added support for quantized object and added layer to __init__

Author: julesmuhizi

qkeras/__init__.py

@@ -33,6 +33,7 @@
 #from .qtools.settings import cfg
 from .qconv2d_batchnorm import QConv2DBatchnorm
 from .qdepthwiseconv2d_batchnorm import QDepthwiseConv2DBatchnorm
+from .qdense_batchnorm import QDenseBatchnorm
 
 assert tf.executing_eagerly(), "QKeras requires TF with eager execution mode on"
 

qkeras/utils.py

@@ -42,6 +42,7 @@
 from .qlayers import Clip
 from .qconv2d_batchnorm import QConv2DBatchnorm
 from .qdepthwiseconv2d_batchnorm import QDepthwiseConv2DBatchnorm
+from .qdense_batchnorm import QDenseBatchnorm
 from .qlayers import QActivation
 from .qlayers import QAdaptiveActivation
 from .qpooling import QAveragePooling2D
@@ -97,6 +98,7 @@
     "QDepthwiseConv2DBatchnorm",
     "QAveragePooling2D",
     "QGlobalAveragePooling2D",
+    "QDenseBatchnorm",
 ]
 
 
@@ -854,6 +856,8 @@ def _add_supported_quantized_objects(custom_objects):
   custom_objects["QConv2DBatchnorm"] = QConv2DBatchnorm
   custom_objects["QDepthwiseConv2DBatchnorm"] = QDepthwiseConv2DBatchnorm
 
+  custom_objects["QDenseBatchnorm"] = QDenseBatchnorm
+
   custom_objects["QAveragePooling2D"] = QAveragePooling2D
   custom_objects["QGlobalAveragePooling2D"] = QGlobalAveragePooling2D