determine loading function.
-  // Currently supported identifiers:
+  // Must be one of:
-  //   _tf_keras_layer, _tf_keras_input_layer, _tf_keras_rnn_layer,
+  //   _tf_keras_input_layer, _tf_keras_layer, _tf_keras_metric,
-  //   _tf_keras_metric, _tf_keras_network, _tf_keras_model,
+  //   _tf_keras_model, _tf_keras_network, _tf_keras_rnn_layer,
   //   _tf_keras_sequential
   string identifier = 4;
   // Metadata containing a JSON-serialized object with the non-TensorFlow

tensorflow/python/keras/saving/saved_model/constants.py

@@ -30,3 +30,22 @@ KERAS_CACHE_KEY = 'keras_serialized_attributes'
 
 # Name of Keras metadata file stored in the SavedModel.
 SAVED_METADATA_PATH = 'keras_metadata.pb'
+
+# Names of SavedObject Keras identifiers.
+INPUT_LAYER_IDENTIFIER = '_tf_keras_input_layer'
+LAYER_IDENTIFIER = '_tf_keras_layer'
+METRIC_IDENTIFIER = '_tf_keras_metric'
+MODEL_IDENTIFIER = '_tf_keras_model'
+NETWORK_IDENTIFIER = '_tf_keras_network'
+RNN_LAYER_IDENTIFIER = '_tf_keras_rnn_layer'
+SEQUENTIAL_IDENTIFIER = '_tf_keras_sequential'
+
+KERAS_OBJECT_IDENTIFIERS = (
+    INPUT_LAYER_IDENTIFIER,
+    LAYER_IDENTIFIER,
+    METRIC_IDENTIFIER,
+    MODEL_IDENTIFIER,
+    NETWORK_IDENTIFIER,
+    RNN_LAYER_IDENTIFIER,
+    SEQUENTIAL_IDENTIFIER,
+)

tensorflow/python/keras/saving/saved_model/layer_serialization.py

@@ -33,7 +33,7 @@ class LayerSavedModelSaver(base_serialization.SavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_layer'
+    return constants.LAYER_IDENTIFIER
 
   @property
   def python_properties(self):
@@ -127,7 +127,7 @@ class InputLayerSavedModelSaver(base_serialization.SavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_input_layer'
+    return constants.INPUT_LAYER_IDENTIFIER
 
   @property
   def python_properties(self):
@@ -153,7 +153,7 @@ class RNNSavedModelSaver(LayerSavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_rnn_layer'
+    return constants.RNN_LAYER_IDENTIFIER
 
   def _get_serialized_attributes_internal(self, serialization_cache):
     objects, functions = (

tensorflow/python/keras/saving/saved_model/load.py

@@ -92,12 +92,6 @@ PUBLIC_ATTRIBUTES = CommonEndpoints.all_functions.union(
 PUBLIC_ATTRIBUTES.add(constants.KERAS_ATTR)
 
 
-KERAS_OBJECT_IDENTIFIERS = (
-    '_tf_keras_layer', '_tf_keras_input_layer', '_tf_keras_network',
-    '_tf_keras_model', '_tf_keras_sequential', '_tf_keras_metric',
-    '_tf_keras_rnn_layer')
-
-
 def load(path, compile=True, options=None):  # pylint: disable=redefined-builtin
   """Loads Keras objects from a SavedModel.
 
@@ -196,7 +190,7 @@ def _read_legacy_metadata(object_graph_def, metadata):
   node_paths = _generate_object_paths(object_graph_def)
   for node_id, proto in enumerate(object_graph_def.nodes):
     if (proto.WhichOneof('kind') == 'user_object' and
-        proto.user_object.identifier in KERAS_OBJECT_IDENTIFIERS):
+        proto.user_object.identifier in constants.KERAS_OBJECT_IDENTIFIERS):
       metadata.nodes.add(
           node_id=node_id,
           node_path=node_paths[node_id],
@@ -347,7 +341,7 @@ class KerasObjectLoader(object):
       if (child_proto.user_object.identifier in
           revived_types.registered_identifiers()):
         setter = revived_types.get_setter(child_proto.user_object)
-      elif obj_child._object_identifier in KERAS_OBJECT_IDENTIFIERS:
+      elif obj_child._object_identifier in constants.KERAS_OBJECT_IDENTIFIERS:
         setter = _revive_setter
       else:
         setter = setattr
@@ -384,7 +378,7 @@ class KerasObjectLoader(object):
     # time by creating objects multiple times).
     metric_list = []
     for node_metadata in self._metadata.nodes:
-      if node_metadata.identifier == '_tf_keras_metric':
+      if node_metadata.identifier == constants.METRIC_IDENTIFIER:
         metric_list.append(node_metadata)
         continue
 
@@ -432,7 +426,7 @@ class KerasObjectLoader(object):
 
   def _revive_from_config(self, identifier, metadata, node_id):
     """Revives a layer/model from config, or returns None."""
-    if identifier == '_tf_keras_metric':
+    if identifier == constants.METRIC_IDENTIFIER:
       obj = self._revive_metric_from_config(metadata)
     else:
       obj = (
@@ -921,11 +915,12 @@ def revive_custom_object(identifier, metadata):
     model_class = training_lib_v1.Model
 
   revived_classes = {
-      '_tf_keras_layer': (RevivedLayer, base_layer.Layer),
+      constants.INPUT_LAYER_IDENTIFIER: (
-      '_tf_keras_input_layer': (RevivedInputLayer, input_layer.InputLayer),
+          RevivedInputLayer, input_layer.InputLayer),
-      '_tf_keras_network': (RevivedNetwork, functional_lib.Functional),
+      constants.LAYER_IDENTIFIER: (RevivedLayer, base_layer.Layer),
-      '_tf_keras_model': (RevivedNetwork, model_class),
+      constants.MODEL_IDENTIFIER: (RevivedNetwork, model_class),
-      '_tf_keras_sequential': (RevivedNetwork, models_lib.Sequential),
+      constants.NETWORK_IDENTIFIER: (RevivedNetwork, functional_lib.Functional),
+      constants.SEQUENTIAL_IDENTIFIER: (RevivedNetwork, models_lib.Sequential),
   }
   parent_classes = revived_classes.get(identifier, None)
 

tensorflow/python/keras/saving/saved_model/metric_serialization.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.keras.saving.saved_model import constants
 from tensorflow.python.keras.saving.saved_model import layer_serialization
 from tensorflow.python.keras.utils import generic_utils
 from tensorflow.python.training.tracking import data_structures
@@ -28,7 +29,7 @@ class MetricSavedModelSaver(layer_serialization.LayerSavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_metric'
+    return constants.METRIC_IDENTIFIER
 
   def _python_properties_internal(self):
     metadata = dict(

tensorflow/python/keras/saving/saved_model/model_serialization.py

@@ -29,7 +29,7 @@ class ModelSavedModelSaver(layer_serialization.LayerSavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_model'
+    return constants.MODEL_IDENTIFIER
 
   def _python_properties_internal(self):
     metadata = super(ModelSavedModelSaver, self)._python_properties_internal()
@@ -63,4 +63,4 @@ class SequentialSavedModelSaver(ModelSavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_sequential'
+    return constants.SEQUENTIAL_IDENTIFIER

tensorflow/python/keras/saving/saved_model/network_serialization.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python.keras.saving.saved_model import constants
 from tensorflow.python.keras.saving.saved_model import model_serialization
 
 
@@ -27,4 +28,4 @@ class NetworkSavedModelSaver(model_serialization.ModelSavedModelSaver):
 
   @property
   def object_identifier(self):
-    return '_tf_keras_network'
+    return constants.NETWORK_IDENTIFIER