Update naming of embedding in callback for TensorBoard integration.

PiperOrigin-RevId: 314693951
Change-Id: I6a3aba5b98ce6865da8814eda554bac1fb6bcaea

tensorflow/python/keras/callbacks.py

@@ -2000,7 +2000,10 @@ class TensorBoard(Callback, version_utils.TensorBoardVersionSelector):
     for layer in self.model.layers:
       if isinstance(layer, embeddings.Embedding):
         embedding = config.embeddings.add()
-        embedding.tensor_name = layer.name + '/.ATTRIBUTES/VARIABLE_VALUE'
+        # Embeddings are always the first layer, so this naming should be
+        # consistent in any keras models checkpoints.
+        name = 'layer_with_weights-0/embeddings/.ATTRIBUTES/VARIABLE_VALUE'
+        embedding.tensor_name = name
 
         if self.embeddings_metadata is not None:
           if isinstance(self.embeddings_metadata, str):

tensorflow/python/keras/callbacks_test.py

@@ -1975,12 +1975,12 @@ class TestTensorBoardV2(keras_parameterized.TestCase):
         callbacks=[tb_cbk])
 
     with open(os.path.join(self.logdir, 'projector_config.pbtxt')) as f:
-      self.assertEqual(
-          f.readlines(), [
-              'embeddings {\n',
-              '  tensor_name: "test_embedding/.ATTRIBUTES/VARIABLE_VALUE"\n',
-              '  metadata_path: "metadata.tsv"\n',
-              '}\n'])
+      self.assertEqual(f.readlines(), [
+          'embeddings {\n',
+          ('  tensor_name: '
+           '"layer_with_weights-0/embeddings/.ATTRIBUTES/VARIABLE_VALUE"\n'),
+          '  metadata_path: "metadata.tsv"\n', '}\n'
+      ])
 
   def test_custom_summary(self):
     if not context.executing_eagerly():

tensorflow/python/keras/protobuf/projector_config.proto

@@ -13,6 +13,10 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
+// This file is a copy of the TensorBoard ProjectorConfig proto.
+// Keep this file in sync with the source proto definition at
+// https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/projector/projector_config.proto
+
 syntax = "proto3";
 
 package third_party.tensorflow.python.keras.protobuf;