diff --git a/TensorFlow/built-in/cv/image_segmentation/DeepLabv3+out_ID0147_for_TensorFlow/DeepLabv3+_ID0147_for_TensorFlow/deeplab/model.py b/TensorFlow/built-in/cv/image_segmentation/DeepLabv3+out_ID0147_for_TensorFlow/DeepLabv3+_ID0147_for_TensorFlow/deeplab/model.py
index 311aaa1acb13cb445053ac12fa09e354423e56df..4f2f87c2f2a9eb88f4cadac52561b2d18edea211 100644
--- a/TensorFlow/built-in/cv/image_segmentation/DeepLabv3+out_ID0147_for_TensorFlow/DeepLabv3+_ID0147_for_TensorFlow/deeplab/model.py
+++ b/TensorFlow/built-in/cv/image_segmentation/DeepLabv3+out_ID0147_for_TensorFlow/DeepLabv3+_ID0147_for_TensorFlow/deeplab/model.py
@@ -57,6 +57,7 @@ from tensorflow.contrib import slim as contrib_slim
 from deeplab.core import dense_prediction_cell
 from deeplab.core import feature_extractor
 from deeplab.core import utils
+from npu_bridge.npu_init import *
 
 slim = contrib_slim
 
@@ -529,11 +530,12 @@ def extract_features(images,
           if model_options.aspp_with_concat_projection:
             concat_logits = slim.conv2d(
                 concat_logits, depth, 1, scope=CONCAT_PROJECTION_SCOPE)
-            concat_logits = slim.dropout(
-                concat_logits,
-                keep_prob=0.9,
-                is_training=is_training,
-                scope=CONCAT_PROJECTION_SCOPE + '_dropout')
+            if is_training:
+                concat_logits = npu_ops.dropout(
+                    concat_logits,
+                    keep_prob=0.9,
+                    name=CONCAT_PROJECTION_SCOPE + '_dropout'
+                )
           if (model_options.add_image_level_feature and
               model_options.aspp_with_squeeze_and_excitation):
             concat_logits *= image_feature