Benchmark (#435)

* Add benchmark for GAN

* Add benchmark for GAN

benchmark/benchmark.yaml

+StyleGANv2:
+  dataset_web: https://paddlegan.bj.bcebos.com/datasets/ffhq.tar
+  config: configs/stylegan_v2_256_ffhq.yaml
+  fp_item: fp32
+  bs_item: 3 8
+  total_iters: 300
+  log_interval: 10
+
+FOMM:
+  dataset_web: https://paddlegan.bj.bcebos.com/datasets/fom_test_data.tar
+  config: configs/firstorder_vox_256.yaml
+  fp_item: fp32
+  bs_item: 8 16
+  epochs: 30
+  log_interval: 10

benchmark/run_all.sh

+
+#!usr/bin/env bash
+
+function parse_yaml {
+   local s='[[:space:]]*' w='[a-zA-Z0-9_]*' fs=$(echo @|tr @ '\034')
+   sed -ne "s|^\($s\):|\1|" \
+        -e "s|^\($s\)\($w\)$s:$s[\"']\(.*\)[\"']$s\$|\1$fs\2$fs\3|p" \
+        -e "s|^\($s\)\($w\)$s:$s\(.*\)$s\$|\1$fs\2$fs\3|p"  $1 |
+   awk -F$fs '{
+      indent = length($1)/2;
+      vname[indent] = $2;
+      if (indent == 0) {
+         model_mode_list[model_num]=$2;
+         printf("model_mode_list[%d]=%s\n",(model_num), $2);
+         printf("model_num=%d\n", (model_num+1));
+         model_num=(model_num+1);
+      }
+      for (i in vname) {if (i > indent) {delete vname[i]}}
+      if (length($3) >= 0) {
+         vn=""; for (i=0; i<indent; i++) {vn=(vn)(vname[i])("_")}
+         printf("%s%s=\"%s\"\n",vn, $2, $3);
+      }
+   }'
+}
+eval $(parse_yaml "benchmark/benchmark.yaml")
+
+
+for model_mode in ${model_mode_list[@]}; do
+      eval fp_item_list='$'"${model_mode}_fp_item"
+      eval bs_list='$'"${model_mode}_bs_item"
+      eval config='$'"${model_mode}_config"
+      eval total_iters='$'"${model_mode}_total_iters"
+      eval epochs='$'"${model_mode}_epochs"
+      eval dataset_web='$'"${model_mode}_dataset_web"
+      eval log_interval='$'"${model_mode}_log_interval"
+      wget ${dataset_web} -O data/${model_mode}.tar
+      tar -vxf data/${model_mode}.tar -C data/
+      if [ -n "$total_iters" ]; then
+          mode="total_iters"
+          max_iter=$total_iters
+      else
+          mode="epochs"
+          max_iter=$epochs
+      fi
+      echo ${epochs}
+      for fp_item in ${fp_item_list[@]}; do
+          for bs_item in ${bs_list[@]}
+            do
+            echo "index is speed, 1gpus, begin, ${model_name}"
+            run_mode=sp
+            CUDA_VISIBLE_DEVICES=0 benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} ${mode} ${max_iter} ${model_mode} ${config} ${log_interval}   #  (5min)
+            sleep 60
+            echo "index is speed, 8gpus, run_mode is multi_process, begin, ${model_name}"
+            run_mode=mp
+            CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} ${mode} ${max_iter} ${model_mode} ${config} ${log_interval}
+            sleep 60
+            done
+      done
+done

benchmark/run_benchmark.sh

+#!/usr/bin/env bash
+set -xe
+# 运行示例：CUDA_VISIBLE_DEVICES=0 bash run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 500 ${model_mode}
+# 参数说明
+function _set_params(){
+    run_mode=${1:-"sp"}          # 单卡sp|多卡mp
+    batch_size=${2:-"64"}
+    fp_item=${3:-"fp32"}        # fp32|fp16
+    mode=${4:-"epochs"}
+    max_iter=${5:-"500"}       # 可选，如果需要修改代码提前中断
+    model_name=${6:-"model_name"}
+    config=${7:-"config"}
+    log_interval=${8:-"1"}
+    run_log_path=${TRAIN_LOG_DIR:-$(pwd)}  # TRAIN_LOG_DIR 后续QA设置该参数
+
+#   以下不用修改
+    device=${CUDA_VISIBLE_DEVICES//,/ }
+    arr=(${device})
+    num_gpu_devices=${#arr[*]}
+    log_file=${run_log_path}/${model_name}_${run_mode}_bs${batch_size}_${fp_item}_${num_gpu_devices}
+}
+function _train(){
+    echo "Train on ${num_gpu_devices} GPUs"
+    echo "current CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES, gpus=$num_gpu_devices, batch_size=$batch_size"
+
+    train_cmd="--config-file=${config}
+               -o dataset.train.batch_size=${batch_size}
+               log_config.interval=${log_interval}
+               ${mode}=${max_iter} "
+    case ${run_mode} in
+    sp) train_cmd="python -u tools/main.py "${train_cmd} ;;
+    mp)
+        train_cmd="python -m paddle.distributed.launch --log_dir=./mylog --gpus=$CUDA_VISIBLE_DEVICES tools/main.py "${train_cmd}
+        log_parse_file="mylog/workerlog.0" ;;
+    *) echo "choose run_mode(sp or mp)"; exit 1;
+    esac
+# 以下不用修改
+    timeout 15m ${train_cmd} > ${log_file} 2>&1
+    if [ $? -ne 0 ];then
+        echo -e "${model_name}, FAIL"
+        export job_fail_flag=1
+    else
+        echo -e "${model_name}, SUCCESS"
+        export job_fail_flag=0
+    fi
+    trap 'for pid in $(jobs -pr); do kill -KILL $pid; done' INT QUIT TERM
+
+    if [ $run_mode = "mp" -a -d mylog ]; then
+        rm ${log_file}
+        cp mylog/workerlog.0 ${log_file}
+    fi
+}
+
+_set_params $@
+_train