add mkldnn_lrn python interface and add it to simple net

paddle/gserver/tests/mkldnn_simple_net.conf

@@ -51,6 +51,8 @@ tmp = img_pool_layer(input=tmp,
             padding=1,
             pool_type=MaxPooling())
 
+tmp = img_cmrnorm_layer(input=tmp, size=5, scale=0.0001, power=0.75)
+
 tmp = fc_layer(input=tmp,
             size=channels,
             bias_attr=False,

python/paddle/trainer/config_parser.py

@@ -2287,11 +2287,17 @@ class Conv3DLayer(Conv3DLayerBase):
 class NormLayer(LayerBase):
     def __init__(self, name, inputs, **xargs):
         super(NormLayer, self).__init__(name, 'norm', 0, inputs=inputs, **xargs)
+        use_mkldnn = bool(int(g_command_config_args.get("use_mkldnn", 0)))
+        use_mkldnn = True if use_mkldnn and self.inputs[
+            0].norm.norm_type == 'cmrnorm-projection' else False
+        self.config.type = 'mkldnn_lrn' if use_mkldnn else self.config.type
         for input_index in xrange(len(self.inputs)):
             input_layer = self.get_input_layer(input_index)
             norm_conf = self.config.inputs[input_index].norm_conf
             parse_norm(self.inputs[input_index].norm, input_layer.name,
                        norm_conf)
+            norm_conf.scale = self.inputs[
+                input_index].norm.scale if use_mkldnn else norm_conf.scale
             self.set_cnn_layer(name, norm_conf.output_y, norm_conf.output_x,
                                norm_conf.channels, False)
             if norm_conf.norm_type == "cross-channel-norm":