From 6c5f928a3e099eb787111c8fe5120118ef2e5155 Mon Sep 17 00:00:00 2001
From: tensor-tang <jian.j.tang@intel.com>
Date: Mon, 27 Nov 2017 14:27:25 +0800
Subject: [PATCH 1/5] enable inference benchmark

---
 benchmark/paddle/image/googlenet.py  |  2 +-
 benchmark/paddle/image/resnet.py     |  2 +-
 benchmark/paddle/image/run_mkldnn.sh | 69 ++++++++++++++++++++++++++--
 benchmark/paddle/image/vgg.py        |  2 +-
 4 files changed, 68 insertions(+), 7 deletions(-)

diff --git a/benchmark/paddle/image/googlenet.py b/benchmark/paddle/image/googlenet.py
index a88ecac67d9e6..5b1f0ca0068a5 100644
--- a/benchmark/paddle/image/googlenet.py
+++ b/benchmark/paddle/image/googlenet.py
@@ -9,7 +9,7 @@
 
 args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
 define_py_data_sources2(
-    "train.list", None, module="provider", obj="process", args=args)
+    "train.list", "test.list", module="provider", obj="process", args=args)
 
 settings(
     batch_size=batch_size,
diff --git a/benchmark/paddle/image/resnet.py b/benchmark/paddle/image/resnet.py
index 6ae1857642e8d..f8c1c2df885d7 100644
--- a/benchmark/paddle/image/resnet.py
+++ b/benchmark/paddle/image/resnet.py
@@ -10,7 +10,7 @@
 
 args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
 define_py_data_sources2(
-    "train.list", None, module="provider", obj="process", args=args)
+    "train.list", "test.list", module="provider", obj="process", args=args)
 
 settings(
     batch_size=batch_size,
diff --git a/benchmark/paddle/image/run_mkldnn.sh b/benchmark/paddle/image/run_mkldnn.sh
index f768f6c29a84b..c78079fa45d62 100755
--- a/benchmark/paddle/image/run_mkldnn.sh
+++ b/benchmark/paddle/image/run_mkldnn.sh
@@ -8,13 +8,13 @@ function train() {
   use_mkldnn=$4
   if [ $4 == "True" ]; then
     thread=1
-    log="logs/${topology}-${layer_num}-mkldnn-${bs}.log"
+    log="logs/train-${topology}-${layer_num}-mkldnn-${bs}.log"
   elif [ $4 == "False" ]; then
     thread=`nproc`
     # each trainer_count use only 1 core to avoid conflict
-    log="logs/${topology}-${layer_num}-${thread}mklml-${bs}.log"
+    log="logs/train-${topology}-${layer_num}-${thread}mklml-${bs}.log"
   else
-    echo "Wrong input $3, use True or False."
+    echo "Wrong input $4, use True or False."
     exit 0
   fi
   args="batch_size=${bs},layer_num=${layer_num}"
@@ -30,13 +30,74 @@ function train() {
     2>&1 | tee ${log} 
 }
 
-if [ ! -d "train.list" ]; then
+function test() {
+  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
+  topology=$1
+  layer_num=$2
+  bs=$3
+  use_mkldnn=$4
+  if [ $4 == "True" ]; then
+    thread=1
+    log="logs/test-${topology}-${layer_num}-mkldnn-${bs}.log"
+  elif [ $4 == "False" ]; then
+    thread=`nproc`
+    if [ $thread -gt $bs ]; then
+      thread=$bs
+    fi
+    log="logs/test-${topology}-${layer_num}-${thread}mklml-${bs}.log"
+  else
+    echo "Wrong input $4, use True or False."
+    exit 0
+  fi
+
+  models_in="models/${topology}-${layer_num}/pass-00000/"
+  if [ ! -d $models_in ]; then
+    echo "Training model ${topology}_${layer_num}"
+    paddle train --job=train \
+      --config="${topology}.py" \
+      --use_mkldnn=True \
+      --use_gpu=False \
+      --trainer_count=1 \
+      --num_passes=1 \
+      --save_dir="models/${topology}-${layer_num}" \
+      --config_args="batch_size=128,layer_num=${layer_num}" \
+      > /dev/null 2>&1
+    echo "Done"
+  fi
+  paddle train --job=test \
+    --config="${topology}.py" \
+    --use_mkldnn=$use_mkldnn \
+    --use_gpu=False \
+    --trainer_count=$thread \
+    --log_period=10 \
+    --config_args="batch_size=${bs},layer_num=${layer_num},is_test=True" \
+    --init_model_path=$models_in \
+    2>&1 | tee ${log} 
+}
+
+if [ ! -f "train.list" ]; then
   echo " " > train.list
 fi
+if [ ! -f "test.list" ]; then
+  echo " " > test.list
+fi
 if [ ! -d "logs" ]; then
   mkdir logs
 fi
+if [ ! -d "models" ]; then
+  mkdir -p models
+fi
+
+# inference benchmark
+for use_mkldnn in True False; do
+  for batchsize in 1 2 4 8 16; do
+    test googlenet v1 $batchsize $use_mkldnn
+    test resnet 50 $batchsize $use_mkldnn
+    test vgg 19 $batchsize $use_mkldnn
+  done
+done
 
+# training benchmark
 for use_mkldnn in True False; do
   for batchsize in 64 128 256; do
     train vgg 19 $batchsize $use_mkldnn
diff --git a/benchmark/paddle/image/vgg.py b/benchmark/paddle/image/vgg.py
index 420884ed8e1ae..97f4dbe0e1aaf 100644
--- a/benchmark/paddle/image/vgg.py
+++ b/benchmark/paddle/image/vgg.py
@@ -9,7 +9,7 @@
 
 args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
 define_py_data_sources2(
-    "train.list", None, module="provider", obj="process", args=args)
+    "train.list", "test.list", module="provider", obj="process", args=args)
 
 settings(
     batch_size=batch_size,

From 849bf9d0d0ebf7ab6509a588b8e1b28e9f4d3d67 Mon Sep 17 00:00:00 2001
From: tensor-tang <jian.j.tang@intel.com>
Date: Thu, 30 Nov 2017 14:17:25 +0800
Subject: [PATCH 2/5] separate mkldnn benchmark as train and infer

---
 benchmark/paddle/image/run_mkldnn.sh       | 107 ---------------------
 benchmark/paddle/image/run_mkldnn_infer.sh |  68 +++++++++++++
 benchmark/paddle/image/run_mkldnn_train.sh |  47 +++++++++
 3 files changed, 115 insertions(+), 107 deletions(-)
 delete mode 100755 benchmark/paddle/image/run_mkldnn.sh
 create mode 100755 benchmark/paddle/image/run_mkldnn_infer.sh
 create mode 100755 benchmark/paddle/image/run_mkldnn_train.sh

diff --git a/benchmark/paddle/image/run_mkldnn.sh b/benchmark/paddle/image/run_mkldnn.sh
deleted file mode 100755
index c78079fa45d62..0000000000000
--- a/benchmark/paddle/image/run_mkldnn.sh
+++ /dev/null
@@ -1,107 +0,0 @@
-set -e
-
-function train() {
-  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
-  topology=$1
-  layer_num=$2
-  bs=$3
-  use_mkldnn=$4
-  if [ $4 == "True" ]; then
-    thread=1
-    log="logs/train-${topology}-${layer_num}-mkldnn-${bs}.log"
-  elif [ $4 == "False" ]; then
-    thread=`nproc`
-    # each trainer_count use only 1 core to avoid conflict
-    log="logs/train-${topology}-${layer_num}-${thread}mklml-${bs}.log"
-  else
-    echo "Wrong input $4, use True or False."
-    exit 0
-  fi
-  args="batch_size=${bs},layer_num=${layer_num}"
-  config="${topology}.py"
-  paddle train --job=time \
-    --config=$config \
-    --use_mkldnn=$use_mkldnn \
-    --use_gpu=False \
-    --trainer_count=$thread \
-    --log_period=10 \
-    --test_period=100 \
-    --config_args=$args \
-    2>&1 | tee ${log} 
-}
-
-function test() {
-  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
-  topology=$1
-  layer_num=$2
-  bs=$3
-  use_mkldnn=$4
-  if [ $4 == "True" ]; then
-    thread=1
-    log="logs/test-${topology}-${layer_num}-mkldnn-${bs}.log"
-  elif [ $4 == "False" ]; then
-    thread=`nproc`
-    if [ $thread -gt $bs ]; then
-      thread=$bs
-    fi
-    log="logs/test-${topology}-${layer_num}-${thread}mklml-${bs}.log"
-  else
-    echo "Wrong input $4, use True or False."
-    exit 0
-  fi
-
-  models_in="models/${topology}-${layer_num}/pass-00000/"
-  if [ ! -d $models_in ]; then
-    echo "Training model ${topology}_${layer_num}"
-    paddle train --job=train \
-      --config="${topology}.py" \
-      --use_mkldnn=True \
-      --use_gpu=False \
-      --trainer_count=1 \
-      --num_passes=1 \
-      --save_dir="models/${topology}-${layer_num}" \
-      --config_args="batch_size=128,layer_num=${layer_num}" \
-      > /dev/null 2>&1
-    echo "Done"
-  fi
-  paddle train --job=test \
-    --config="${topology}.py" \
-    --use_mkldnn=$use_mkldnn \
-    --use_gpu=False \
-    --trainer_count=$thread \
-    --log_period=10 \
-    --config_args="batch_size=${bs},layer_num=${layer_num},is_test=True" \
-    --init_model_path=$models_in \
-    2>&1 | tee ${log} 
-}
-
-if [ ! -f "train.list" ]; then
-  echo " " > train.list
-fi
-if [ ! -f "test.list" ]; then
-  echo " " > test.list
-fi
-if [ ! -d "logs" ]; then
-  mkdir logs
-fi
-if [ ! -d "models" ]; then
-  mkdir -p models
-fi
-
-# inference benchmark
-for use_mkldnn in True False; do
-  for batchsize in 1 2 4 8 16; do
-    test googlenet v1 $batchsize $use_mkldnn
-    test resnet 50 $batchsize $use_mkldnn
-    test vgg 19 $batchsize $use_mkldnn
-  done
-done
-
-# training benchmark
-for use_mkldnn in True False; do
-  for batchsize in 64 128 256; do
-    train vgg 19 $batchsize $use_mkldnn
-    train resnet 50 $batchsize $use_mkldnn
-    train googlenet v1 $batchsize $use_mkldnn
-  done
-done
diff --git a/benchmark/paddle/image/run_mkldnn_infer.sh b/benchmark/paddle/image/run_mkldnn_infer.sh
new file mode 100755
index 0000000000000..3081d5e7b549d
--- /dev/null
+++ b/benchmark/paddle/image/run_mkldnn_infer.sh
@@ -0,0 +1,68 @@
+set -e
+
+function infer() {
+  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
+  topology=$1
+  layer_num=$2
+  bs=$3
+  use_mkldnn=$4
+  if [ $4 == "True" ]; then
+    thread=1
+    log="logs/infer-${topology}-${layer_num}-mkldnn-${bs}.log"
+  elif [ $4 == "False" ]; then
+    thread=`nproc`
+    if [ $thread -gt $bs ]; then
+      thread=$bs
+    fi
+    log="logs/infer-${topology}-${layer_num}-${thread}mklml-${bs}.log"
+  else
+    echo "Wrong input $4, use True or False."
+    exit 0
+  fi
+
+  models_in="models/${topology}-${layer_num}/pass-00000/"
+  if [ ! -d $models_in ]; then
+    echo "Training model ${topology}_${layer_num}"
+    paddle train --job=train \
+      --config="${topology}.py" \
+      --use_mkldnn=True \
+      --use_gpu=False \
+      --trainer_count=1 \
+      --num_passes=1 \
+      --save_dir="models/${topology}-${layer_num}" \
+      --config_args="batch_size=128,layer_num=${layer_num}" \
+      > /dev/null 2>&1
+    echo "Done"
+  fi
+  paddle train --job=test \
+    --config="${topology}.py" \
+    --use_mkldnn=$use_mkldnn \
+    --use_gpu=False \
+    --trainer_count=$thread \
+    --log_period=32 \
+    --config_args="batch_size=${bs},layer_num=${layer_num},is_infer=True" \
+    --init_model_path=$models_in \
+    2>&1 | tee ${log} 
+}
+
+if [ ! -f "train.list" ]; then
+  echo " " > train.list
+fi
+if [ ! -f "test.list" ]; then
+  echo " " > test.list
+fi
+if [ ! -d "logs" ]; then
+  mkdir logs
+fi
+if [ ! -d "models" ]; then
+  mkdir -p models
+fi
+
+# inference benchmark
+for use_mkldnn in True False; do
+  for batchsize in 1 2 4 8 16; do
+    infer googlenet v1 $batchsize $use_mkldnn
+    infer resnet 50 $batchsize $use_mkldnn
+    infer vgg 19 $batchsize $use_mkldnn
+  done
+done
diff --git a/benchmark/paddle/image/run_mkldnn_train.sh b/benchmark/paddle/image/run_mkldnn_train.sh
new file mode 100755
index 0000000000000..320206239ae96
--- /dev/null
+++ b/benchmark/paddle/image/run_mkldnn_train.sh
@@ -0,0 +1,47 @@
+set -e
+
+function train() {
+  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
+  topology=$1
+  layer_num=$2
+  bs=$3
+  use_mkldnn=$4
+  if [ $4 == "True" ]; then
+    thread=1
+    log="logs/train-${topology}-${layer_num}-mkldnn-${bs}.log"
+  elif [ $4 == "False" ]; then
+    thread=`nproc`
+    # each trainer_count use only 1 core to avoid conflict
+    log="logs/train-${topology}-${layer_num}-${thread}mklml-${bs}.log"
+  else
+    echo "Wrong input $4, use True or False."
+    exit 0
+  fi
+  args="batch_size=${bs},layer_num=${layer_num}"
+  config="${topology}.py"
+  paddle train --job=time \
+    --config=$config \
+    --use_mkldnn=$use_mkldnn \
+    --use_gpu=False \
+    --trainer_count=$thread \
+    --log_period=10 \
+    --test_period=100 \
+    --config_args=$args \
+    2>&1 | tee ${log} 
+}
+
+if [ ! -f "train.list" ]; then
+  echo " " > train.list
+fi
+if [ ! -d "logs" ]; then
+  mkdir logs
+fi
+
+# training benchmark
+for use_mkldnn in True False; do
+  for batchsize in 64 128 256; do
+    train vgg 19 $batchsize $use_mkldnn
+    train resnet 50 $batchsize $use_mkldnn
+    train googlenet v1 $batchsize $use_mkldnn
+  done
+done

From a5aac614108c4b2b6d88d0c3446e4184911a319c Mon Sep 17 00:00:00 2001
From: tensor-tang <jian.j.tang@intel.com>
Date: Thu, 30 Nov 2017 14:24:35 +0800
Subject: [PATCH 3/5] skip cost when inference

---
 benchmark/paddle/image/googlenet.py | 20 +++++++++++++++-----
 benchmark/paddle/image/provider.py  | 14 ++++++++++----
 benchmark/paddle/image/resnet.py    | 27 +++++++++++++++++++--------
 benchmark/paddle/image/vgg.py       | 18 ++++++++++++++----
 4 files changed, 58 insertions(+), 21 deletions(-)

diff --git a/benchmark/paddle/image/googlenet.py b/benchmark/paddle/image/googlenet.py
index 5b1f0ca0068a5..d3dc0506d58dc 100644
--- a/benchmark/paddle/image/googlenet.py
+++ b/benchmark/paddle/image/googlenet.py
@@ -6,8 +6,15 @@
 num_class = 1000
 batch_size = get_config_arg('batch_size', int, 128)
 use_gpu = get_config_arg('use_gpu', bool, True)
-
-args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
+is_infer = get_config_arg("is_infer", bool, False)
+
+args = {
+    'height': height,
+    'width': width,
+    'color': True,
+    'num_class': num_class,
+    'is_infer': is_infer
+}
 define_py_data_sources2(
     "train.list", "test.list", module="provider", obj="process", args=args)
 
@@ -146,7 +153,6 @@ def inception(name, input, channels, \
     return cat
 
 
-lab = data_layer(name="label", size=1000)
 data = data_layer(name="input", size=3 * height * width)
 
 # stage 1
@@ -224,6 +230,10 @@ def inception(name, input, channels, \
 dropout = dropout_layer(name="dropout", input=pool5, dropout_rate=0.4)
 out3 = fc_layer(
     name="output3", input=dropout, size=1000, act=SoftmaxActivation())
-loss3 = cross_entropy(name='loss3', input=out3, label=lab)
 
-outputs(loss3)
+if is_infer:
+    outputs(out3)
+else:
+    lab = data_layer(name="label", size=num_class)
+    loss3 = cross_entropy(name='loss3', input=out3, label=lab)
+    outputs(loss3)
diff --git a/benchmark/paddle/image/provider.py b/benchmark/paddle/image/provider.py
index 4703944c87225..a3a6b6fc4d1ee 100644
--- a/benchmark/paddle/image/provider.py
+++ b/benchmark/paddle/image/provider.py
@@ -13,8 +13,11 @@ def initHook(settings, height, width, color, num_class, **kwargs):
         settings.data_size = settings.height * settings.width * 3
     else:
         settings.data_size = settings.height * settings.width
-
-    settings.slots = [dense_vector(settings.data_size), integer_value(1)]
+    settings.is_infer = kwargs.get('is_infer', False)
+    if settings.is_infer:
+        settings.slots = [dense_vector(settings.data_size)]
+    else:
+        settings.slots = [dense_vector(settings.data_size), integer_value(1)]
 
 
 @provider(
@@ -22,5 +25,8 @@ def initHook(settings, height, width, color, num_class, **kwargs):
 def process(settings, file_list):
     for i in xrange(1024):
         img = np.random.rand(1, settings.data_size).reshape(-1, 1).flatten()
-        lab = random.randint(0, settings.num_class - 1)
-        yield img.astype('float32'), int(lab)
+        if settings.is_infer:
+            yield img.astype('float32')
+        else:
+            lab = random.randint(0, settings.num_class - 1)
+            yield img.astype('float32'), int(lab)
diff --git a/benchmark/paddle/image/resnet.py b/benchmark/paddle/image/resnet.py
index f8c1c2df885d7..163394e5660da 100644
--- a/benchmark/paddle/image/resnet.py
+++ b/benchmark/paddle/image/resnet.py
@@ -6,9 +6,15 @@
 num_class = 1000
 batch_size = get_config_arg('batch_size', int, 64)
 layer_num = get_config_arg("layer_num", int, 50)
-is_test = get_config_arg("is_test", bool, False)
-
-args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
+is_infer = get_config_arg("is_infer", bool, False)
+
+args = {
+    'height': height,
+    'width': width,
+    'color': True,
+    'num_class': num_class,
+    'is_infer': is_infer
+}
 define_py_data_sources2(
     "train.list", "test.list", module="provider", obj="process", args=args)
 
@@ -45,7 +51,10 @@ def conv_bn_layer(name,
         act=LinearActivation(),
         bias_attr=False)
     return batch_norm_layer(
-        name=name + "_bn", input=tmp, act=active_type, use_global_stats=is_test)
+        name=name + "_bn",
+        input=tmp,
+        act=active_type,
+        use_global_stats=is_infer)
 
 
 def bottleneck_block(name, input, num_filters1, num_filters2):
@@ -207,7 +216,9 @@ def deep_res_net(res2_num=3, res3_num=4, res4_num=6, res5_num=3):
 else:
     print("Wrong layer number.")
 
-lbl = data_layer(name="label", size=num_class)
-loss = cross_entropy(name='loss', input=resnet, label=lbl)
-inputs(img, lbl)
-outputs(loss)
+if is_infer:
+    outputs(resnet)
+else:
+    lbl = data_layer(name="label", size=num_class)
+    loss = cross_entropy(name='loss', input=resnet, label=lbl)
+    outputs(loss)
diff --git a/benchmark/paddle/image/vgg.py b/benchmark/paddle/image/vgg.py
index 97f4dbe0e1aaf..2d8075bcf2285 100644
--- a/benchmark/paddle/image/vgg.py
+++ b/benchmark/paddle/image/vgg.py
@@ -6,8 +6,15 @@
 num_class = 1000
 batch_size = get_config_arg('batch_size', int, 64)
 layer_num = get_config_arg('layer_num', int, 19)
+is_infer = get_config_arg("is_infer", bool, False)
 
-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
+}
 define_py_data_sources2(
     "train.list", "test.list", module="provider", obj="process", args=args)
 
@@ -98,6 +105,9 @@ def vgg_network(vgg_num=3):
 else:
     print("Wrong layer number.")
 
-lab = data_layer('label', num_class)
-loss = cross_entropy(input=vgg, label=lab)
-outputs(loss)
+if is_infer:
+    outputs(vgg)
+else:
+    lab = data_layer('label', num_class)
+    loss = cross_entropy(input=vgg, label=lab)
+    outputs(loss)

From aef639448c67999e3bfc094c6d39ca528fe193a4 Mon Sep 17 00:00:00 2001
From: tensor-tang <jian.j.tang@intel.com>
Date: Thu, 30 Nov 2017 14:33:43 +0800
Subject: [PATCH 4/5] skip train list when inference, skip test list when
 training

---
 benchmark/paddle/image/googlenet.py | 6 +++++-
 benchmark/paddle/image/resnet.py    | 6 +++++-
 benchmark/paddle/image/vgg.py       | 6 +++++-
 3 files changed, 15 insertions(+), 3 deletions(-)

diff --git a/benchmark/paddle/image/googlenet.py b/benchmark/paddle/image/googlenet.py
index d3dc0506d58dc..7059c13bd2c2b 100644
--- a/benchmark/paddle/image/googlenet.py
+++ b/benchmark/paddle/image/googlenet.py
@@ -16,7 +16,11 @@
     'is_infer': is_infer
 }
 define_py_data_sources2(
-    "train.list", "test.list", module="provider", obj="process", args=args)
+    "train.list" if not is_infer else None,
+    "test.list" if is_infer else None,
+    module="provider",
+    obj="process",
+    args=args)
 
 settings(
     batch_size=batch_size,
diff --git a/benchmark/paddle/image/resnet.py b/benchmark/paddle/image/resnet.py
index 163394e5660da..4a14363ff1db4 100644
--- a/benchmark/paddle/image/resnet.py
+++ b/benchmark/paddle/image/resnet.py
@@ -16,7 +16,11 @@
     'is_infer': is_infer
 }
 define_py_data_sources2(
-    "train.list", "test.list", module="provider", obj="process", args=args)
+    "train.list" if not is_infer else None,
+    "test.list" if is_infer else None,
+    module="provider",
+    obj="process",
+    args=args)
 
 settings(
     batch_size=batch_size,
diff --git a/benchmark/paddle/image/vgg.py b/benchmark/paddle/image/vgg.py
index 2d8075bcf2285..8d0a1e97a451c 100644
--- a/benchmark/paddle/image/vgg.py
+++ b/benchmark/paddle/image/vgg.py
@@ -16,7 +16,11 @@
     'is_infer': is_infer
 }
 define_py_data_sources2(
-    "train.list", "test.list", module="provider", obj="process", args=args)
+    "train.list" if not is_infer else None,
+    "test.list" if is_infer else None,
+    module="provider",
+    obj="process",
+    args=args)
 
 settings(
     batch_size=batch_size,

From 79b17097f65a0c6a0b25eb7385b423c01129f003 Mon Sep 17 00:00:00 2001
From: tensor-tang <jian.j.tang@intel.com>
Date: Fri, 1 Dec 2017 00:27:43 +0800
Subject: [PATCH 5/5] cal FPS of inference result

---
 benchmark/paddle/image/provider.py         |  2 +-
 benchmark/paddle/image/run_mkldnn_infer.sh | 22 ++++++++++++++++++++--
 2 files changed, 21 insertions(+), 3 deletions(-)

diff --git a/benchmark/paddle/image/provider.py b/benchmark/paddle/image/provider.py
index a3a6b6fc4d1ee..927b1759941f3 100644
--- a/benchmark/paddle/image/provider.py
+++ b/benchmark/paddle/image/provider.py
@@ -23,7 +23,7 @@ def initHook(settings, height, width, color, num_class, **kwargs):
 @provider(
     init_hook=initHook, min_pool_size=-1, cache=CacheType.CACHE_PASS_IN_MEM)
 def process(settings, file_list):
-    for i in xrange(1024):
+    for i in xrange(2560 if settings.is_infer else 1024):
         img = np.random.rand(1, settings.data_size).reshape(-1, 1).flatten()
         if settings.is_infer:
             yield img.astype('float32')
diff --git a/benchmark/paddle/image/run_mkldnn_infer.sh b/benchmark/paddle/image/run_mkldnn_infer.sh
index 3081d5e7b549d..03a76c0540092 100755
--- a/benchmark/paddle/image/run_mkldnn_infer.sh
+++ b/benchmark/paddle/image/run_mkldnn_infer.sh
@@ -1,5 +1,12 @@
 set -e
 
+function clock_to_seconds() {
+  hours=`echo $1 | awk -F ':' '{print $1}'`
+  mins=`echo $1 | awk -F ':' '{print $2}'`
+  secs=`echo $1 | awk -F ':' '{print $3}'`
+  echo `bc -l <<< "$secs + $mins * 60 + $hours * 3600"`
+}
+
 function infer() {
   unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
   topology=$1
@@ -34,15 +41,26 @@ function infer() {
       > /dev/null 2>&1
     echo "Done"
   fi
+  log_period=$((256 / bs))
   paddle train --job=test \
     --config="${topology}.py" \
     --use_mkldnn=$use_mkldnn \
     --use_gpu=False \
     --trainer_count=$thread \
-    --log_period=32 \
+    --log_period=$log_period \
     --config_args="batch_size=${bs},layer_num=${layer_num},is_infer=True" \
     --init_model_path=$models_in \
-    2>&1 | tee ${log} 
+    2>&1 | tee ${log}
+
+  # calculate the last 5 logs period time of 1280 samples,
+  # the time before are burning time.
+  start=`tail ${log} -n 7 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
+  end=`tail ${log} -n 2 | head -n 1 | awk -F ' ' '{print $2}' | xargs`
+  start_sec=`clock_to_seconds $start`
+  end_sec=`clock_to_seconds $end`
+  fps=`bc <<< "scale = 2; 1280 / ($end_sec - $start_sec)"`
+  echo "Last 1280 samples start: ${start}(${start_sec} sec), end: ${end}(${end_sec} sec;" >> ${log}
+  echo "FPS: $fps images/sec" >> ${log}
 }
 
 if [ ! -f "train.list" ]; then