From 8df4f0ce0acc838dd252ae504d44676c35cb6a6b Mon Sep 17 00:00:00 2001
From: Paul Andrey <paul.andrey@hotmail.fr>
Date: Fri, 13 Mar 2020 16:15:59 +0100
Subject: [PATCH 1/2] Fixed `Wrapper`'s `get_config` and `from_config`.

* `get_config`: properly serialize the wrapped layer.
  This notably fixes issues when wrapping custom layers that have
  been registered using `tf.keras.utils.register_keras_serializable`.
* `from_config`: properly copy input config to avoid side effects.
---
 tensorflow/python/keras/layers/wrappers.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/tensorflow/python/keras/layers/wrappers.py b/tensorflow/python/keras/layers/wrappers.py
index 97b51501b18..3efbdac8729 100644
--- a/tensorflow/python/keras/layers/wrappers.py
+++ b/tensorflow/python/keras/layers/wrappers.py
@@ -68,10 +68,7 @@ class Wrapper(Layer):
 
   def get_config(self):
     config = {
-        'layer': {
-            'class_name': self.layer.__class__.__name__,
-            'config': self.layer.get_config()
-        }
+        'layer': generic_utils.serialize_keras_object(self.layer)
     }
     base_config = super(Wrapper, self).get_config()
     return dict(list(base_config.items()) + list(config.items()))
@@ -80,7 +77,7 @@ class Wrapper(Layer):
   def from_config(cls, config, custom_objects=None):
     from tensorflow.python.keras.layers import deserialize as deserialize_layer  # pylint: disable=g-import-not-at-top
     # Avoid mutating the input dict
-    config = config.copy()
+    config = copy.deepcopy(config)
     layer = deserialize_layer(
         config.pop('layer'), custom_objects=custom_objects)
     return cls(layer, **config)

From bb463f8fa4791dff2ae5a14bd55b378941059292 Mon Sep 17 00:00:00 2001
From: Paul Andrey <paul.andrey@hotmail.fr>
Date: Wed, 25 Mar 2020 15:58:00 +0100
Subject: [PATCH 2/2] Fixed `Bidirectional` serialization.

* Fixed `Bidirectional` de-serialization by skipping super call, as
`copy.deepcopy` cannot handle instantiated layers within a config
dictionary.
* On the side, improved `backward_layer` attribute's serialization
scheme, so that registered custom layers may be re-instantiated.
---
 tensorflow/python/keras/layers/wrappers.py | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/tensorflow/python/keras/layers/wrappers.py b/tensorflow/python/keras/layers/wrappers.py
index 3efbdac8729..bfc564afa27 100644
--- a/tensorflow/python/keras/layers/wrappers.py
+++ b/tensorflow/python/keras/layers/wrappers.py
@@ -423,7 +423,8 @@ class Bidirectional(Wrapper):
       # Keep the custom backward layer config, so that we can save it later. The
       # layer's name might be updated below with prefix 'backward_', and we want
       # to preserve the original config.
-      self._backward_layer_config = backward_layer.get_config()
+      self._backward_layer_config = generic_utils.serialize_keras_object(
+          backward_layer)
 
     self.forward_layer._name = 'forward_' + self.forward_layer.name
     self.backward_layer._name = 'backward_' + self.backward_layer.name
@@ -717,26 +718,26 @@ class Bidirectional(Wrapper):
       config['num_constants'] = self._num_constants
 
     if hasattr(self, '_backward_layer_config'):
-      config['backward_layer'] = {
-          'class_name': self.backward_layer.__class__.__name__,
-          'config': self._backward_layer_config,
-      }
+      config['backward_layer'] = self._backward_layer_config
     base_config = super(Bidirectional, self).get_config()
     return dict(list(base_config.items()) + list(config.items()))
 
   @classmethod
   def from_config(cls, config, custom_objects=None):
     # Instead of updating the input, create a copy and use that.
-    config = config.copy()
+    config = copy.deepcopy(config)
     num_constants = config.pop('num_constants', 0)
+    # Handle forward layer instantiation (as would parent class).
+    from tensorflow.python.keras.layers import deserialize as deserialize_layer  # pylint: disable=g-import-not-at-top
+    config['layer'] = deserialize_layer(
+        config['layer'], custom_objects=custom_objects)
+    # Handle (optional) backward layer instantiation.
     backward_layer_config = config.pop('backward_layer', None)
     if backward_layer_config is not None:
-      from tensorflow.python.keras.layers import deserialize as deserialize_layer  # pylint: disable=g-import-not-at-top
       backward_layer = deserialize_layer(
           backward_layer_config, custom_objects=custom_objects)
       config['backward_layer'] = backward_layer
-
-    layer = super(Bidirectional, cls).from_config(config,
-                                                  custom_objects=custom_objects)
+    # Instantiate the wrapper, adjust it and return it.
+    layer = cls(**config)
     layer._num_constants = num_constants
     return layer