未验证 提交 233d05d9 编写于 作者: H hysunflower 提交者: GitHub

update_gan scripts for benchmark (#500)

* update_gan scripts for benchmark

* update_gan scripts for benchmark
上级 3c9dd7b3
......@@ -2,7 +2,7 @@ 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
bs_item: 8
total_iters: 100
log_interval: 5
......@@ -10,7 +10,7 @@ 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
bs_item: 16
epochs: 1
log_interval: 1
......@@ -18,7 +18,7 @@ esrgan:
dataset_web: https://paddlegan.bj.bcebos.com/datasets/DIV2KandSet14.tar
config: configs/esrgan_psnr_x4_div2k.yaml
fp_item: fp32
bs_item: 32 64
bs_item: 32
total_iters: 300
log_interval: 10
......@@ -26,7 +26,7 @@ edvr:
dataset: data/REDS
config: configs/edvr_m_wo_tsa.yaml
fp_item: fp32
bs_item: 4 64
bs_item: 4
total_iters: 300
log_interval: 10
......
#!usr/bin/env bash
export BENCHMARK_ROOT=/workspace
run_env=$BENCHMARK_ROOT/run_env
log_date=`date "+%Y.%m%d.%H%M%S"`
frame=paddle2.1.3
cuda_version=10.2
save_log_dir=${BENCHMARK_ROOT}/logs/${frame}_${log_date}_${cuda_version}/
if [[ -d ${save_log_dir} ]]; then
rm -rf ${save_log_dir}
fi
# this for update the log_path coding mat
export TRAIN_LOG_DIR=${save_log_dir}/train_log
mkdir -p ${TRAIN_LOG_DIR}
log_path=${TRAIN_LOG_DIR}
################################# 配置python, 如:
rm -rf $run_env
mkdir $run_env
echo `which python3.7`
ln -s $(which python3.7)m-config $run_env/python3-config
ln -s $(which python3.7) $run_env/python
ln -s $(which pip3.7) $run_env/pip
export PATH=$run_env:${PATH}
cd $BENCHMARK_ROOT
pip install -v -e .
#!usr/bin/env bash
export BENCHMARK_ROOT=/workspace
run_env=$BENCHMARK_ROOT/run_env
log_date=`date "+%Y.%m%d.%H%M%S"`
frame=paddle2.1.3
cuda_version=10.2
save_log_dir=${BENCHMARK_ROOT}/logs/${frame}_${log_date}_${cuda_version}/
if [[ -d ${save_log_dir} ]]; then
rm -rf ${save_log_dir}
fi
# this for update the log_path coding mat
export TRAIN_LOG_DIR=${save_log_dir}/train_log
mkdir -p ${TRAIN_LOG_DIR}
log_path=${TRAIN_LOG_DIR}
################################# 配置python, 如:
rm -rf $run_env
mkdir $run_env
echo `which python3.7`
ln -s $(which python3.7)m-config $run_env/python3-config
ln -s $(which python3.7) $run_env/python
ln -s $(which pip3.7) $run_env/pip
export PATH=$run_env:${PATH}
cd $BENCHMARK_ROOT
pip install -v -e .
export log_path=${LOG_PATH_INDEX_DIR:-$(pwd)}
function parse_yaml {
local s='[[:space:]]*' w='[a-zA-Z0-9_]*' fs=$(echo @|tr @ '\034')
......@@ -79,17 +51,17 @@ for model_mode in ${model_mode_list[@]}; do
for fp_item in ${fp_item_list[@]}; do
for bs_item in ${bs_list[@]}
do
echo "index is speed, 1gpus, begin, ${model_name}"
echo "index is speed, 1gpus, begin, ${model_mode}"
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} ${profile} # (5min)
CUDA_VISIBLE_DEVICES=0 benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} ${mode} ${max_iter} ${model_mode} ${config} ${log_interval} ${profile} | tee ${log_path}/gan_dygraph_${model_mode}_${run_mode}_bs${bs_item}_${fp_item}_speed_1gpus 2>&1 # (5min)
sleep 60
echo "index is speed, 8gpus, run_mode is multi_process, begin, ${model_name}"
echo "index is speed, 8gpus, run_mode is multi_process, begin, ${model_mode}"
run_mode=mp
basicvsr_name=basicvsr
if [ ${model_mode} = ${basicvsr_name} ]; then
CUDA_VISIBLE_DEVICES=0,1,2,3 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} ${mode} ${max_iter} ${model_mode} ${config} ${log_interval} ${profile}
CUDA_VISIBLE_DEVICES=0,1,2,3 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} ${mode} ${max_iter} ${model_mode} ${config} ${log_interval} ${profile} | tee ${log_path}/gan_dygraph_${model_mode}_${run_mode}_bs${bs_item}_${fp_item}_speed_4gpus4p 2>&1
else
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} ${profile}
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} ${profile} | tee ${log_path}/gan_dygraph_${model_mode}_${run_mode}_bs${bs_item}_${fp_item}_speed_8gpus8p 2>&1
fi
sleep 60
done
......
......@@ -14,6 +14,15 @@ function _set_params(){
run_log_path=${TRAIN_LOG_DIR:-$(pwd)} # TRAIN_LOG_DIR 后续QA设置该参数
need_profile=${9:-"off"}
index=1
base_batch_size=${batch_size}
mission_name="图像生成"
direction_id=0
keyword="ips:"
keyword_loss="G_idt_A_loss:"
skip_steps=5
ips_unit="images/s"
# 以下不用修改
device=${CUDA_VISIBLE_DEVICES//,/ }
arr=(${device})
......@@ -23,9 +32,6 @@ function _set_params(){
log_profile=${run_log_path}/${model_name}_model.profile
}
function _analysis_log(){
python benchmark/analysis_log.py ${model_name} ${log_file} ${res_log_file}
}
function _train(){
echo "Train on ${num_gpu_devices} GPUs"
......@@ -65,9 +71,8 @@ function _train(){
cp mylog/workerlog.0 ${log_file}
fi
_analysis_log
}
source ${BENCHMARK_ROOT}/scripts/run_model.sh # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;该脚本在连调时可从benchmark repo中下载https://github.com/PaddlePaddle/benchmark/blob/master/scripts/run_model.sh;如果不联调只想要产出训练log可以注掉本行,提交时需打开
_set_params $@
_train
_run
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