diff --git a/test/test.sh b/test/test.sh index b95b8ead2b4c0fe5fde32aef5289db037a67d06a..52afbbb3e2454d2e959c59871232c48b8ba0b36f 100644 --- a/test/test.sh +++ b/test/test.sh @@ -110,7 +110,7 @@ function func_inference(){ for threads in ${cpu_threads_list[*]}; do for batch_size in ${batch_size_list[*]}; do _save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}" - command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path}" + command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True" eval $command status_check $? "${command}" "${status_log}" done @@ -124,7 +124,7 @@ function func_inference(){ fi for batch_size in ${batch_size_list[*]}; do _save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}" - command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path}" + command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True" eval $command status_check $? "${command}" "${status_log}" done @@ -138,9 +138,9 @@ if [ ${MODE} != "infer" ]; then IFS="|" for gpu in ${gpu_list[*]}; do - use_gpu=True + train_use_gpu=True if [ ${gpu} = "-1" ];then - use_gpu=False + train_use_gpu=False env="" elif [ ${#gpu} -le 1 ];then env="export CUDA_VISIBLE_DEVICES=${gpu}" @@ -181,7 +181,7 @@ for gpu in ${gpu_list[*]}; do save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}" if [ ${#gpu} -le 2 ];then # epoch_num #TODO - cmd="${python} ${run_train} ${train_use_gpu_key}=${use_gpu} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num} ${save_model_key}=${save_log} " + cmd="${python} ${run_train} ${train_use_gpu_key}=${train_use_gpu} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num} ${save_model_key}=${save_log} " elif [ ${#gpu} -le 15 ];then cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${autocast_key}=${autocast} ${epoch_key}=${epoch_num} ${save_model_key}=${save_log}" else