revert > train.log

test_tipc/test_train_inference_python.sh

@@ -317,25 +317,25 @@ else
                 set_train_params1=$(func_set_params "${train_param_key1}" "${train_param_value1}")
                 set_use_gpu=$(func_set_params "${train_use_gpu_key}" "${train_use_gpu}")
                 if [ ${#ips} -le 26 ];then
-                    save_log="${LOG_PATH}/${model_name}_gpus_${gpu}_autocast_${autocast}_bs_${train_batch_value}_sp"
+                    save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}"
                     nodes=1
                 else
                     IFS=","
                     ips_array=(${ips})
                     IFS="|"
                     nodes=${#ips_array[@]}
-                    save_log="${LOG_PATH}/${model_name}_gpus_${gpu}_autocast_${autocast}_bs_${train_batch_value}_mp"
+                    save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}"
                 fi
 
                 btrain_log="${LOG_PATH}/benchmark_train/${model_name}_bs${train_batch_value}_${autocast}"
 
                 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} > ${btrain_log} 2>&1 "
+                    cmd="${python} ${run_train} ${set_use_gpu}  ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} "
                 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}  > ${btrain_log} 2>&1 "
+                    cmd="${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} ${set_amp_config}"
                 else     # train with multi-machine
-                    cmd="${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} > ${btrain_log} 2>&1 "
+                    cmd="${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}"
                 fi
                 # run train
                 eval $cmd