Merge pull request #38339 from feihugis:issue_class_and_config_for_serialized_keras_object

PiperOrigin-RevId: 314589293
Change-Id: I42a04d7d27764aba10bd935e5cd80ab97d2833a8

tensorflow/python/keras/utils/generic_utils.py

@@ -296,6 +296,15 @@ def class_and_config_for_serialized_keras_object(
     raise ValueError('Unknown ' + printable_module_name + ': ' + class_name)
 
   cls_config = config['config']
+  # Check if `cls_config` is a list. If it is a list, return the class and the
+  # associated class configs for recursively deserialization. This case will
+  # happen on the old version of sequential model (e.g. `keras_version` ==
+  # "2.0.6"), which is serialized in a different structure, for example
+  # "{'class_name': 'Sequential',
+  #   'config': [{'class_name': 'Embedding', 'config': ...}, {}, ...]}".
+  if isinstance(cls_config, list):
+    return (cls, cls_config)
+
   deserialized_objects = {}
   for key, item in cls_config.items():
     if isinstance(item, dict) and '__passive_serialization__' in item:

tensorflow/python/keras/utils/generic_utils_test.py

@@ -18,6 +18,8 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import numpy as np
+
 from tensorflow.python import keras
 from tensorflow.python.platform import test
 
@@ -298,6 +300,51 @@ class SerializeKerasObjectTest(test.TestCase):
     self.assertEqual(new_layer.units, 3)
     self.assertIs(new_layer.units.fn, serializable_fn)
 
+  def test_serializable_with_old_config(self):
+    # model config generated by tf-1.2.1
+    old_model_config = {
+        'class_name':
+            'Sequential',
+        'config': [{
+            'class_name': 'Dense',
+            'config': {
+                'name': 'dense_1',
+                'trainable': True,
+                'batch_input_shape': [None, 784],
+                'dtype': 'float32',
+                'units': 32,
+                'activation': 'linear',
+                'use_bias': True,
+                'kernel_initializer': {
+                    'class_name': 'Ones',
+                    'config': {
+                        'dtype': 'float32'
+                    }
+                },
+                'bias_initializer': {
+                    'class_name': 'Zeros',
+                    'config': {
+                        'dtype': 'float32'
+                    }
+                },
+                'kernel_regularizer': None,
+                'bias_regularizer': None,
+                'activity_regularizer': None,
+                'kernel_constraint': None,
+                'bias_constraint': None
+            }
+        }]
+    }
+    old_model = keras.utils.generic_utils.deserialize_keras_object(
+        old_model_config, module_objects={'Sequential': keras.Sequential})
+    new_model = keras.Sequential([
+        keras.layers.Dense(32, input_dim=784, kernel_initializer='Ones'),
+    ])
+    input_data = np.random.normal(2, 1, (5, 784))
+    output = old_model.predict(input_data)
+    expected_output = new_model.predict(input_data)
+    self.assertAllEqual(output, expected_output)
+
 
 class SliceArraysTest(test.TestCase):