diff --git a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/pip-requirements.txt b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/pip-requirements.txt
index a90c02fe57c8fd8b78226eabfbc114d1f35278a1..4829dd3a1b9f501b323b7dd1b7200891c24bf7a3 100644
--- a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/pip-requirements.txt
+++ b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/pip-requirements.txt
@@ -1,3 +1,3 @@
 torch==1.10.0
-torchvision==0.11.3
+torchvision==0.6.0a0
 numpy==1.21.2
\ No newline at end of file
diff --git a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/run_symnet.py b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/run_symnet.py
index 7556ce8d15a588fefa194326e25ff517bb47be45..def3bc0f21fe2b43e1203c47aa750abb01e00b4c 100644
--- a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/run_symnet.py
+++ b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/run_symnet.py
@@ -180,7 +180,7 @@ if args.ifNPU == True:
 profiling_dir = "/cache/profiling"
 os.makedirs(profiling_dir)
 
-import moxing as mox
+#import moxing as mox
 
 
 ############################################################
@@ -206,7 +206,7 @@ def main():
         sw = SolverWrapper(net, train_dataloader, test_dataloader, args)
         sw.trainval_model(sess, args.epoch)
 
-    mox.file.copy_parallel(profiling_dir, args.train_url)
+    #mox.file.copy_parallel(profiling_dir, args.train_url)
 
 
 ################################################################################
diff --git a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/test/train_full_1p.sh b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/test/train_full_1p.sh
index c663be49d974421d9f32e639709d71a18b35156a..fc25ec4692727da016c22f7ef4a94a2a08ae2a28 100644
--- a/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/test/train_full_1p.sh
+++ b/TensorFlow/contrib/cv/SYMNET_ID1292_for_Tensorflow/test/train_full_1p.sh
@@ -7,7 +7,13 @@
 ##########################################################
 # shell脚本所在路径
 cur_path=`echo $(cd $(dirname $0);pwd)`
-
+cd /
+if [ -d ./cache/profiling ]
+then
+    rm -rf ./cache
+fi
+cd ${cur_path}
+#cur_path=`echo $(cd $(dirname $0);pwd)`
 # 判断当前shell是否是performance
 perf_flag=`echo $0 | grep performance | wc -l`
 
@@ -113,13 +119,51 @@ epochs=700
 
 if [ x"${modelarts_flag}" != x ];
 then
-    python3.7 ./run_symnet.py --name UT_best --data UT --epoch=${epochs} --obj_pred UT_obj_lr1e-3_test_ep260.pkl --trained_weight snapshot_epoch_586.ckpt --batchnorm  --wordvec onehot  --lr 1e-4 --bz=${batch_size} --lambda_cls_attr 1 --lambda_cls_obj 0.5 --lambda_trip 0.5 --lambda_sym 0.01 --lambda_axiom 0.03 --data_url=${data_path} --train_url=${output_path}
-#    python3.7 ./test_symnet.py --name UT_best --data UT --epoch=${epochs} --obj_pred UT_obj_lr1e-3_test_ep260.pkl --wordvec onehot --batchnorm --data_url=${data_path} --train_url=${output_path}
+    echo -------123456--------
+    python3.7 ./run_symnet.py --name UT_best \
+        --data UT \
+        --epoch=${epochs} \
+        --obj_pred UT_obj_lr1e-3_test_ep260.pkl \
+        --trained_weight snapshot_epoch_586.ckpt \
+        --batchnorm  \
+        --wordvec onehot  \
+        --lr 1e-4 \
+        --bz=${batch_size} \
+        --lambda_cls_attr 1 \
+        --lambda_cls_obj 0.5 \
+        --lambda_trip 0.5 \
+        --lambda_sym 0.01 \
+        --lambda_axiom 0.03 \
+        --data_url=${data_path}/data/ \
+        --train_url=${output_path} 1>${print_log} 2>&1
+#    python3.7 ./test_symnet.py --name UT_best \
+        #--data UT \
+        #--epoch 600 \
+        #--obj_pred UT_lr1e-3_ep140.pkl \
+        #--wordvec onehot \
+        #--batchnorm >>${print_log} 2>&1
 else
-    python3.7 ./run_symnet.py --name UT_best --data UT --epoch${epochs} --obj_pred UT_obj_lr1e-3_test_ep260.pkl --trained_weight snapshot_epoch_586.ckpt --batchnorm  --wordvec onehot  --lr 1e-4 --bz=${batch_size} --lambda_cls_attr 1 --lambda_cls_obj 0.5 --lambda_trip 0.5 --lambda_sym 0.01 --lambda_axiom 0.03 --data_url=${data_path} --train_url=${output_path} 1>${print_log} 2>&1
-#    python3.7 ./test_symnet.py --name UT_best --data UT --epoch=${epochs} --obj_pred UT_obj_lr1e-3_test_ep260.pkl --wordvec onehot --batchnorm --data_url=${data_path} --train_url=${output_path}
+    echo --------1234567----------
+    python3.7 ./run_symnet.py --name UT_best \
+        --data UT \
+        --epoch=${epochs} \
+        --obj_pred UT_obj_lr1e-3_test_ep260.pkl \
+        --trained_weight snapshot_epoch_586.ckpt \
+        --batchnorm  \
+        --wordvec onehot  \
+        --lr 1e-4 \
+        --bz=${batch_size} \
+        --lambda_cls_attr 1 \
+        --lambda_cls_obj 0.5 \
+        --lambda_trip 0.5 \
+        --lambda_sym 0.01 \
+        --lambda_axiom 0.03 \
+        --data_url=${data_path}/data \
+        --train_url=${output_path} 1>${print_log} 2>&1
+
 fi
 
+
 # 性能相关数据计算
 StepTime=`grep "sec/step :" ${print_log} | tail -n 20 | awk -F ':' '{print $NF}' | awk '{sum+=$1} END {print sum/NR}'`
 FPS=`awk 'BEGIN{printf "%.2f\n", '${batch_size}'/'${StepTime}'}'`
@@ -184,4 +228,9 @@ echo "ActualFPS = ${FPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${StepTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+cd /
+if [ -d ./cache/profiling ]
+then
+    rm -rf ./cache
+fi
diff --git a/TensorFlow/contrib/cv/UDCVO_ID2359_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/UDCVO_ID2359_for_TensorFlow/test/train_performance_1p.sh
index 4a72627bfe582424001c7c54817da5e5d3238cd4..8b1e18d922a07576e158bff7487fdce5e0d79f3a 100644
--- a/TensorFlow/contrib/cv/UDCVO_ID2359_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/contrib/cv/UDCVO_ID2359_for_TensorFlow/test/train_performance_1p.sh
@@ -141,7 +141,7 @@ then
     --rot_param exponential \
     --n_summary 10 \
     --n_checkpoint 50 \
-    --checkpoint_path /home/ma-user/modelarts/outputs/train_url_0/
+    --checkpoint_path /home/ma-user/modelarts/outputs/train_url_0/ >${print_log} 2>&1 
 else
     #python3.7 ./LeNet.py --data_path=${data_path} --output_path=${output_path} --steps=${train_steps} > ${print_log}
     python3.7 src/train_voiced.py \