diff --git a/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/main.py b/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/main.py
index 5f7c2f953d88856756918a8cac8d005e16ee1978..c80a2ad7378d8af478833b3b12ec9bd4c8e6c7aa 100644
--- a/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/main.py
+++ b/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/main.py
@@ -40,6 +40,8 @@ from npu_bridge.estimator import npu_ops
 from tensorflow.core.protobuf.rewriter_config_pb2 import RewriterConfig
 
 from npu_bridge.npu_init import *
+from npu_bridge.estimator.npu import npu_plugin
+npu_plugin.set_device_sat_mode(1)
 
 flags = tf.app.flags
 flags.DEFINE_integer("epoch", 25, "Epoch to train [25]")
diff --git a/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/model.py b/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/model.py
index 7e3575453220342c28271588db2f04564df6e9b2..e22a821a11995010767d82b89aad7670ee7d05d3 100644
--- a/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/model.py
+++ b/TensorFlow/built-in/graph/DCGAN_ID0686_for_TensorFlow/model.py
@@ -318,22 +318,22 @@ class DCGAN(object):
           # modify for NPU start
           # 增加loss scale打印
           lossScale = tf.get_default_graph().get_tensor_by_name("loss_scale:0")
-          overflow_status_reduce_all = tf.get_default_graph().get_tensor_by_name("overflow_status_reduce_all:0")
-
-          # _, summary_str = self.sess.run([d_optim, self.d_sum],
-          #   feed_dict={
-          #     self.inputs: batch_images,
-          #     self.z: batch_z,
-          #     self.y:batch_labels,
-          #   })
-          l_s, overflow_status_reduce_all, _, summary_str = self.sess.run(
-            [lossScale, overflow_status_reduce_all, d_optim, self.d_sum], feed_dict={
-              self.inputs: batch_images,
-              self.z: batch_z,
-              self.y:batch_labels,
-            })
-          print("lossScale==========================:", l_s)
-          print("overflow_status_reduce_all is======:", overflow_status_reduce_all)
+          #overflow_status_reduce_all = tf.get_default_graph().get_tensor_by_name("overflow_status_reduce_all:0")
+
+          _, summary_str = self.sess.run([d_optim, self.d_sum],
+             feed_dict={
+               self.inputs: batch_images,
+               self.z: batch_z,
+               self.y:batch_labels,
+             })
+          #l_s, overflow_status_reduce_all, _, summary_str = self.sess.run(
+          #  [lossScale, overflow_status_reduce_all, d_optim, self.d_sum], feed_dict={
+          #    self.inputs: batch_images,
+          #    self.z: batch_z,
+          #    self.y:batch_labels,
+          #  })
+          #print("lossScale==========================:", l_s)
+          #print("overflow_status_reduce_all is======:", overflow_status_reduce_all)
           # 注释add summary提升性能
           # self.writer.add_summary(summary_str, counter)
           # modify for NPU end