seperate openblas train/infer script with mkl

benchmark/paddle/image/run_openblas_infer.sh

@@ -0,0 +1,62 @@
+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 $3}'`
+  echo `awk 'BEGIN{printf "%.2f",('$secs' + '$mins' * 60 + '$hours' * 3600)}'`
+}
+
+function infer() {
+  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
+  topology=$1
+  layer_num=$2
+  bs=$3
+  thread=`nproc`
+  if [ $thread -gt $bs ]; then
+    thread=$bs
+  fi
+  log="logs/infer-${topology}-${layer_num}-${thread}openblas-${bs}.log"
+
+  models_in="models/${topology}-${layer_num}/pass-00000/"
+  if [ ! -d $models_in ]; then
+    echo "./run_mkl_infer.sh to save the model first"
+    exit 0
+  fi
+  log_period=$((256 / bs))
+  paddle train --job=test \
+    --config="${topology}.py" \
+    --use_gpu=False \
+    --trainer_count=$thread \
+    --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}
+
+  # 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 $end`
+  fps=`awk 'BEGIN{printf "%.2f",(1280 / ('$end_sec' - '$start_sec'))}'`
+  echo "Last 1280 samples start: ${start}(${start_sec} sec), end: ${end}(${end_sec} sec;" >> ${log}
+  echo "FPS: $fps images/sec" 2>&1 | tee -a ${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
+
+# inference benchmark
+for batchsize in 1 2 4 8 16; do
+  infer googlenet v1 $batchsize
+  infer resnet 50 $batchsize
+  infer vgg 19 $batchsize
+done

benchmark/paddle/image/run_openblas_train.sh

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+set -e
+
+function train() {
+  unset OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
+  topology=$1
+  layer_num=$2
+  bs=$3
+  thread=`nproc`
+  # each trainer_count use only 1 core to avoid conflict
+  log="logs/train-${topology}-${layer_num}-${thread}openblas-${bs}.log"
+  args="batch_size=${bs},layer_num=${layer_num}"
+  config="${topology}.py"
+  paddle train --job=time \
+    --config=$config \
+    --use_gpu=False \
+    --trainer_count=$thread \
+    --log_period=10 \
+    --test_period=100 \
+    --config_args=$args \
+    2>&1 | tee ${log} 
+
+  avg_time=`tail ${log} -n 1 | awk -F ' ' '{print $8}' | sed 's/avg=//'`
+  fps=`awk 'BEGIN{printf "%.2f",('$bs' / '$avg_time' * 1000)}'`
+  echo "FPS: $fps images/sec" 2>&1 | tee -a ${log}
+}
+
+if [ ! -f "train.list" ]; then
+  echo " " > train.list
+fi
+if [ ! -d "logs" ]; then
+  mkdir logs
+fi
+
+# training benchmark
+for batchsize in 64 128 256; do
+  train vgg 19 $batchsize
+  train resnet 50 $batchsize
+  train googlenet v1 $batchsize
+done