diff --git a/PaddleCV/PaddleGAN/README.md b/PaddleCV/PaddleGAN/README.md
index c2e3fb4082c73e26f810374351aaeacbad8cb874..2c1de576970c8014dac3c51b39100758a542b6f1 100644
--- a/PaddleCV/PaddleGAN/README.md
+++ b/PaddleCV/PaddleGAN/README.md
@@ -21,7 +21,7 @@
 注意：
 1. StarGAN，AttGAN和STGAN由于梯度惩罚所需的操作目前只支持GPU，需使用GPU训练。
 2. GAN模型目前仅仅验证了单机单卡训练和预测结果。
-3. CGAN和DCGAN两个模型训练使用的数据集为MNIST数据集；StarGAN，AttGAN和STGAN的数据集为CelebA数据集。Pix2Pix和CycleGAN支持的数据集可以参考download.py中的cycle_pix_dataset。
+3. CGAN和DCGAN两个模型训练使用的数据集为MNIST数据集；StarGAN，AttGAN和STGAN的数据集为CelebA数据集。Pix2Pix和CycleGAN支持的数据集可以参考download.py中的cycle_pix_dataset。cityscapes数据集需要从[官方](https://www.cityscapes-dataset.com)下载数据，下载完之后使用`scripts/prepare_cityscapes_dataset.py`处理，处理后的文件夹命名为cityscapes并放入data目录下即可。
 4. PaddlePaddle1.5.1及之前的版本不支持在AttGAN和STGAN模型里的判别器加上的instance norm。如果要在判别器中加上instance norm，请源码编译develop分支并安装。
 5. 中间效果图保存在${output_dir}/test文件夹中。对于Pix2Pix来说，inputA 和inputB 代表输入的两种风格的图片，fakeB表示生成图片；对于CycleGAN来说，inputA表示输入图片，fakeB表示inputA根据生成的图片，cycA表示fakeB经过生成器重构出来的对应于inputA的重构图片；对于StarGAN，AttGAN和STGAN来说，第一行表示原图，之后的每一行都代表一种属性变换。
 6. infer过程使用的test_list文件和训练过程中使用的train_list具有相同格式，第一行为样本数量，第二行为属性，之后的行中第一个表示图片名称，之后的-1和1表示该图片是否拥有该属性(1为有该属性，-1为没有该属性)。
diff --git a/PaddleCV/PaddleGAN/download.py b/PaddleCV/PaddleGAN/download.py
index 295f8f1e8492b83ca8534c56942cb1a817696d7c..b3452325fda06a855f2a7a80aae74e65c18212b0 100644
--- a/PaddleCV/PaddleGAN/download.py
+++ b/PaddleCV/PaddleGAN/download.py
@@ -153,8 +153,8 @@ if __name__ == '__main__':
     args = parser.parse_args()
     cycle_pix_dataset = [
         'apple2orange', 'summer2winter_yosemite', 'horse2zebra', 'monet2photo',
-        'cezanne2photo', 'ukiyoe2photo', 'vangogh2photo', 'maps', 'cityscapes',
-        'facades', 'iphone2dslr_flower', 'ae_photos', 'mini'
+        'cezanne2photo', 'ukiyoe2photo', 'vangogh2photo', 'maps', 'facades',
+        'iphone2dslr_flower', 'ae_photos', 'mini'
     ]
 
     pwd = os.path.join(os.path.dirname(__file__), 'data')
diff --git a/PaddleCV/PaddleGAN/infer.py b/PaddleCV/PaddleGAN/infer.py
index 347852a267c22c43fa64b897b8fb1bec1295d6eb..9b2a1202032802d79f3180cfe25ae4145c6127d8 100644
--- a/PaddleCV/PaddleGAN/infer.py
+++ b/PaddleCV/PaddleGAN/infer.py
@@ -82,6 +82,7 @@ def infer(args):
         name='image_name', shape=[args.n_samples], dtype='int32')
 
     model_name = 'net_G'
+
     if args.model_net == 'CycleGAN':
         py_reader = fluid.io.PyReader(
             feed_list=[input, image_name],
diff --git a/PaddleCV/PaddleGAN/scripts/prepare_cityscapes_dataset.py b/PaddleCV/PaddleGAN/scripts/prepare_cityscapes_dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..0dc8422ac32eacf0f85c48b596cc8e0cb669f388
--- /dev/null
+++ b/PaddleCV/PaddleGAN/scripts/prepare_cityscapes_dataset.py
@@ -0,0 +1,70 @@
+import os
+import argparse
+import functools
+import glob
+from PIL import Image
+''' Based on https://github.com/junyanz/CycleGAN'''
+
+
+def load_image(path):
+    return Image.open(path).convert('RGB').resize((256, 256))
+
+
+def propress_cityscapes(gtFine_dir, leftImg8bit_dir, output_dir, phase):
+    save_dir = os.path.join(output_dir, phase)
+    try:
+        os.makedirs(save_dir)
+    except Exception as e:
+        print("{} makedirs".format(e))
+        pass
+    try:
+        os.makedirs(os.path.join(save_dir, 'A'))
+    except Exception as e:
+        print("{} makedirs".format(e))
+    try:
+        os.makedirs(os.path.join(save_dir, 'B'))
+    except Exception as e:
+        print("{} makedirs".format(e))
+
+    seg_expr = os.path.join(gtFine_dir, phase, "*", "*_color.png")
+    seg_paths = glob.glob(seg_expr)
+    seg_paths = sorted(seg_paths)
+
+    photo_expr = os.path.join(leftImg8bit_dir, phase, "*", '*_leftImg8bit.png')
+    photo_paths = glob.glob(photo_expr)
+    photo_paths = sorted(photo_paths)
+
+    assert len(seg_paths) == len(photo_paths), \
+          "[%d] gtFine images NOT match [%d] leftImg8bit images. Aborting." % (len(segmap_paths), len(photo_paths))
+
+    for i, (seg_path, photo_path) in enumerate(zip(seg_paths, photo_paths)):
+        seg_image = load_image(seg_path)
+        photo_image = load_image(photo_path)
+        # save image
+        save_path = os.path.join(save_dir, 'A', "%d_A.jpg" % i)
+        photo_image.save(save_path, format='JPEG', subsampling=0, quality=100)
+        save_path = os.path.join(save_dir, 'B', "%d_B.jpg" % i)
+        seg_image.save(save_path, format='JPEG', subsampling=0, quality=100)
+
+        if i % 10 == 0:
+            print("proprecess %d ~ %d images." % (i, i + 10))
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description=__doc__)
+    # yapf: disable
+    parser.add_argument('--gtFine_dir',       type=str,     default=None,       help='Path to Cityscapes gtFine directory.')
+    parser.add_argument('--leftImg8bit_dir',  type=str,     default=None,       help='Path to Cityscapes leftImg8bit_trainvaltest directory.')
+    parser.add_argument('--output_dir',       type=str,     default=None,       help='Path to output Cityscapes directory.')
+    # yapf: enable
+    args = parser.parse_args()
+
+    print('Preparing Cityscapes Dataset for val phase')
+    propress_cityscapes(args.gtFine_dir, args.leftImg8bit_dir, args.output_dir,
+                        'val')
+
+    print('Preparing Cityscapes Dataset for train phase')
+    propress_cityscapes(args.gtFine_dir, args.leftImg8bit_dir, args.output_dir,
+                        'train')
+
+    print("DONE!!!")
diff --git a/PaddleCV/PaddleGAN/scripts/run_attgan.sh b/PaddleCV/PaddleGAN/scripts/run_attgan.sh
index b0fce2de8a3e03346cfae5bc91717130ba25c015..c339d05857765b480b910d7ff64701d8d061d4b2 100644
--- a/PaddleCV/PaddleGAN/scripts/run_attgan.sh
+++ b/PaddleCV/PaddleGAN/scripts/run_attgan.sh
@@ -1 +1 @@
-python train.py --model_net AttGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt  --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 120 --output ./output/attgan/ >log_out 2>log_err
+python train.py --model_net AttGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt  --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 120 --dis_norm instance_norm --output ./output/attgan/ >log_out 2>log_err
diff --git a/PaddleCV/PaddleGAN/scripts/run_stgan.sh b/PaddleCV/PaddleGAN/scripts/run_stgan.sh
index 44d616112c13b5238b954b27861a59c69e9dc3c2..d258de51930cec8d82f147039ad3d622610ca8e7 100644
--- a/PaddleCV/PaddleGAN/scripts/run_stgan.sh
+++ b/PaddleCV/PaddleGAN/scripts/run_stgan.sh
@@ -1 +1 @@
-python train.py --model_net STGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 50 --output ./output/stgan/ >log_out 2>log_err
+python train.py --model_net STGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 50 --dis_norm instance_norm --output ./output/stgan/ >log_out 2>log_err
diff --git a/PaddleCV/PaddleGAN/train.py b/PaddleCV/PaddleGAN/train.py
index be10d4ac4e785efa2e3014d0312b6dbd194b7e38..62da9d8afac568dcc23b51c541f0ba805ce077c8 100644
--- a/PaddleCV/PaddleGAN/train.py
+++ b/PaddleCV/PaddleGAN/train.py
@@ -30,7 +30,8 @@ import trainer
 def train(cfg):
 
     MODELS = [
-        "CGAN", "DCGAN", "Pix2pix", "CycleGAN", "StarGAN", "AttGAN", "STGAN", "SPADE"
+        "CGAN", "DCGAN", "Pix2pix", "CycleGAN", "StarGAN", "AttGAN", "STGAN",
+        "SPADE"
     ]
     if cfg.model_net not in MODELS:
         raise NotImplementedError("{} is not support!".format(cfg.model_net))
diff --git a/PaddleCV/PaddleGAN/trainer/SPADE.py b/PaddleCV/PaddleGAN/trainer/SPADE.py
index 5c427c4a1350e3e10f1afe8694da0ec10b1fd714..1ef1f4f74f45116ace16b94986e7d23ee95797ae 100644
--- a/PaddleCV/PaddleGAN/trainer/SPADE.py
+++ b/PaddleCV/PaddleGAN/trainer/SPADE.py
@@ -325,7 +325,7 @@ class SPADE(object):
 
         ### memory optim
         build_strategy = fluid.BuildStrategy()
-        build_strategy.enable_inplace = False
+        build_strategy.enable_inplace = True
         build_strategy.sync_batch_norm = False
 
         gen_trainer_program = fluid.CompiledProgram(