Add keras LBNLayer.

lbn.py

@@ -13,7 +13,7 @@ __contact__ = "https://git.rwth-aachen.de/3pia/lbn"
 __email__ = "marcel.rieger@cern.ch"
 __version__ = "1.0.3"
 
-__all__ = ["LBN", "FeatureFactoryBase", "FeatureFactory"]
+__all__ = ["LBN", "LBNLayer", "FeatureFactoryBase", "FeatureFactory"]
 
 
 import os
@@ -522,6 +522,29 @@ class LBN(object):
         self._norm_features = self.batch_norm(self.features, training=self.is_training)
 
 
+class LBNLayer(tf.keras.layers.Layer):
+    """
+    Keras layer of the :py:class:`LBN` that forwards the standard interface of :py:meth:`__init__`
+    and py:meth:`__call__`.
+
+    .. py:attribute:: lbn
+       type: LBN
+
+       Reference to the internal :py:class:`LBN` instance that is initialized with the contructor
+       arguments of this class.
+    """
+
+    def __init__(self, *args, **kwargs):
+        super(LBNLayer, self).__init__()
+
+        # create the LBN instalce
+        self.lbn = LBN(*args, **kwargs)
+
+    def __call__(self, *args, **kwargs):
+        # forward to lbn.__call__
+        return self.lbn(*args, **kwargs)
+
+
 class FeatureFactoryBase(object):
     """
     Base class of the feature factory. It does not implement actual features but rather the