enable alexnet benchmark

benchmark/paddle/image/alexnet.py

@@ -6,8 +6,18 @@
 width = 227
 num_class = 1000
 batch_size = get_config_arg('batch_size', int, 128)
+use_mkldnn = get_config_arg('use_mkldnn', bool, False)
+is_infer = get_config_arg("is_infer", bool, False)
+num_samples = get_config_arg('num_samples', int, 2560)
 
-args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
+args = {
+    'height': height,
+    'width': width,
+    'color': True,
+    'num_class': num_class,
+    'is_infer': is_infer,
+    'num_samples': num_samples
+}
 define_py_data_sources2(
     "train.list", None, module="provider", obj="process", args=args)
 
@@ -31,7 +41,12 @@
 
 # conv2
 net = img_conv_layer(
-    input=net, filter_size=5, num_filters=256, stride=1, padding=2, groups=1)
+    input=net,
+    filter_size=5,
+    num_filters=256,
+    stride=1,
+    padding=2,
+    groups=2 if use_mkldnn else 1)
 net = img_cmrnorm_layer(input=net, size=5, scale=0.0001, power=0.75)
 net = img_pool_layer(input=net, pool_size=3, stride=2)
 
@@ -40,11 +55,21 @@
     input=net, filter_size=3, num_filters=384, stride=1, padding=1)
 # conv4
 net = img_conv_layer(
-    input=net, filter_size=3, num_filters=384, stride=1, padding=1, groups=1)
+    input=net,
+    filter_size=3,
+    num_filters=384,
+    stride=1,
+    padding=1,
+    groups=2 if use_mkldnn else 1)
 
 # conv5
 net = img_conv_layer(
-    input=net, filter_size=3, num_filters=256, stride=1, padding=1, groups=1)
+    input=net,
+    filter_size=3,
+    num_filters=256,
+    stride=1,
+    padding=1,
+    groups=2 if use_mkldnn else 1)
 net = img_pool_layer(input=net, pool_size=3, stride=2)
 
 net = fc_layer(

benchmark/paddle/image/run_mkl_infer.sh

@@ -79,6 +79,7 @@ fi
 # inference benchmark
 for use_mkldnn in True False; do
   for batchsize in 1 2 4 8 16; do
+    infer alexnet group2 $batchsize $use_mkldnn
     infer googlenet v1 $batchsize $use_mkldnn
     infer resnet 50 $batchsize $use_mkldnn
     infer vgg 19 $batchsize $use_mkldnn

benchmark/paddle/image/run_mkl_train.sh

@@ -47,5 +47,6 @@ for use_mkldnn in True False; do
     train vgg 19 $batchsize $use_mkldnn
     train resnet 50 $batchsize $use_mkldnn
     train googlenet v1 $batchsize $use_mkldnn
+    train alexnet group2 $batchsize $use_mkldnn
   done
 done

benchmark/paddle/image/run_openblas_infer.sh

@@ -56,6 +56,7 @@ fi
 
 # inference benchmark
 for batchsize in 1 2 4 8 16; do
+  infer alexnet group2 $batchsize $use_mkldnn
   infer googlenet v1 $batchsize
   infer resnet 50 $batchsize
   infer vgg 19 $batchsize

benchmark/paddle/image/run_openblas_train.sh

@@ -36,4 +36,5 @@ for batchsize in 64 128 256; do
   train vgg 19 $batchsize
   train resnet 50 $batchsize
   train googlenet v1 $batchsize
+  train alexnet group2 $batchsize $use_mkldnn
 done