Fix issue where the disable_tracking decorator obfuscates layer constructors.

docs/mkdocs.yml

@@ -73,8 +73,6 @@ nav:
   - Baby RNN: examples/babi_rnn.md
   - Baby MemNN: examples/babi_memnn.md
   - CIFAR-10 CNN: examples/cifar10_cnn.md
-  - CIFAR-10 CNN-Capsule: examples/cifar10_cnn_capsule.md
-  - CIFAR-10 CNN with augmentation (TF): examples/cifar10_cnn_tfaugment2d.md
   - CIFAR-10 ResNet: examples/cifar10_resnet.md
   - Convolution filter visualization: examples/conv_filter_visualization.md
   - Convolutional LSTM: examples/conv_lstm.md

keras/layers/normalization.py

@@ -5,7 +5,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from ..engine.base_layer import Layer, InputSpec, disable_tracking
+from ..engine.base_layer import Layer, InputSpec
 from .. import initializers
 from .. import regularizers
 from .. import constraints

keras/layers/recurrent.py

@@ -46,7 +46,6 @@ class StackedRNNCells(Layer):
     ```
     """
 
-    @disable_tracking
     def __init__(self, cells, **kwargs):
         for cell in cells:
             if not hasattr(cell, 'call'):
@@ -391,7 +390,6 @@ class RNN(Layer):
     ```
     """
 
-    @disable_tracking
     def __init__(self, cell,
                  return_sequences=False,
                  return_state=False,
@@ -410,7 +408,7 @@ class RNN(Layer):
                              '(tuple of integers, '
                              'one integer per RNN state).')
         super(RNN, self).__init__(**kwargs)
-        self.cell = cell
+        self._set_cell(cell)
         self.return_sequences = return_sequences
         self.return_state = return_state
         self.go_backwards = go_backwards
@@ -424,6 +422,13 @@ class RNN(Layer):
         self.constants_spec = None
         self._num_constants = None
 
+    @disable_tracking
+    def _set_cell(self, cell):
+        # This is isolated in its own method in order to use
+        # the disable_tracking decorator without altering the
+        # visible signature of __init__.
+        self.cell = cell
+
     @property
     def states(self):
         if self._states is None:

keras/layers/wrappers.py

@@ -360,18 +360,12 @@ class Bidirectional(Wrapper):
     ```
     """
 
-    @disable_tracking
     def __init__(self, layer, merge_mode='concat', weights=None, **kwargs):
         if merge_mode not in ['sum', 'mul', 'ave', 'concat', None]:
             raise ValueError('Invalid merge mode. '
                              'Merge mode should be one of '
                              '{"sum", "mul", "ave", "concat", None}')
-        self.forward_layer = copy.copy(layer)
-        config = layer.get_config()
-        config['go_backwards'] = not config['go_backwards']
-        self.backward_layer = layer.__class__.from_config(config)
-        self.forward_layer.name = 'forward_' + self.forward_layer.name
-        self.backward_layer.name = 'backward_' + self.backward_layer.name
+        self._set_sublayers(layer)
         self.merge_mode = merge_mode
         if weights:
             nw = len(weights)
@@ -386,6 +380,18 @@ class Bidirectional(Wrapper):
         self.input_spec = layer.input_spec
         self._num_constants = None
 
+    @disable_tracking
+    def _set_sublayers(self, layer):
+        # This is isolated in its own method in order to use
+        # the disable_tracking decorator without altering the
+        # visible signature of __init__.
+        self.forward_layer = copy.copy(layer)
+        config = layer.get_config()
+        config['go_backwards'] = not config['go_backwards']
+        self.backward_layer = layer.__class__.from_config(config)
+        self.forward_layer.name = 'forward_' + self.forward_layer.name
+        self.backward_layer.name = 'backward_' + self.backward_layer.name
+
     @property
     def trainable(self):
         return self._trainable