diff --git a/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_full_1p.sh
index fe078086b4be5cfdcd83852e6faf6ba96d8d7899..105c5916b21f2f1d815ab410a1454a6488e5c09a 100644
--- a/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_full_1p.sh
@@ -17,6 +17,7 @@ learning_rate=
 
 #参数配置
 data_path=$cur_path
+dynamic_input="1"
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_full_1p.sh --data_path=../"
@@ -27,6 +28,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`
    fi
 done
 
@@ -62,6 +65,7 @@ nohup python3 train.py \
        --epochs ${train_epochs} \
        --data-dir $data_path/pascal-voc \
        --vgg-dir $data_path/vgg_graph \
+       --dynamic_input ${dynamic_input} \
 	   "${@:1}"  > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
@@ -117,3 +121,4 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 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 "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_performance_1p.sh
index 0004076aa3695ba342771864a8ae6c77b1649e99..2c004af3bd140ab20091a95601a9dce5a3432593 100644
--- a/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/test/train_performance_1p.sh
@@ -19,6 +19,7 @@ learning_rate=
 
 #参数配置
 data_path=$cur_path
+dynamic_input="1"
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_performance_1p.sh --data_path=../"
@@ -29,6 +30,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`      
    fi
 done
 
@@ -64,6 +67,7 @@ nohup python3 train.py \
        --epochs ${train_epochs} \
        --data-dir $data_path/pascal-voc \
        --vgg-dir $data_path/vgg_graph \
+       --dynamic_input ${dynamic_input} \
 	   "${@:1}"  > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
@@ -118,3 +122,4 @@ echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID
 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 "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/detection/SSD-VGG_ID1619_for_TensorFlow/train.py b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/train.py
index 10fd58af0692b3eba416b77cedb4942a597cf492..822a1beaf6ecddc52160eef119808ce0e6507d14 100644
--- a/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/train.py
+++ b/TensorFlow/built-in/cv/detection/SSD-VGG_ID1619_for_TensorFlow/train.py
@@ -107,7 +107,9 @@ def main():
     parser.add_argument('--dump_path', type=str, default='/home/HwHiAiUser/',
                         help='dump path')
     parser.add_argument('--data_path', type=str, default='./',
-                        help='data path')                        
+                        help='data path') 
+    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")                                               
     #****** npu modify end ******
 
     args = parser.parse_args()
@@ -130,6 +132,7 @@ def main():
     print('[i] Overflow dump flag:    ', args.over_dump)
     print('[i] data dump flag:    ', args.data_dump)
     print('[i] Dump path:    ', args.dump_path)
+    print('[i] dynamic_input:    ', args.dynamic_input)
     #****** npu modify end ******
     #---------------------------------------------------------------------------
     # Find an existing checkpoint
@@ -205,7 +208,12 @@ def 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.")
     custom_op.parameter_map["use_off_line"].b = True
     custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes(args.precision_mode)
     if args.over_dump:
diff --git a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/TrainResNet.py b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/TrainResNet.py
index 46f51c5a8a75e624f7d7703e3af3d1c184c83176..b184e85ea086bdde820e360916b63f95e0a31aa2 100644
--- a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/TrainResNet.py
+++ b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/TrainResNet.py
@@ -56,16 +56,17 @@ from scipy import misc
 from utils import *
 
 def parse_args():
-	desc = "MAIN"
-	parser = argparse.ArgumentParser(description=desc)
-	parser.add_argument('--label_path', type=str, default='./label/label_1200.npy', help='Path of Label.npy')
-	parser.add_argument('--image_name_path', type=str, default='./label/name_1200.npy', help='Path of image file names')
-	############################add train_data_path##################################
-	parser.add_argument('--train_data_path', type=str, default='./train_data/1200_data.npy', help='Path of train data')
-	############################add train_data_path##################################
-	parser.add_argument('--parentPath', type=str, default='./CACD2000_Crop/', help='image path')
-	parser.add_argument('--epochs', type=int, default=100, help='NUM_EPOCHS')
-	return parser.parse_args()
+    desc = "MAIN"
+    parser = argparse.ArgumentParser(description=desc)
+    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')
+    parser.add_argument('--label_path', type=str, default='./label/label_1200.npy', help='Path of Label.npy')
+    parser.add_argument('--image_name_path', type=str, default='./label/name_1200.npy', help='Path of image file names')
+    ############################add train_data_path##################################
+    parser.add_argument('--train_data_path', type=str, default='./train_data/1200_data.npy', help='Path of train data')
+    ############################add train_data_path##################################
+    parser.add_argument('--parentPath', type=str, default='./CACD2000_Crop/', help='image path')
+    parser.add_argument('--epochs', type=int, default=100, help='NUM_EPOCHS')
+    return parser.parse_args()
 args = parse_args()
 
 # image size
@@ -145,7 +146,12 @@ def Train(epochs=100):
     custom_op = global_config.graph_options.rewrite_options.custom_optimizers.add()
     custom_op.name = "NpuOptimizer"
     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.")
     global_config.graph_options.rewrite_options.remapping = RewriterConfig.OFF
     global_config.graph_options.rewrite_options.memory_optimization = RewriterConfig.OFF
     #with tf.Session() as sess:
diff --git a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_full_1p.sh
index 33673edf993d910f76dad4120f6dc90e3a4a90fb..2c86cd50ac105482a7b8deb2a0ccab1808d60925 100644
--- a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_full_1p.sh
@@ -20,6 +20,7 @@ learning_rate=
 
 #参数配置
 data_path=""
+dynamic_input="1"
 #work_dir="$cur_path/estimator_working_dir"
 #export_path="$cur_path/outputs/models/000001-first_generation"
 
@@ -32,6 +33,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`       
    fi
 done
 
@@ -58,7 +61,8 @@ nohup python3 TrainResNet.py \
 				--image_name_path ${data_path}/label/name_1200.npy \
                 --train_data_path ${data_path}/train_data/1200_data.npy \
 				--parentPath ${data_path}/CACD2000_Crop/ \
-				--epochs 100 > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+				--epochs 100 \
+            --dynamic_input ${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 end=$(date +%s)
 e2e_time=$(( $end - $start ))
@@ -114,4 +118,4 @@ echo "TrainingTime = ${TrainingTime}"       >> $cur_path/test/output/$ASCEND_DEV
 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
diff --git a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_performance_1p.sh
index 3e357429902a0f5556e2e4e9d49453c561822517..41420ab08efc93ce377e6a9fbcda5e445574b653 100644
--- a/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/Face-ResNet50_ID1372_for_TensorFlow/test/train_performance_1p.sh
@@ -20,6 +20,7 @@ learning_rate=
 
 #参数配置
 data_path=""
+dynamic_input="1"
 #work_dir="$cur_path/estimator_working_dir"
 #export_path="$cur_path/outputs/models/000001-first_generation"
 
@@ -32,6 +33,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`        
    fi
 done
 
@@ -58,7 +61,8 @@ nohup python3 TrainResNet.py \
 				--image_name_path ${data_path}/label/name_1200.npy \
                 --train_data_path ${data_path}/train_data/1200_data.npy \
 				--parentPath ${data_path}/CACD2000_Crop/ \
-				--epochs 2 > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+				--epochs 2 \
+            --dynamic_input ${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 end=$(date +%s)
 e2e_time=$(( $end - $start ))
@@ -114,4 +118,4 @@ echo "TrainingTime = ${TrainingTime}"       >> $cur_path/test/output/$ASCEND_DEV
 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
diff --git a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/main.py b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/main.py
index f52a29fe18e2b2fcf2e44e6e80f2db17fa533509..659c8a97d95e71a28862b2d5931e04e01d2fe2d3 100644
--- a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/main.py
+++ b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/main.py
@@ -39,6 +39,7 @@ parser.add_argument('--epochs', default=5, type=int)
 parser.add_argument('--train_data_path', default='./data/membrane/train')
 parser.add_argument('--test_data_path', default='./data/membrane/test')
 parser.add_argument('--predict_data_path', default='./data/membrane/predict')
+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()
 
 def main():
@@ -66,7 +67,12 @@ 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_segmentation/2D_Unet_ID2337_for_TensorFlow/model.py b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/model.py
index 310f7a7dea4fd64ea78a215469d69caaebf06d3b..597ae0418a05bf5ccde90919d9a81996679a010a 100644
--- a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/model.py
+++ b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/model.py
@@ -28,6 +28,7 @@
 # limitations under the License.
 #
 from npu_bridge.npu_init import *
+from npu_bridge.estimator.npu import npu_convert_dropout
 import numpy as np
 import os
 import skimage.io as io
@@ -67,11 +68,17 @@ def unet(pretrained_weights = None,input_size = (256,256,1)):
     conv4 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool3)
     conv4 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv4)
     drop4 = Dropout(0.5)(conv4)
+    # drop4 = npu_ops.dropout(0.5)(conv4)
+    # drop4 = npu_ops.dropout(conv4, 0.5)
+    # drop4 = tf.keras.layers.Dropout(0.5)(conv4)
     pool4 = MaxPooling2D(pool_size=(2, 2))(drop4)
 
     conv5 = Conv2D(1024, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool4)
     conv5 = Conv2D(1024, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv5)
     drop5 = Dropout(0.5)(conv5)
+    # drop5 = npu_ops.dropout(0.5)(conv5)
+    # drop5 = npu_ops.dropout(conv5, 0.5)
+    # drop5 = tf.keras.layers.Dropout(0.5)(conv5)
 
     up6 = Conv2D(512, 2, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(UpSampling2D(size = (2,2))(drop5))
     merge6 = concatenate([drop4,up6], axis = 3)
diff --git a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_full_1p.sh
index 315bbaa301593277116db7c8d1d5c125460817f8..1b4179dae92d74ece6e03c015647abec1d46d5f1 100644
--- a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_full_1p.sh
@@ -18,6 +18,7 @@ learning_rate=
 
 #参数配置
 data_path=""
+dynamic_input="1"
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_full_1p.sh --data_path=./datasets"
@@ -28,6 +29,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`       
    fi
 done
 
@@ -51,7 +54,8 @@ start=$(date +%s)
 python3 main.py --epochs=${train_epochs} \
                 --train_data_path=${data_path}/data/membrane/train \
                 --test_data_path=${data_path}/data/membrane/test \
-                --predict_data_path=${cur_path}/test/predict > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+                --predict_data_path=${cur_path}/test/predict \
+                --dynamic_input ${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
 end=$(date +%s)
@@ -109,4 +113,5 @@ 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_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_performance_1p.sh
index fef0301deb185c69877d804f6989c94f5e085682..7e23b40fe14a71b758e29629f568b0b12b3426b0 100644
--- a/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_segmentation/2D_Unet_ID2337_for_TensorFlow/test/train_performance_1p.sh
@@ -1,6 +1,8 @@
 #!/bin/bash
 cur_path=`pwd`/../
 
+export ASCEND_SLOG_PRINT_TO_STDOUT=1
+export ASCEND_GLOBAL_LOG_LEVEL=0
 #基础参数，需要模型审视修改
 #Batch Size
 batch_size=2
@@ -18,6 +20,9 @@ learning_rate=
 
 #参数配置
 data_path=""
+dynamic_input="1"
+
+source /usr/local/Ascend/latest/bin/setenv.bash
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_performance_1p.sh --data_path=./datasets"
@@ -28,6 +33,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`      
    fi
 done
 
@@ -51,7 +58,8 @@ start=$(date +%s)
 python3 main.py --epochs=${train_epochs} \
                 --train_data_path=${data_path}/data/membrane/train \
                 --test_data_path=${data_path}/data/membrane/test \
-                --predict_data_path=${cur_path}/test/predict > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+                --predict_data_path=${cur_path}/test/predict \
+                --dynamic_input ${dynamic_input} > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 
 end=$(date +%s)
@@ -109,4 +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_segmentation/OSMN_ID1103_for_TensorFlow/osmn_coco_pretrain.py b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/osmn_coco_pretrain.py
index 2e3809f4a023affa3f13d22f761553b8c87b8dd1..c7c891bf48bac9303ab9e4b836177ad2c934b2b2 100644
--- a/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/osmn_coco_pretrain.py
+++ b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/osmn_coco_pretrain.py
@@ -81,6 +81,12 @@ def add_arguments(parser):
             required=False,
             default=[0.8, 1, 1.2],
             help='Image scales for data augmentation')
+    group.add_argument(
+            '--dynamic_input',
+            type=str,
+            required=False,
+            default='1',
+            help='--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph')            
 
 print(" ".join(sys.argv[:]))
 
@@ -115,7 +121,12 @@ config.gpu_options.per_process_gpu_memory_fraction = 0.9
 custom_op = config.graph_options.rewrite_options.custom_optimizers.add()
 custom_op.name = "NpuOptimizer"
 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.")
 custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("allow_mix_precision")
 
 #custom_op.parameter_map["mix_compile_mode"].b = True
diff --git a/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_full_1p.sh
index 7ac40e7b23a146f7ceb74cb785edfa44c5cf48c0..e8e9cc8838824f4882eda861a2b19c682bc55fcf 100644
--- a/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_full_1p.sh
@@ -19,6 +19,7 @@ learning_rate=
 
 #参数配置
 data_path="../data/"
+dynamic_input="1"
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_full_1p.sh --data_path=../data"
@@ -29,6 +30,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`       
    fi
 done
 
@@ -65,7 +68,8 @@ nohup python3 osmn_coco_pretrain.py --data_path ${data_path}/data/ \
         --model_save_path $cur_path/models/ \
         --training_iters $train_steps \
         --display_iters 100 \
-        --save_iters 50000 > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+        --save_iters 50000 \
+        --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 ))
@@ -107,3 +111,4 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 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_segmentation/OSMN_ID1103_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_performance_1p.sh
index 5392e196023e9bc994716613b033bbed3b90fd07..06f15be3a50633e35262312bafacff6c6059bf52 100644
--- a/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_segmentation/OSMN_ID1103_for_TensorFlow/test/train_performance_1p.sh
@@ -1,6 +1,8 @@
 #!/bin/bash
 cur_path=`pwd`/../
 #export ASCEND_DEVICE_ID=3
+export ASCEND_SLOG_PRINT_TO_STDOUT=1
+export ASCEND_GLOBAL_LOG_LEVEL=0
 
 #基础参数，需要模型审视修改
 #Batch Size
@@ -19,6 +21,7 @@ learning_rate=
 
 #参数配置
 data_path="/data"
+dynamic_input="1"
 
 if [[ $1 == --help || $1 == --h ]];then
    echo "usage:./train_performance_1p.sh --data_path=../data"
@@ -29,6 +32,8 @@ for para in $*
 do
    if [[ $para == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`      
    fi
 done
 
@@ -65,7 +70,8 @@ nohup python3 osmn_coco_pretrain.py --data_path $data_path/data/ \
         --model_save_path $cur_path/models/ \
         --training_iters $train_steps \
         --display_iters 100 \
-        --save_iters 500 > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+        --save_iters 500 \
+        --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 ))
@@ -106,4 +112,5 @@ echo "CaseName = ${CaseName}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseN
 echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${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/contrib/cv/ADAGAN_ID2115_for_TensorFlow/adagan_gmm.py b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/adagan_gmm.py
index bd236179ef49023503138e3491be45bd8295e581..627bed38ad477b1a39ccefcd1fc4b6b266776253 100644
--- a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/adagan_gmm.py
+++ b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/adagan_gmm.py
@@ -175,6 +175,7 @@ if __name__ == '__main__':
     parser.add_argument("--data_url", type=str, default="/test-modelartsxc/dataset/train")
     parser.add_argument("--modelarts_data_dir", type=str, default="/cache/dataset/train")
     parser.add_argument("--modelarts_result_dir", type=str, default="/cache/result")
+    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") 
     config, unparsed = parser.parse_known_args()
     while len(sys.argv) > 1:
         sys.argv.pop()
diff --git a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/gan.py b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/gan.py
index 7c302bfcc13406bc3203a8b7709e16edcecc2704..8ea87113b2d7f4a9c5fd8739f5227c51022c15f4 100644
--- a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/gan.py
+++ b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/gan.py
@@ -58,7 +58,12 @@ class Gan(object):
         custom_op = 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")
+        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.")
         config.graph_options.rewrite_options.remapping = RewriterConfig.OFF  # 必须显式关闭remap
         run_config = NPURunConfig(enable_data_pre_proc=False)
 
diff --git a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_full_1p.sh
index c120d0eeb28f24ad7cc9baecad297ffc7748942b..54281fe469b2cb2daa43b53d0a6b534e2c8d4dfd 100644
--- a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_full_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`          
     fi
 done
 
@@ -111,7 +114,7 @@ do
 
     #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
 
-    python3 adagan_gmm.py > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
+    python3 adagan_gmm.py --dynamic_input ${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
 
 
 done 
@@ -156,4 +159,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_performance_1p.sh
index 1bbb9a1daff5ad772f5af0dfb7a8db6980d01130..a96512fac4dbc14bcbb1518efa189ea612a63a42 100644
--- a/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/contrib/cv/ADAGAN_ID2115_for_TensorFlow/test/train_performance_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`         
     fi
 done
 
@@ -113,7 +116,8 @@ do
 
     python3 adagan_gmm.py \
 	--epochs=${train_epochs} \
-	--steps=${train_steps} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
+	--steps=${train_steps} \
+    --dynamic_input ${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
 
 
 done 
@@ -158,4 +162,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/HybridSN_ID1160_for_TensorFlow/Hybrid-Spectral-Net.py b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/Hybrid-Spectral-Net.py
index 55a6cce34215a8f7cb1e3da2aaf57e9efe54a21e..3de262a376e26a1badac3e82dc882983f7ba9f54 100644
--- a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/Hybrid-Spectral-Net.py
+++ b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/Hybrid-Spectral-Net.py
@@ -62,13 +62,6 @@ import scipy.io as sio
 # %matplotlib inline
 from tensorflow.core.protobuf.rewriter_config_pb2 import RewriterConfig
 
-config = tf.compat.v1.ConfigProto()
-custom_op = config.graph_options.rewrite_options.custom_optimizers.add()
-custom_op.name = "NpuOptimizer"
-custom_op.parameter_map["use_off_line"].b = True
-config.graph_options.rewrite_options.remapping = RewriterConfig.OFF
-custom_op.parameter_map["dynamic_input"].b = True
-custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
 
 flags = tf.compat.v1.flags
 FLAGS = flags.FLAGS
@@ -91,6 +84,23 @@ flags.DEFINE_integer(
     "train_step", 100,
     "total epochs for training")
 
+flags.DEFINE_integer(
+    "dynamic_input", "1", 
+    "--dynamic_input=1 Use fuzzy compilation. --dynamic_input=lazy_recompile Compile using lazy static graph")
+
+config = tf.compat.v1.ConfigProto()
+custom_op = config.graph_options.rewrite_options.custom_optimizers.add()
+custom_op.name = "NpuOptimizer"
+custom_op.parameter_map["use_off_line"].b = True
+config.graph_options.rewrite_options.remapping = RewriterConfig.OFF
+custom_op.parameter_map["dynamic_input"].b = True
+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 VARIABLES
 dataset = 'SA'
diff --git a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_full_1p.sh
index acf6eef09f99aee617bf555b3fdbb4a59d7fb3d5..34cd7e3022362e153c3af62825fb60b0f88d2d0b 100644
--- a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_full_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`        
     fi
 done
 
@@ -120,7 +123,7 @@ do
 	
     #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
 
-    python3 Hybrid-Spectral-Net.py --datapath=${data_path} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
+    python3 Hybrid-Spectral-Net.py --datapath=${data_path} --dynamic_input=${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
 
 
 done 
@@ -165,4 +168,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_performance_1p.sh
index 6114bf636b5fd722690297a254959b91fd0c9fca..c6362c04e9de7cfcc76eff184e07be7588b3547c 100644
--- a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/test/train_performance_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`         
     fi
 done
 
@@ -120,7 +123,7 @@ do
 	
     #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
 
-    python3 Hybrid-Spectral-Net.py --train_step=${train_steps} --datapath=${data_path} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
+    python3 Hybrid-Spectral-Net.py --train_step=${train_steps} --datapath=${data_path} --dynamic_input=${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
 
 
 done 
@@ -165,4 +168,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/MGCNN_ID1039_for_TensorFlow/mgcnn_npu.py b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/mgcnn_npu.py
index 908b689952a6de682ac41ad6036b713cfa50e137..cba82218939e99aac62b9515c9239220a292b7aa 100644
--- a/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/mgcnn_npu.py
+++ b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/mgcnn_npu.py
@@ -187,17 +187,6 @@ class mgcnn(object):
 
 
 if __name__ == '__main__':
-    # npu_keras_sess = set_keras_session_npu_config()
-    # ***** npu modify begin *****
-    os.system(" export ENABLE_FORCE_V2_CONTROL = 1")
-    # export ENABLE_FORCE_V2_CONTROL = 1
-    global_config = tf.ConfigProto(log_device_placement=False)
-    custom_op = global_config.graph_options.rewrite_options.custom_optimizers.add()
-    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")
-    npu_keras_sess = set_keras_session_npu_config(config=global_config)
     # ***** npu modify end *****
 
     description = ("Train a CNN to classify four cosmological models\n" +
@@ -223,8 +212,26 @@ if __name__ == '__main__':
                         help="specific gpu id to use")
     parser.add_argument("-datapath", "--datapath", type=str, default="/cache/dataset/data",
                         help="specific gpu id to use")
+    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()
 
+    # npu_keras_sess = set_keras_session_npu_config()
+    # ***** npu modify begin *****
+    os.system(" export ENABLE_FORCE_V2_CONTROL = 1")
+    # export ENABLE_FORCE_V2_CONTROL = 1
+    global_config = tf.ConfigProto(log_device_placement=False)
+    custom_op = global_config.graph_options.rewrite_options.custom_optimizers.add()
+    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
+    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)
 
     noise_opts = {0: "clean", 1: "sigma035", 2: "sigma070"}
     noise_name = noise_opts[args.noise]
diff --git a/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_full_1p.sh
index 274129ace16858e26a22d8019c268ed82d2279dc..97be2b7ed88dcad00ebe8282faa0e7d2b00221e5 100644
--- a/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_full_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`         
     fi
 done
 
@@ -123,7 +126,8 @@ do
     python3 mgcnn_npu.py \
 	--datapath=${data_path}/data/ \
 	--iterations=${train_steps} \
-	--epochs=${train_epochs} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+	--epochs=${train_epochs} \
+    --dynamic_input ${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 
 
 done 
@@ -171,4 +175,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_performance_1p.sh
index 657a4a24350c97ed344d6d63f488192c9a6951d6..3d0535194aca7da1045beeba2be2dbff1e354225 100644
--- a/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/contrib/cv/MGCNN_ID1039_for_TensorFlow/test/train_performance_1p.sh
@@ -13,6 +13,7 @@ RANK_ID_START=0
 # 数据集路径,保持为空,不需要修改
 data_path=''
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要修改
 export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -78,6 +79,8 @@ do
 
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
+    elif [[ $para == --dynamic_input* ]];then
+        dynamic_input=`echo ${para#*=}`         
     fi
 done
 
@@ -123,7 +126,8 @@ do
     python3 mgcnn_npu.py \
 	--datapath=${data_path}/data/ \
 	--iterations=${train_steps} \
-	--epochs=${train_epochs} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+	--epochs=${train_epochs} \
+    --dynamic_input ${dynamic_input} > ${cur_path}test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 
 
 done 
@@ -171,4 +175,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/test/output/$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/contrib/cv/tprnn_ID1297_for_TensorFlow/post_tprnn_npu_code_chun/tprnn_train_human.py b/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/post_tprnn_npu_code_chun/tprnn_train_human.py
index 9d0f92adf728e93ad6727990ee3a8cbbc287d60a..7b5a086ece2879282bd434371a55383ed2e1331b 100644
--- a/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/post_tprnn_npu_code_chun/tprnn_train_human.py
+++ b/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/post_tprnn_npu_code_chun/tprnn_train_human.py
@@ -145,6 +145,10 @@ parser.add_argument(
 parser.add_argument(
     "--data_url", type=str, default="./dataset"
 )  # PyCharm插件传入的 Data Path in OBS路径
+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"
+    )
+
 
 #add
 parser.add_argument("--locals_dir", default="/data2/NRE_Check/wx1056345/ID1297_tprnn/data/h3.6m/dataset")
@@ -318,7 +322,12 @@ def train():
     custom_op.name = "NpuOptimizer"
     #add
     custom_op.parameter_map['dynamic_input'].b = True
-    custom_op.parameter_map["dynamic_graph_execute_mode"].s = tf.compat.as_bytes("lazy_recompile")
+    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.")
     ##混合精度
     custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("force_fp16")
 
diff --git a/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/test/train_performance_1p.sh
index af988dc747033804fa5d6f65d6e01347854415c8..6480b950598ae04017cdb837afed9455add1c281 100644
--- a/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/contrib/cv/tprnn_ID1297_for_TensorFlow/test/train_performance_1p.sh
@@ -14,6 +14,7 @@ RANK_ID_START=0
 data_path=''
 #预训练模型地址
 ckpt_path=''
+dynamic_input="1"
 
 #设置默认日志级别,不需要改
 #export ASCEND_GLOBAL_LOG_LEVEL=3
@@ -77,7 +78,9 @@ do
         data_path=`echo ${para#*=}`
     elif [[ $para == --ckpt_path* ]];then
         ckpt_path=`echo ${para#*=}`
-        fi
+   elif [[ $para == --dynamic_input* ]];then
+      dynamic_input=`echo ${para#*=}`         
+    fi
 done
 # #校验是否传入data_path,不需要修改
 # if [[$data_path == ""]];then
@@ -105,7 +108,8 @@ python3 tprnn_train_human.py \
      --locals_dir=${data_path} \
      --model_dir=$cur_path/result \
 	 --iterations=1000 \
-	 --test_every=2000 > ${cur_path}/test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
+	 --test_every=2000 \
+     --dynamic_input ${dynamic_input} > ${cur_path}/test/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1
 wait
 
 #训练结束时间，不需要修改
@@ -155,4 +159,5 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "TrainingTime = ${TrainingTime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "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 "Accuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+#echo "Accuracy = ${train_accuracy}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file