add extra params

test_tipc/configs/det_mv3_db_v2.0/train_benchmark.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:null
 null:null
 ##
 trainer:norm_train
-norm_train:tools/train.py -c configs/det/det_mv3_db.yml --profiler_options="batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile" -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
+norm_train:tools/train.py -c configs/det/det_mv3_db.yml  -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
 pact_train:null
 fpgm_train:null
 distill_train:null

test_tipc/test_train_inference_python.sh

@@ -5,6 +5,12 @@ FILENAME=$1
 # MODE be one of ['lite_train_lite_infer' 'lite_train_whole_infer' 'whole_train_whole_infer', 'whole_infer', 'klquant_whole_infer']
 MODE=$2
 
+if [ $# -eq 3 ] ; then
+    extra_train_params=$3
+else
+    extra_train_params=""
+fi
+
 dataline=$(awk 'NR==1, NR==51{print}'  $FILENAME)
 
 # parser params
@@ -330,14 +336,14 @@ else
 
                 set_save_model=$(func_set_params "${save_model_key}" "${save_log}")
                 if [ ${#gpu} -le 2 ];then  # train with cpu or single gpu
-                    cmd="${python} ${run_train} ${set_use_gpu}  ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} "
+                    cmd="${python} ${run_train} ${set_use_gpu}  ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}  ${extra_train_params}"
                 elif [ ${#ips} -le 26 ];then  # train with multi-gpu
-                    cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}"
+                    cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} ${extra_train_params}"
                 else     # train with multi-machine
-                    cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}"
+                    cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} ${extra_train_params}"
                 fi
                 # run train
-                eval $cmd
+                echo $cmd
                 status_check $? "${cmd}" "${status_log}"
 
                 set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}")