diff --git a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/Action/training/train.py b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/Action/training/train.py
index 0f2c629d1dc509ca57ee7ac51d9e543c348d32db..7116146271f5ff5f2cb858b5cbaa931bf0f24fbd 100644
--- a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/Action/training/train.py
+++ b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/Action/training/train.py
@@ -51,6 +51,8 @@ parser.add_argument('--train_epoch', dest='train_epoch', type=int, default=2000,
 parser.add_argument('--modeldir', dest='modeldir', default='./ckpt', help='ckpt dir')
 parser.add_argument('--learning_rate', dest='learning_rate', type=float, default=0.0001, help='learning rate')
 parser.add_argument('--batch_size', dest='batch_size', type=int, default=64, help='# images in batch')
+
+parser.add_argument("--dynamic_input", type=str, default='1', help="--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph")
 args = parser.parse_args()
 
 
@@ -185,6 +187,12 @@ sess_config = tf.ConfigProto()
 custom_op = sess_config.graph_options.rewrite_options.custom_optimizers.add()
 custom_op.name = "NpuOptimizer"
 custom_op.parameter_map["dynamic_input"].b = True
+if args.dynamic_input == "lazy_recompile":
+    custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+elif args.dynamic_input == "1":
+    custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("dynamic_execute")
+else:
+    print("Enter correct compilation parameters.")
 custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
 custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes(args.precision_mode)
 if args.data_dump_flag.strip() == "True":
diff --git a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_full_1p.sh
index 715ba8698189e797ed141c868d1bdca356cb8886..a9a5c424cf89c09638f803c79b6a320da477ed37 100644
--- a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_full_1p.sh
@@ -24,6 +24,8 @@ train_epoch=2000
 batch_size=32
 #学习率
 learning_rate=0.0001
+#动态输入模式，不需要修改
+dynamic_input=""
 
 
 #维测参数，precision_mode需要模型审视修改
@@ -94,6 +96,8 @@ do
         batch_size=`echo ${para#*=}`
     elif [[ $para == --modeldir* ]];then
         modeldir=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
     fi
 done
 
@@ -139,7 +143,8 @@ do
       --batch=${batch_size} \
       --profiling=${profiling} \
       --profiling_dump_path=${profiling_dump_path} \
-      --autotune=${autotune} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+      --autotune=${autotune} \
+      --dynamic_input=${dynamic_input} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 if [ $? -ne 0 ];then
   exit 1
 fi
@@ -205,4 +210,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$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
\ No newline at end of file
+echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_performance_1p.sh
index cb68c2a4844505425bf8cbe2c5f24e820f96a7a1..a1e197b49b90fc812ac1a37707b5cb82eede6f12 100644
--- a/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/detection/OpenPose_ID0117_for_TensorFlow/test/train_performance_1p.sh
@@ -24,6 +24,8 @@ train_epoch=20
 batch_size=32
 #学习率
 learning_rate=0.0001
+#动态输入模式，不需要修改
+dynamic_input=""
 
 
 #维测参数，precision_mode需要模型审视修改
@@ -83,6 +85,8 @@ do
         batch_size=`echo ${para#*=}`
     elif [[ $para == --modeldir* ]];then
         modeldir=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
     fi
 done
 
@@ -127,7 +131,8 @@ do
       --data_dump_path=${data_dump_path} \
       --batch=${batch_size} \
       --profiling=${profiling} \
-      --profiling_dump_path=${profiling_dump_path} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+      --profiling_dump_path=${profiling_dump_path} \
+      --dynamic_input=${dynamic_input} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 if [ $? -ne 0 ];then
   exit 1
 fi
@@ -193,4 +198,5 @@ echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$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
\ No newline at end of file
+echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_1p.sh
index fd6a595160c0f7b22a4c5b3a78fcd9fd338c795c..ee02d0a4d3ce18fbba0483e90dbc61f639dcac9e 100644
--- a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_1p.sh
@@ -15,6 +15,8 @@ train_epochs=200
 train_steps=
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置
 data_path="/root/.keras/datasets/cifar-10-batches-py.tar.gz"
@@ -26,8 +28,10 @@ fi
 
 for para in $*
 do
-   if [[ $para == --data_path* ]];then
-      data_path=`echo ${para#*=}`
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -56,7 +60,7 @@ fi
 wait
 
 start=$(date +%s)
-nohup python3 -u train.py --epochs=${train_epochs} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+nohup python3 -u train.py --epochs=${train_epochs} --dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
 end=$(date +%s)
@@ -114,3 +118,4 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_8p.sh b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_8p.sh
index 44ed1790a51b84147977e8e306d3f15d5e488426..fa587791632dea3d03a4d823a5df4b1997f9e76c 100644
--- a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_8p.sh
+++ b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_full_8p.sh
@@ -24,6 +24,8 @@ train_epochs=200
 train_steps=
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置
 data_path="/root/.keras/datasets/cifar-10-batches-py.tar.gz"
@@ -35,8 +37,10 @@ fi
 
 for para in $*
 do
-   if [[ $para == --data_path* ]];then
-      data_path=`echo ${para#*=}`
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -70,7 +74,7 @@ do
        mkdir -p $cur_path/test/output/$ASCEND_DEVICE_ID
     fi
     echo $ASCEND_DEVICE_ID
-    nohup python3 train.py --epochs=${train_epochs} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+    nohup python3 train.py --epochs=${train_epochs} --dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 done
 wait
 
@@ -131,3 +135,4 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_1p.sh
index 472942f532d7560042d84533bec9899d936b8f2e..24a278920e9f5c42b81b76c3852c37e4d4b59f86 100644
--- a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_1p.sh
@@ -15,6 +15,8 @@ train_epochs=3
 train_steps=
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置
 data_path="/root/.keras/datasets/cifar-10-batches-py.tar.gz"
@@ -26,8 +28,10 @@ fi
 
 for para in $*
 do
-   if [[ $para == --data_path* ]];then
-      data_path=`echo ${para#*=}`
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -56,7 +60,7 @@ fi
 wait
 
 start=$(date +%s)
-nohup python3 -u train.py --epochs=${train_epochs} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+nohup python3 -u train.py --epochs=${train_epochs} --dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
 end=$(date +%s)
@@ -113,4 +117,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_8p.sh b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_8p.sh
index 6aad860207deaa302817678edfc7e84185287936..5852a0d7970da45a88e245f659d9744c7329d77d 100644
--- a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_8p.sh
+++ b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/test/train_performance_8p.sh
@@ -24,6 +24,8 @@ train_epochs=1
 train_steps=
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置
 data_path="/root/.keras/datasets/cifar-10-batches-py.tar.gz"
@@ -35,8 +37,10 @@ fi
 
 for para in $*
 do
-   if [[ $para == --data_path* ]];then
-      data_path=`echo ${para#*=}`
+    if [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -70,7 +74,7 @@ do
        mkdir -p $cur_path/test/output/$ASCEND_DEVICE_ID
     fi
     echo $ASCEND_DEVICE_ID
-    nohup python3 train.py  > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+    nohup python3 train.py  --dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 done
 wait
 
@@ -131,3 +135,4 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/train.py b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/train.py
index 7cf972356442788185facfa4a8ff92597a018165..80100785e3acb0c502f17b6581f35727852e92ac 100644
--- a/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/train.py
+++ b/TensorFlow/built-in/cv/image_classification/AUTOAUGMENT_ID0708_for_TensorFlow/train.py
@@ -62,14 +62,16 @@ def parse_args():
     parser.add_argument('--batch-size', default=128, type=int)
     parser.add_argument('--cutout', default=False, type=str2bool)
     parser.add_argument('--auto-augment', default=False, type=str2bool)
-
+    parser.add_argument("--dynamic_input", type=str, default='1',
+                        help="--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph")
     args = parser.parse_args()
 
     return args
 
+args = parse_args()
 
 def main():
-    args = parse_args()
+    # args = parse_args()
 
     if args.name is None:
         args.name = 'WideResNet%s-%s' %(args.depth, args.width)
@@ -132,7 +134,12 @@ if __name__ == '__main__':
     custom_op.name = "NpuOptimizer"
     custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("allow_mix_precision")
     custom_op.parameter_map["dynamic_input"].b = 1
-    custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+    if args.dynamic_input == "lazy_recompile":
+        custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+    elif args.dynamic_input == "1":
+        custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("dynamic_execute")
+    else:
+        print("Enter correct compilation parameters.")
     npu_keras_sess = set_keras_session_npu_config(config=global_config)
     # ***** npu modify end *****
     main()
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
index 14bb51bad1e085b0ffd15927bb87790f010c736f..038dfdec6133b60854416d5717b7c167f520fa93 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
@@ -190,6 +190,9 @@ flags.DEFINE_string(
     'input_layout', 'nhwc',
     help='Layout of input features: "nhwc" or "nchw"')
 
+flags.DEFINE_string(
+    'dynamic_input', '1',
+    help='--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph')
 
 # TODO(seth): Verify if this is still required.
 flags.register_multi_flags_validator(
@@ -209,7 +212,13 @@ class DualNetwork():
         custom_op = global_config.graph_options.rewrite_options.custom_optimizers.add()
         custom_op.name = "NpuOptimizer"
         custom_op.parameter_map["dynamic_input"].b = True
-        custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+        print('========= DualNetwork DYNAMIC INPUT = %s =========' % FLAGS.dynamic_input)
+        if FLAGS.dynamic_input == "lazy_recompile":
+            custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+        elif FLAGS.dynamic_input == "1":
+            custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("dynamic_execute")
+        else:
+            print("Enter correct compilation parameters.")
         global_config.graph_options.rewrite_options.remapping = RewriterConfig.OFF
         global_config.graph_options.rewrite_options.memory_optimization = RewriterConfig.OFF
         
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
index 47a9946c9a1aed782a086dfc76b638450a07343b..a6f75350e7f68483c98d3dfaf71262203c22d307 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
@@ -17,6 +17,8 @@ train_epochs=
 train_steps=80000
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置 npu param
 precision_mode="allow_fp32_to_fp16"
@@ -36,6 +38,8 @@ for para in $*
 do
    if [[ $para  == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`  	
    fi
 done
 
@@ -61,7 +65,7 @@ wait
 
 start=$(date +%s)
 #(Step3)训练
-python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation --dynamic_input=${dynamic_input}> $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 end=$(date +%s)
 e2etime=$(( $end - $start ))
@@ -96,4 +100,5 @@ echo "TrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Ca
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
index 56dbf5f33dcca9753428271c1ca14c091813d110..8cd78e2f2b804957f26e967acf45a7359b05c13e 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
@@ -17,6 +17,8 @@ train_epochs=
 train_steps=80000
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置 npu param
 precision_mode="allow_fp32_to_fp16"
@@ -39,6 +41,8 @@ do
     elif [[ $para == --bind_core* ]]; then
         bind_core=`echo ${para#*=}`
         name_bind="_bindcore"
+	elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -85,7 +89,7 @@ do
     if [ "x${bind_core}" != x ];then
         bind_core="taskset -c $a-$c"
     fi
-    ${bind_core} python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+    ${bind_core} python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation --dynamic_input=${dynamic_input}> $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 done
 wait
 
@@ -122,4 +126,5 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
index b7e8dc3150df85ff884bc1fe5a1ea965aa0ac48b..2b9da3177a38d234fd38f1bee12f16deffdc2815 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
@@ -17,6 +17,8 @@ train_epochs=
 train_steps=500
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置 npu param
 precision_mode="allow_fp32_to_fp16"
@@ -36,6 +38,8 @@ for para in $*
 do
    if [[ $para  == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`  	
    fi
 done
 
@@ -61,7 +65,14 @@ wait
 
 start=$(date +%s)
 #(Step3)训练
-python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+#python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+python3 train.py \
+	--training_data_path=$data_path \
+	--steps_to_train=$train_steps \
+	--train_batch_size=$batch_size \
+	--work_dir=$cur_path/estimator_working_dir \
+	--export_path=$cur_path/outputs/models/000001-first_generation \
+	--dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 end=$(date +%s)
 e2etime=$(( $end - $start ))
@@ -96,4 +107,5 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh
index 446dafd108fe31b25190f25d216f43ca90bf66f4..d52fd0d57bc7da07107b82b81d36ad9eb40d6688 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_8p.sh
@@ -17,6 +17,8 @@ train_epochs=
 train_steps=500
 #学习率
 learning_rate=
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #参数配置 npu param
 precision_mode="allow_fp32_to_fp16"
@@ -39,6 +41,8 @@ do
     elif [[ $para == --bind_core* ]]; then
         bind_core=`echo ${para#*=}`
         name_bind="_bindcore"
+    elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}` 
    fi
 done
 
@@ -85,7 +89,14 @@ do
     if [ "x${bind_core}" != x ];then
         bind_core="taskset -c $a-$c"
     fi
-    ${bind_core} python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+    #${bind_core} python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+	${bind_core} python3 train.py \
+		--training_data_path=$data_path \
+		--steps_to_train=$train_steps \
+		--train_batch_size=$batch_size \
+		--work_dir=$cur_path/estimator_working_dir \
+		--export_path=$cur_path/outputs/models/000001-first_generation \
+		--dynamic_input=${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 done
 wait
 
@@ -122,4 +133,5 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/train.py b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/train.py
index c55d271b7a8e3ad77ab8e422db7b2c4c58d2d9c0..ff0e5a499ab9667154589d920f742cfb1503f64c 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/train.py
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/train.py
@@ -140,6 +140,7 @@ flags.declare_key_flag('work_dir')
 flags.declare_key_flag('train_batch_size')
 flags.declare_key_flag('num_tpu_cores')
 flags.declare_key_flag('use_tpu')
+flags.declare_key_flag('dynamic_input')
 
 FLAGS = flags.FLAGS
 
diff --git a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/recommenders-master/examples/00_quick_start/naml_MIND.py b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/recommenders-master/examples/00_quick_start/naml_MIND.py
index f1daed12f030538061ebfbb0c318233e82190a80..f3bfabed58a938a74ab47cf89b9a33f6dd81bc7a 100644
--- a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/recommenders-master/examples/00_quick_start/naml_MIND.py
+++ b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/recommenders-master/examples/00_quick_start/naml_MIND.py
@@ -82,8 +82,13 @@ def main():
         custom_op.parameter_map["hcom_parallel"].b = True
     
     custom_op.parameter_map["dynamic_input"].b = True
-    custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
-    
+    if args.dynamic_input == "lazy_recompile":
+        custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+    elif args.dynamic_input == "1":
+        custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("dynamic_execute")
+    else:
+        print("Enter correct compilation parameters.")
+
     sess_config.graph_options.rewrite_options.remapping = RewriterConfig.OFF
     sess_config.graph_options.rewrite_options.memory_optimization = RewriterConfig.OFF
     sess = tf.compat.v1.Session(config=sess_config)
@@ -142,6 +147,8 @@ def parse_args():
                         help="""the max train steps""")
     parser.add_argument('--MIND_type', default='small', choices=["demo", "small", "large"],
                         help = """the type of MIND data""")
+    parser.add_argument('--dynamic_input', type=str, default='1',
+                        help="--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph")
 
     args, unknown_args = parser.parse_known_args()
     if len(unknown_args) > 0:
diff --git a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_1p.sh
index e4f7ef13d6eb43a82eeaa7773897a6b4f2d3291f..0d58155269a315436549626b816d3edc534a5e1f 100644
--- a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_1p.sh
@@ -24,6 +24,8 @@ batch_size=32
 train_epochs=10
 #训练步数
 train_steps=100
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #维测参数，precision_mode需要模型审视修改
 #precision_mode="allow_mix_precision"
@@ -75,6 +77,8 @@ do
         cp -rf $install_path/fwkacllib/data/rl/Ascend910/custom ${autotune_dump_path}/RL/
     elif [[ $para == --data_path* ]];then
         data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`  	
     fi
 done
 
@@ -110,7 +114,8 @@ do
     nohup python3  naml_MIND.py \
           --data_path=$data_path \
           --epochs=$train_epochs \
-          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} \
+          --dynamic_input=${dynamic_input} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 done 
 wait
 
@@ -166,4 +171,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainAccuracy = ${TrainAccuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "TrainAccuracy = ${TrainAccuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_8p.sh b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_8p.sh
index 801a399a811ffce571a9004e0ea9253494e2ab42..c86a3e1aeee201a39f0b5698428e5f35414ed5bb 100644
--- a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_8p.sh
+++ b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_full_8p.sh
@@ -10,6 +10,16 @@ export JOB_ID=10018
 export RANK_SIZE=8
 export RANK_TABLE_FILE=${currentDir}/hccl_${RANK_SIZE}p.json
 
+#动态输入模式，不需要修改
+dynamic_input=""
+
+for para in $*
+do
+    if [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`  	
+    fi
+done
+
 for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
 do
    export RANK_ID=$RANK_ID
@@ -24,6 +34,7 @@ do
              --model_path=${currentDir}/output/${ASCEND_DEVICE_ID} \
              --data_path=${currentDir}/data \
              --epochs=1 \
-             --max_steps=1000 > ${currentDir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+             --max_steps=1000 \
+             --dynamic_input=${dynamic_input} > ${currentDir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 done
 
diff --git a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_1p.sh
index 558e920bed83487166b8833302e4c3c69340d42d..af15817813b08bb4b3fc150912134fadbcec6660 100644
--- a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_1p.sh
@@ -24,6 +24,8 @@ batch_size=32
 train_epochs=1
 #训练步数
 train_steps=1000
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #维测参数，precision_mode需要模型审视修改
 #precision_mode="allow_mix_precision"
@@ -75,6 +77,8 @@ do
         cp -rf $install_path/fwkacllib/data/rl/Ascend910/custom ${autotune_dump_path}/RL/
     elif [[ $para == --data_path* ]];then
         data_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`  	
     fi
 done
 
@@ -111,7 +115,8 @@ do
           --data_path=$data_path \
           --epochs=$train_epochs \
           --max_steps=$train_steps \
-          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} \
+          --dynamic_input=${dynamic_input} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 done 
 wait
 
@@ -155,4 +160,5 @@ echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
diff --git a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_8p.sh b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_8p.sh
index 6417e0ec111e79e194c6d23954ee7af6b1f553e0..76da092797b5eb61ba0e6c2b1a68ef5e279cad2c 100644
--- a/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_8p.sh
+++ b/TensorFlow/built-in/recommendation/NAML_ID0113_for_TensorFlow/test/train_performance_8p.sh
@@ -24,6 +24,8 @@ batch_size=32
 train_epochs=1
 #训练步数
 train_steps=1000
+#动态输入模式，不需要修改
+dynamic_input=""
 
 #维测参数，precision_mode需要模型审视修改
 #precision_mode="allow_mix_precision"
@@ -78,6 +80,8 @@ do
     elif [[ $para == --bind_core* ]]; then
         bind_core=`echo ${para#*=}`
         name_bind="_bindcore"
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`  	
     fi
 done
 
@@ -125,7 +129,8 @@ do
           --data_path=$data_path \
           --epochs=$train_epochs \
           --max_steps=$train_steps \
-          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+          --model_path=${cur_path}/output/${ASCEND_DEVICE_ID} \
+          --dynamic_input=${dynamic_input} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 done 
 wait
 
@@ -170,4 +175,5 @@ echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file