diff --git a/examples/bert/bert_classifier.py b/examples/bert/bert_classifier.py
index e3c9726c9a1eb257748e7a8d2fb35e316b7bd80b..3d47ecb5d6b5b38f4a691ef0268ffc301bcfb3eb 100644
--- a/examples/bert/bert_classifier.py
+++ b/examples/bert/bert_classifier.py
@@ -14,14 +14,14 @@
 """BERT fine-tuning in Paddle Dygraph Mode."""
 
 import paddle.fluid as fluid
-from hapi.metrics import Accuracy
-from hapi.configure import Config
-from hapi.text.bert import BertEncoder
+from paddle.incubate.hapi.metrics import Accuracy
+from paddle.incubate.hapi.configure import Config
+from paddle.incubate.hapi.text.bert import BertEncoder
 from paddle.fluid.dygraph import Linear, Layer
-from hapi.loss import SoftmaxWithCrossEntropy
-from hapi.model import set_device, Model, Input
-import hapi.text.tokenizer.tokenization as tokenization
-from hapi.text.bert import BertConfig, BertDataLoader, BertInputExample, make_optimizer
+from paddle.incubate.hapi.loss import SoftmaxWithCrossEntropy
+from paddle.incubate.hapi.model import set_device, Model, Input
+import paddle.incubate.hapi.text.tokenizer.tokenization as tokenization
+from paddle.incubate.hapi.text.bert import BertConfig, BertDataLoader, BertInputExample, make_optimizer
 
 
 class ClsModelLayer(Model):
@@ -157,7 +157,8 @@ def main():
         labels,
         device=device)
 
-    cls_model.bert_layer.load("./bert_uncased_L-12_H-768_A-12/bert", reset_optimizer=True)
+    cls_model.bert_layer.load(
+        "./bert_uncased_L-12_H-768_A-12/bert", reset_optimizer=True)
 
     # do train
     cls_model.fit(train_data=train_dataloader.dataloader,
diff --git a/examples/bert_leveldb/bert_classifier.py b/examples/bert_leveldb/bert_classifier.py
index 51b1192f83a89de6491d82f1748bbead345df742..02d112fe7009eab8230ef51bbbdd5d8ed9958aab 100644
--- a/examples/bert_leveldb/bert_classifier.py
+++ b/examples/bert_leveldb/bert_classifier.py
@@ -14,14 +14,14 @@
 """BERT fine-tuning in Paddle Dygraph Mode."""
 
 import paddle.fluid as fluid
-from hapi.metrics import Accuracy
-from hapi.configure import Config
-from hapi.text.bert import BertEncoder
+from paddle.incubate.hapi.metrics import Accuracy
+from paddle.incubate.hapi.configure import Config
+from paddle.incubate.hapi.text.bert import BertEncoder
 from paddle.fluid.dygraph import Linear, Layer
-from hapi.loss import SoftmaxWithCrossEntropy
-from hapi.model import set_device, Model, Input
-import hapi.text.tokenizer.tokenization as tokenization
-from hapi.text.bert import BertConfig, BertDataLoader, BertInputExample, make_optimizer
+from paddle.incubate.hapi.loss import SoftmaxWithCrossEntropy
+from paddle.incubate.hapi.model import set_device, Model, Input
+import paddle.incubate.hapi.text.tokenizer.tokenization as tokenization
+from paddle.incubate.hapi.text.bert import BertConfig, BertDataLoader, BertInputExample, make_optimizer
 
 
 class ClsModelLayer(Model):
@@ -159,7 +159,8 @@ def main():
         labels,
         device=device)
 
-    cls_model.bert_layer.load("./bert_uncased_L-12_H-768_A-12/bert", reset_optimizer=True)
+    cls_model.bert_layer.load(
+        "./bert_uncased_L-12_H-768_A-12/bert", reset_optimizer=True)
 
     # do train
     cls_model.fit(train_data=train_dataloader.dataloader,
diff --git a/examples/bmn/bmn_metric.py b/examples/bmn/bmn_metric.py
index cbcad9a1e15d5356127c748194ac907bcfda5967..e4ba8aec1c2c7d4673e89b706a6e830204879bff 100644
--- a/examples/bmn/bmn_metric.py
+++ b/examples/bmn/bmn_metric.py
@@ -20,7 +20,7 @@ import json
 
 sys.path.append('../')
 
-from hapi.metrics import Metric
+from paddle.incubate.hapi.metrics import Metric
 from bmn_utils import boundary_choose, bmn_post_processing
 
 
diff --git a/examples/bmn/eval.py b/examples/bmn/eval.py
index c8d4f26caf4b7d4e56ee88623f90b6d40a6e02dd..3fd8aea7792eefba0ee0096db703628fef77bcd9 100644
--- a/examples/bmn/eval.py
+++ b/examples/bmn/eval.py
@@ -18,7 +18,7 @@ import sys
 import logging
 import paddle.fluid as fluid
 
-from hapi.model import set_device, Input
+from paddle.incubate.hapi.model import set_device, Input
 
 from modeling import bmn, BmnLoss
 from bmn_metric import BmnMetric
diff --git a/examples/bmn/modeling.py b/examples/bmn/modeling.py
index bfd65b318ad5f0c8a3ea2191f9a7c2a4d18b691e..5fac438879b61d42e2adad7114dd80cd9693c61c 100644
--- a/examples/bmn/modeling.py
+++ b/examples/bmn/modeling.py
@@ -17,9 +17,9 @@ from paddle.fluid import ParamAttr
 import numpy as np
 import math
 
-from hapi.model import Model
-from hapi.loss import Loss
-from hapi.download import get_weights_path_from_url
+from paddle.incubate.hapi.model import Model
+from paddle.incubate.hapi.loss import Loss
+from paddle.incubate.hapi.download import get_weights_path_from_url
 
 __all__ = ["BMN", "BmnLoss", "bmn"]
 
diff --git a/examples/bmn/predict.py b/examples/bmn/predict.py
index b984c06fa8d4863b437e22e91b9d633638994c77..e96e837ccfbbb6e5c56fb12f4353bd2cca69a89e 100644
--- a/examples/bmn/predict.py
+++ b/examples/bmn/predict.py
@@ -18,7 +18,7 @@ import os
 import logging
 import paddle.fluid as fluid
 
-from hapi.model import set_device, Input
+from paddle.incubate.hapi.model import set_device, Input
 
 from modeling import bmn, BmnLoss
 from bmn_metric import BmnMetric
diff --git a/examples/bmn/reader.py b/examples/bmn/reader.py
index d8f125e10337a6e3fb9b241d4893ec96c86eba62..36780b2f3e1044a22626374ba1fa5d1730af0301 100644
--- a/examples/bmn/reader.py
+++ b/examples/bmn/reader.py
@@ -21,7 +21,7 @@ import sys
 
 sys.path.append('../')
 
-from hapi.distributed import DistributedBatchSampler
+from paddle.incubate.hapi.distributed import DistributedBatchSampler
 from paddle.io import Dataset, DataLoader
 
 logger = logging.getLogger(__name__)
diff --git a/examples/bmn/train.py b/examples/bmn/train.py
index 1e2bf449113656060e759c50fc933fd15572ef0b..2a25c1ac76a5dcc0515232756a03b28b611e28ce 100644
--- a/examples/bmn/train.py
+++ b/examples/bmn/train.py
@@ -18,7 +18,7 @@ import logging
 import sys
 import os
 
-from hapi.model import set_device, Input
+from paddle.incubate.hapi.model import set_device, Input
 
 from reader import BmnDataset
 from config_utils import *
diff --git a/examples/cyclegan/cyclegan.py b/examples/cyclegan/cyclegan.py
index 076e13d3ebe079fbb639d6ec80d432403af03cfd..f6a2dae378eb3d97f0345329dc8b7ecb2bb6585e 100644
--- a/examples/cyclegan/cyclegan.py
+++ b/examples/cyclegan/cyclegan.py
@@ -19,8 +19,8 @@ from __future__ import print_function
 import numpy as np
 
 import paddle.fluid as fluid
-from hapi.model import Model
-from hapi.loss import Loss
+from paddle.incubate.hapi.model import Model
+from paddle.incubate.hapi.loss import Loss
 
 from layers import ConvBN, DeConvBN
 
diff --git a/examples/cyclegan/infer.py b/examples/cyclegan/infer.py
index 2fb2b35eefc8ffb1b4fc10f58ce519e998415055..bbefaf6db4b131d68ac4d3cb84d5a658a5c61bac 100644
--- a/examples/cyclegan/infer.py
+++ b/examples/cyclegan/infer.py
@@ -25,7 +25,7 @@ from PIL import Image
 from scipy.misc import imsave
 
 import paddle.fluid as fluid
-from hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.model import Model, Input, set_device
 
 from check import check_gpu, check_version
 from cyclegan import Generator, GeneratorCombine
diff --git a/examples/cyclegan/test.py b/examples/cyclegan/test.py
index 67f7183e2229ec9509e23e9ac81dc54122290056..ba7d5c5889be77d483d5321edba7c2ac8265cf53 100644
--- a/examples/cyclegan/test.py
+++ b/examples/cyclegan/test.py
@@ -22,7 +22,7 @@ import numpy as np
 from scipy.misc import imsave
 
 import paddle.fluid as fluid
-from hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.model import Model, Input, set_device
 
 from check import check_gpu, check_version
 from cyclegan import Generator, GeneratorCombine
diff --git a/examples/cyclegan/train.py b/examples/cyclegan/train.py
index 4ca77dd66996afcc00218eafaafefa25a2a7c771..de9ed63b5cf4a16bdf2dbc607f74f61f208ba733 100644
--- a/examples/cyclegan/train.py
+++ b/examples/cyclegan/train.py
@@ -24,7 +24,7 @@ import time
 
 import paddle
 import paddle.fluid as fluid
-from hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.model import Model, Input, set_device
 
 from check import check_gpu, check_version
 from cyclegan import Generator, Discriminator, GeneratorCombine, GLoss, DLoss
@@ -78,12 +78,12 @@ def main():
     g_AB.prepare(inputs=[input_A], device=FLAGS.device)
     g_BA.prepare(inputs=[input_B], device=FLAGS.device)
 
-    g.prepare(g_optimizer, GLoss(), inputs=[input_A, input_B],
-        device=FLAGS.device)
-    d_A.prepare(da_optimizer, DLoss(), inputs=[input_B, fake_B],
-        device=FLAGS.device)
-    d_B.prepare(db_optimizer, DLoss(), inputs=[input_A, fake_A],
-        device=FLAGS.device)
+    g.prepare(
+        g_optimizer, GLoss(), inputs=[input_A, input_B], device=FLAGS.device)
+    d_A.prepare(
+        da_optimizer, DLoss(), inputs=[input_B, fake_B], device=FLAGS.device)
+    d_B.prepare(
+        db_optimizer, DLoss(), inputs=[input_A, fake_A], device=FLAGS.device)
 
     if FLAGS.resume:
         g.load(FLAGS.resume)
diff --git a/examples/handwritten_number_recognition/mnist.py b/examples/handwritten_number_recognition/mnist.py
index 36db96ca3715e877c443480bbda598a7545dc1b7..a3b77dab56ea549e07f7e071afab19eb18d08e51 100644
--- a/examples/handwritten_number_recognition/mnist.py
+++ b/examples/handwritten_number_recognition/mnist.py
@@ -19,12 +19,12 @@ import argparse
 
 from paddle import fluid
 from paddle.fluid.optimizer import Momentum
-from hapi.datasets.mnist import MNIST as MnistDataset
+from paddle.incubate.hapi.datasets.mnist import MNIST as MnistDataset
 
-from hapi.model import Input, set_device
-from hapi.loss import CrossEntropy
-from hapi.metrics import Accuracy
-from hapi.vision.models import LeNet
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.loss import CrossEntropy
+from paddle.incubate.hapi.metrics import Accuracy
+from paddle.incubate.hapi.vision.models import LeNet
 
 
 def main():
diff --git a/examples/image_classification/imagenet_dataset.py b/examples/image_classification/imagenet_dataset.py
index 27c41d6fb4cfe752f311d2e2c65380aa29bc4323..27a90091e301ce039b129f6f74518a2bd5779557 100644
--- a/examples/image_classification/imagenet_dataset.py
+++ b/examples/image_classification/imagenet_dataset.py
@@ -18,8 +18,8 @@ import math
 import random
 import numpy as np
 
-from hapi.datasets import DatasetFolder
-from hapi.vision.transforms import transforms
+from paddle.incubate.hapi.datasets import DatasetFolder
+from paddle.incubate.hapi.vision.transforms import transforms
 from paddle import fluid
 
 
diff --git a/examples/image_classification/main.py b/examples/image_classification/main.py
index e5aea412fbeb619d90002f3c9f817788b021821a..ff0c95b534c6ec74792ff4f9962f1563fa4698dd 100644
--- a/examples/image_classification/main.py
+++ b/examples/image_classification/main.py
@@ -27,11 +27,11 @@ import paddle.fluid as fluid
 from paddle.fluid.dygraph.parallel import ParallelEnv
 from paddle.io import BatchSampler, DataLoader
 
-from hapi.model import Input, set_device
-from hapi.loss import CrossEntropy
-from hapi.distributed import DistributedBatchSampler
-from hapi.metrics import Accuracy
-import hapi.vision.models as models
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.loss import CrossEntropy
+from paddle.incubate.hapi.distributed import DistributedBatchSampler
+from paddle.incubate.hapi.metrics import Accuracy
+import paddle.incubate.hapi.vision.models as models
 
 from imagenet_dataset import ImageNetDataset
 
diff --git a/examples/ocr/eval.py b/examples/ocr/eval.py
index 1adffa5401679ab0d49cc586c0238ce1c01fa1b8..6b5fd48bc9ee000d7a4c4e19818931f87af4a47c 100644
--- a/examples/ocr/eval.py
+++ b/examples/ocr/eval.py
@@ -19,8 +19,8 @@ import functools
 import paddle.fluid.profiler as profiler
 import paddle.fluid as fluid
 
-from hapi.model import Input, set_device
-from hapi.vision.transforms import BatchCompose
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.vision.transforms import BatchCompose
 
 from utility import add_arguments, print_arguments
 from utility import SeqAccuracy, LoggerCallBack, SeqBeamAccuracy
diff --git a/examples/ocr/predict.py b/examples/ocr/predict.py
index 242d4f80b9bbdbade61b0cc086196482ffa588e9..f1eac38751a19eb1cf494f673e9680a4ece1f369 100644
--- a/examples/ocr/predict.py
+++ b/examples/ocr/predict.py
@@ -25,9 +25,9 @@ from PIL import Image
 import paddle.fluid.profiler as profiler
 import paddle.fluid as fluid
 
-from hapi.model import Input, set_device
-from hapi.datasets.folder import ImageFolder
-from hapi.vision.transforms import BatchCompose
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.datasets.folder import ImageFolder
+from paddle.incubate.hapi.vision.transforms import BatchCompose
 
 from utility import add_arguments, print_arguments
 from utility import postprocess, index2word
diff --git a/examples/ocr/seq2seq_attn.py b/examples/ocr/seq2seq_attn.py
index 66da91ce7d84c458bd6424da8c364a9ed25776c4..117749cb27d2b41c7e308e5540433465475a7368 100644
--- a/examples/ocr/seq2seq_attn.py
+++ b/examples/ocr/seq2seq_attn.py
@@ -19,9 +19,9 @@ import paddle.fluid as fluid
 import paddle.fluid.layers as layers
 from paddle.fluid.layers import BeamSearchDecoder
 
-from hapi.text import RNNCell, RNN, DynamicDecode
-from hapi.model import Model
-from hapi.loss import Loss
+from paddle.incubate.hapi.text import RNNCell, RNN, DynamicDecode
+from paddle.incubate.hapi.model import Model
+from paddle.incubate.hapi.loss import Loss
 
 
 class ConvBNPool(fluid.dygraph.Layer):
diff --git a/examples/ocr/train.py b/examples/ocr/train.py
index d72173dfde7791b53af80f04697f8e3defd01445..b69c90e752e125da69028d50b02a83edc06b09f3 100644
--- a/examples/ocr/train.py
+++ b/examples/ocr/train.py
@@ -24,8 +24,8 @@ import functools
 import paddle.fluid.profiler as profiler
 import paddle.fluid as fluid
 
-from hapi.model import Input, set_device
-from hapi.vision.transforms import BatchCompose
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.vision.transforms import BatchCompose
 
 from utility import add_arguments, print_arguments
 from utility import SeqAccuracy, LoggerCallBack
diff --git a/examples/ocr/utility.py b/examples/ocr/utility.py
index d47b3f17d16452c1292402abc15b534eec4b3459..59b7f4206b23af6cdfe162596c4dc2f78e9b3a06 100644
--- a/examples/ocr/utility.py
+++ b/examples/ocr/utility.py
@@ -21,8 +21,8 @@ import numpy as np
 import paddle.fluid as fluid
 import six
 
-from hapi.metrics import Metric
-from hapi.callbacks import ProgBarLogger
+from paddle.incubate.hapi.metrics import Metric
+from paddle.incubate.hapi.callbacks import ProgBarLogger
 
 
 def print_arguments(args):
diff --git a/examples/sentiment_classification/models.py b/examples/sentiment_classification/models.py
index 313b928778f64001c5b37888bc546d6ff33bd970..7efaff520725fc41ff0ed928d1e260111e7103c8 100644
--- a/examples/sentiment_classification/models.py
+++ b/examples/sentiment_classification/models.py
@@ -15,13 +15,13 @@ import paddle.fluid as fluid
 from paddle.fluid.dygraph.nn import Linear, Embedding
 from paddle.fluid.dygraph.base import to_variable
 import numpy as np
-from hapi.model import Model
-from hapi.text.text import GRUEncoderLayer as BiGRUEncoder
-from hapi.text.test import BOWEncoder, CNNEncoder, GRUEncoder
+from paddle.incubate.hapi.model import Model
+from paddle.incubate.hapi.text.text import GRUEncoderLayer as BiGRUEncoder
+from paddle.incubate.hapi.text.test import BOWEncoder, CNNEncoder, GRUEncoder
 
 
 class CNN(Model):
-    def __init__(self,  dict_dim, batch_size, seq_len):
+    def __init__(self, dict_dim, batch_size, seq_len):
         super(CNN, self).__init__()
         self.dict_dim = dict_dim
         self.emb_dim = 128
@@ -36,15 +36,19 @@ class CNN(Model):
             dict_size=self.dict_dim + 1,
             emb_dim=self.emb_dim,
             seq_len=self.seq_len,
-            filter_size= self.win_size,
-            num_filters= self.hid_dim,
-            hidden_dim= self.hid_dim,
+            filter_size=self.win_size,
+            num_filters=self.hid_dim,
+            hidden_dim=self.hid_dim,
             padding_idx=None,
             act='tanh')
-        self._fc1 = Linear(input_dim = self.hid_dim*self.seq_len, output_dim=self.fc_hid_dim, act="softmax")
-        self._fc_prediction = Linear(input_dim = self.fc_hid_dim,
-                                 output_dim = self.class_dim,
-                                 act="softmax")
+        self._fc1 = Linear(
+            input_dim=self.hid_dim * self.seq_len,
+            output_dim=self.fc_hid_dim,
+            act="softmax")
+        self._fc_prediction = Linear(
+            input_dim=self.fc_hid_dim,
+            output_dim=self.class_dim,
+            act="softmax")
 
     def forward(self, inputs):
         conv_3 = self._encoder(inputs)
@@ -69,11 +73,14 @@ class BOW(Model):
             padding_idx=None,
             bow_dim=self.hid_dim,
             seq_len=self.seq_len)
-        self._fc1 = Linear(input_dim = self.hid_dim, output_dim=self.hid_dim, act="tanh")
-        self._fc2 = Linear(input_dim = self.hid_dim, output_dim=self.fc_hid_dim, act="tanh")
-        self._fc_prediction = Linear(input_dim = self.fc_hid_dim,
-                                 output_dim = self.class_dim,
-                                 act="softmax")
+        self._fc1 = Linear(
+            input_dim=self.hid_dim, output_dim=self.hid_dim, act="tanh")
+        self._fc2 = Linear(
+            input_dim=self.hid_dim, output_dim=self.fc_hid_dim, act="tanh")
+        self._fc_prediction = Linear(
+            input_dim=self.fc_hid_dim,
+            output_dim=self.class_dim,
+            act="softmax")
 
     def forward(self, inputs):
         bow_1 = self._encoder(inputs)
@@ -94,10 +101,12 @@ class GRU(Model):
         self.class_dim = 2
         self.batch_size = batch_size
         self.seq_len = seq_len
-        self._fc1 = Linear(input_dim=self.hid_dim, output_dim=self.fc_hid_dim, act="tanh")
-        self._fc_prediction = Linear(input_dim=self.fc_hid_dim,
-                                 output_dim=self.class_dim,
-                                 act="softmax")
+        self._fc1 = Linear(
+            input_dim=self.hid_dim, output_dim=self.fc_hid_dim, act="tanh")
+        self._fc_prediction = Linear(
+            input_dim=self.fc_hid_dim,
+            output_dim=self.class_dim,
+            act="softmax")
         self._encoder = GRUEncoder(
             dict_size=self.dict_dim + 1,
             emb_dim=self.emb_dim,
@@ -112,7 +121,7 @@ class GRU(Model):
         prediction = self._fc_prediction(fc_1)
         return prediction
 
-        
+
 class BiGRU(Model):
     def __init__(self, dict_dim, batch_size, seq_len):
         super(BiGRU, self).__init__()
@@ -130,11 +139,13 @@ class BiGRU(Model):
             is_sparse=False)
         h_0 = np.zeros((self.batch_size, self.hid_dim), dtype="float32")
         h_0 = to_variable(h_0)
-        self._fc1 = Linear(input_dim = self.hid_dim, output_dim=self.hid_dim*3)
-        self._fc2 = Linear(input_dim = self.hid_dim*2, output_dim=self.fc_hid_dim, act="tanh")
-        self._fc_prediction = Linear(input_dim=self.fc_hid_dim,
-                                 output_dim=self.class_dim,
-                                 act="softmax")
+        self._fc1 = Linear(input_dim=self.hid_dim, output_dim=self.hid_dim * 3)
+        self._fc2 = Linear(
+            input_dim=self.hid_dim * 2, output_dim=self.fc_hid_dim, act="tanh")
+        self._fc_prediction = Linear(
+            input_dim=self.fc_hid_dim,
+            output_dim=self.class_dim,
+            act="softmax")
         self._encoder = BiGRUEncoder(
             grnn_hidden_dim=self.hid_dim,
             input_dim=self.hid_dim * 3,
@@ -144,7 +155,8 @@ class BiGRU(Model):
 
     def forward(self, inputs):
         emb = self.embedding(inputs)
-        emb = fluid.layers.reshape(emb, shape=[self.batch_size, -1, self.hid_dim])
+        emb = fluid.layers.reshape(
+            emb, shape=[self.batch_size, -1, self.hid_dim])
         fc_1 = self._fc1(emb)
         encoded_vector = self._encoder(fc_1)
         encoded_vector = fluid.layers.tanh(encoded_vector)
diff --git a/examples/sentiment_classification/sentiment_classifier.py b/examples/sentiment_classification/sentiment_classifier.py
index b5f6a0d9845420f3d77e97b989cbdd44fc0b38a0..7bd2d6a974f1cd3c01fa7fa909eff7babba258b3 100644
--- a/examples/sentiment_classification/sentiment_classifier.py
+++ b/examples/sentiment_classification/sentiment_classifier.py
@@ -13,14 +13,13 @@
 # limitations under the License.
 """Sentiment Classification in Paddle Dygraph Mode. """
 
-
 from __future__ import print_function
 import numpy as np
 import paddle.fluid as fluid
-from hapi.model import set_device, Model, CrossEntropy, Input
-from hapi.configure import Config
-from hapi.text.senta import SentaProcessor
-from hapi.metrics import Accuracy
+from paddle.incubate.hapi.model import set_device, Model, CrossEntropy, Input
+from paddle.incubate.hapi.configure import Config
+from paddle.incubate.hapi.text.senta import SentaProcessor
+from paddle.incubate.hapi.metrics import Accuracy
 from models import CNN, BOW, GRU, BiGRU
 import json
 import os
@@ -32,12 +31,14 @@ args.Print()
 device = set_device("gpu" if args.use_cuda else "cpu")
 dev_count = fluid.core.get_cuda_device_count() if args.use_cuda else 1
 
+
 def main():
     if args.do_train:
         train()
     elif args.do_infer:
         infer()
 
+
 def train():
     fluid.enable_dygraph(device)
     processor = SentaProcessor(
@@ -66,31 +67,28 @@ def train():
         epoch=args.epoch,
         shuffle=False)
     if args.model_type == 'cnn_net':
-        model = CNN( args.vocab_size, args.batch_size,
-                     args.padding_size)
+        model = CNN(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'bow_net':
-        model = BOW( args.vocab_size, args.batch_size,
-                     args.padding_size)
+        model = BOW(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'gru_net':
-        model = GRU( args.vocab_size, args.batch_size,
-                     args.padding_size)
+        model = GRU(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'bigru_net':
-        model = BiGRU( args.vocab_size, args.batch_size,
-                       args.padding_size)
-    
-    optimizer = fluid.optimizer.Adagrad(learning_rate=args.lr, parameter_list=model.parameters()) 
-    
+        model = BiGRU(args.vocab_size, args.batch_size, args.padding_size)
+
+    optimizer = fluid.optimizer.Adagrad(
+        learning_rate=args.lr, parameter_list=model.parameters())
+
     inputs = [Input([None, None], 'int64', name='doc')]
     labels = [Input([None, 1], 'int64', name='label')]
-    
+
     model.prepare(
         optimizer,
         CrossEntropy(),
-        Accuracy(topk=(1,)),
+        Accuracy(topk=(1, )),
         inputs,
         labels,
         device=device)
-    
+
     model.fit(train_data=train_data_generator,
               eval_data=eval_data_generator,
               batch_size=args.batch_size,
@@ -99,6 +97,7 @@ def train():
               eval_freq=args.eval_freq,
               save_freq=args.save_freq)
 
+
 def infer():
     fluid.enable_dygraph(device)
     processor = SentaProcessor(
@@ -114,38 +113,37 @@ def infer():
         epoch=1,
         shuffle=False)
     if args.model_type == 'cnn_net':
-        model_infer = CNN( args.vocab_size, args.batch_size,
-                           args.padding_size)
+        model_infer = CNN(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'bow_net':
-        model_infer = BOW( args.vocab_size, args.batch_size,
-                           args.padding_size)
+        model_infer = BOW(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'gru_net':
-        model_infer = GRU( args.vocab_size, args.batch_size,
-                           args.padding_size)
+        model_infer = GRU(args.vocab_size, args.batch_size, args.padding_size)
     elif args.model_type == 'bigru_net':
-        model_infer = BiGRU( args.vocab_size, args.batch_size,
-                             args.padding_size)
-    
+        model_infer = BiGRU(args.vocab_size, args.batch_size,
+                            args.padding_size)
+
     print('Do inferring ...... ')
     inputs = [Input([None, None], 'int64', name='doc')]
     model_infer.prepare(
-        None,
-        CrossEntropy(),
-        Accuracy(topk=(1,)),
-        inputs,
-        device=device)
+        None, CrossEntropy(), Accuracy(topk=(1, )), inputs, device=device)
     model_infer.load(args.checkpoints, reset_optimizer=True)
     preds = model_infer.predict(test_data=infer_data_generator)
     preds = np.array(preds[0]).reshape((-1, 2))
 
     if args.output_dir:
         with open(os.path.join(args.output_dir, 'predictions.json'), 'w') as w:
-            
+
             for p in range(len(preds)):
                 label = np.argmax(preds[p])
-                result = json.dumps({'index': p, 'label': label, 'probs': preds[p].tolist()})
-                w.write(result+'\n')
-        print('Predictions saved at '+os.path.join(args.output_dir, 'predictions.json'))
+                result = json.dumps({
+                    'index': p,
+                    'label': label,
+                    'probs': preds[p].tolist()
+                })
+                w.write(result + '\n')
+        print('Predictions saved at ' + os.path.join(args.output_dir,
+                                                     'predictions.json'))
+
 
 if __name__ == '__main__':
     main()
diff --git a/examples/seq2seq/predict.py b/examples/seq2seq/predict.py
index 930c2e5189469ed174da02e9cf5d6e6e8c2b5a05..db8aef1330fb8a33934c17c789563a606fcd5350 100644
--- a/examples/seq2seq/predict.py
+++ b/examples/seq2seq/predict.py
@@ -23,7 +23,7 @@ import paddle.fluid as fluid
 from paddle.fluid.layers.utils import flatten
 from paddle.fluid.io import DataLoader
 
-from hapi.model import Input, set_device
+from paddle.incubate.hapi.model import Input, set_device
 from args import parse_args
 from seq2seq_base import BaseInferModel
 from seq2seq_attn import AttentionInferModel
diff --git a/examples/seq2seq/seq2seq_attn.py b/examples/seq2seq/seq2seq_attn.py
index ce9cc089ca2133549fbdd08ed600e69d4235e08c..37c84cbcd76381b13ff066fd97f600d7b347ab07 100644
--- a/examples/seq2seq/seq2seq_attn.py
+++ b/examples/seq2seq/seq2seq_attn.py
@@ -19,8 +19,8 @@ from paddle.fluid.initializer import UniformInitializer
 from paddle.fluid.dygraph import Embedding, Linear, Layer
 from paddle.fluid.layers import BeamSearchDecoder
 
-from hapi.model import Model, Loss
-from hapi.text import DynamicDecode, RNN, BasicLSTMCell, RNNCell
+from paddle.incubate.hapi.model import Model, Loss
+from paddle.incubate.hapi.text import DynamicDecode, RNN, BasicLSTMCell, RNNCell
 
 from seq2seq_base import Encoder
 
diff --git a/examples/seq2seq/seq2seq_base.py b/examples/seq2seq/seq2seq_base.py
index c28e2dc52935526d69d78ae73bfd48c92528b93c..6342ca112df6b92baed052fd17eaba215400440f 100644
--- a/examples/seq2seq/seq2seq_base.py
+++ b/examples/seq2seq/seq2seq_base.py
@@ -19,8 +19,8 @@ from paddle.fluid.initializer import UniformInitializer
 from paddle.fluid.dygraph import Embedding, Linear, Layer
 from paddle.fluid.layers import BeamSearchDecoder
 
-from hapi.model import Model, Loss
-from hapi.text import DynamicDecode, RNN, BasicLSTMCell, RNNCell
+from paddle.incubate.hapi.model import Model, Loss
+from paddle.incubate.hapi.text import DynamicDecode, RNN, BasicLSTMCell, RNNCell
 
 
 class CrossEntropyCriterion(Loss):
diff --git a/examples/seq2seq/train.py b/examples/seq2seq/train.py
index 55a31d39ad74686728593824151ac4bdf7b1b1ba..cd4fab9c932714e1da630c2d32a6b1243f03e7a0 100644
--- a/examples/seq2seq/train.py
+++ b/examples/seq2seq/train.py
@@ -21,7 +21,7 @@ import numpy as np
 import paddle.fluid as fluid
 from paddle.fluid.io import DataLoader
 
-from hapi.model import Input, set_device
+from paddle.incubate.hapi.model import Input, set_device
 from args import parse_args
 from seq2seq_base import BaseModel, CrossEntropyCriterion
 from seq2seq_attn import AttentionModel
diff --git a/examples/seq2seq/utility.py b/examples/seq2seq/utility.py
index aa0dd4a461d24d8a7799ff47c9d63a65bf87d401..95a38ff05d577a48947e6a71b14f6e6bf7c6894a 100644
--- a/examples/seq2seq/utility.py
+++ b/examples/seq2seq/utility.py
@@ -16,8 +16,8 @@ import math
 
 import paddle.fluid as fluid
 
-from hapi.metrics import Metric
-from hapi.callbacks import ProgBarLogger
+from paddle.incubate.hapi.metrics import Metric
+from paddle.incubate.hapi.callbacks import ProgBarLogger
 
 
 class TrainCallback(ProgBarLogger):
diff --git a/examples/sequence_tagging/eval.py b/examples/sequence_tagging/eval.py
index f58337be83b49978494bb1e9a9634ecb9256b909..2520d95a42c64468d8206015a4c5991174c679ee 100644
--- a/examples/sequence_tagging/eval.py
+++ b/examples/sequence_tagging/eval.py
@@ -28,11 +28,11 @@ import numpy as np
 work_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.append(os.path.join(work_dir, "../"))
 
-from hapi.model import set_device, Input
-from hapi.text.sequence_tagging import SeqTagging, ChunkEval, LacLoss
-from hapi.text.sequence_tagging import LacDataset, LacDataLoader
-from hapi.text.sequence_tagging import check_gpu, check_version
-from hapi.text.sequence_tagging import PDConfig
+from paddle.incubate.hapi.model import set_device, Input
+from paddle.incubate.hapi.text.sequence_tagging import SeqTagging, ChunkEval, LacLoss
+from paddle.incubate.hapi.text.sequence_tagging import LacDataset, LacDataLoader
+from paddle.incubate.hapi.text.sequence_tagging import check_gpu, check_version
+from paddle.incubate.hapi.text.sequence_tagging import PDConfig
 
 import paddle.fluid as fluid
 from paddle.fluid.layers.utils import flatten
@@ -65,7 +65,8 @@ def main(args):
         device=place)
     model.load(args.init_from_checkpoint, skip_mismatch=True)
 
-    eval_result = model.evaluate(eval_dataset.dataloader, batch_size=args.batch_size)
+    eval_result = model.evaluate(
+        eval_dataset.dataloader, batch_size=args.batch_size)
     print("precison: %.5f" % (eval_result["precision"][0]))
     print("recall: %.5f" % (eval_result["recall"][0]))
     print("F1: %.5f" % (eval_result["F1"][0]))
diff --git a/examples/sequence_tagging/predict.py b/examples/sequence_tagging/predict.py
index e8802e4a91ee4fbd339be29a83914cf24b9839c1..5b1620d45df6cd490da0fe6ab15d81229c3ed304 100644
--- a/examples/sequence_tagging/predict.py
+++ b/examples/sequence_tagging/predict.py
@@ -29,11 +29,11 @@ import numpy as np
 work_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.append(os.path.join(work_dir, "../"))
 
-from hapi.text.sequence_tagging import SeqTagging
-from hapi.model import Input, set_device
-from hapi.text.sequence_tagging import LacDataset, LacDataLoader
-from hapi.text.sequence_tagging import check_gpu, check_version
-from hapi.text.sequence_tagging import PDConfig
+from paddle.incubate.hapi.text.sequence_tagging import SeqTagging
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.text.sequence_tagging import LacDataset, LacDataLoader
+from paddle.incubate.hapi.text.sequence_tagging import check_gpu, check_version
+from paddle.incubate.hapi.text.sequence_tagging import PDConfig
 
 import paddle.fluid as fluid
 from paddle.fluid.layers.utils import flatten
diff --git a/examples/sequence_tagging/train.py b/examples/sequence_tagging/train.py
index 56507ad05b96baab8d7d262da3b7655e82df6f23..69b76b1510c58e66dc423aad457167af5fa0fa93 100644
--- a/examples/sequence_tagging/train.py
+++ b/examples/sequence_tagging/train.py
@@ -28,11 +28,11 @@ import numpy as np
 work_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.append(os.path.join(work_dir, "../"))
 
-from hapi.model import Input, set_device
-from hapi.text.sequence_tagging import SeqTagging, LacLoss, ChunkEval
-from hapi.text.sequence_tagging import LacDataset, LacDataLoader
-from hapi.text.sequence_tagging import check_gpu, check_version
-from hapi.text.sequence_tagging import PDConfig
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.text.sequence_tagging import SeqTagging, LacLoss, ChunkEval
+from paddle.incubate.hapi.text.sequence_tagging import LacDataset, LacDataLoader
+from paddle.incubate.hapi.text.sequence_tagging import check_gpu, check_version
+from paddle.incubate.hapi.text.sequence_tagging import PDConfig
 
 import paddle.fluid as fluid
 from paddle.fluid.optimizer import AdamOptimizer
diff --git a/examples/style-transfer/README.md b/examples/style-transfer/README.md
index 84b57bd6a6faabb72c89382fd083f51a7a7ab767..46b2b300a2ce6ad066019602e16ffe451cc2ddbf 100644
--- a/examples/style-transfer/README.md
+++ b/examples/style-transfer/README.md
@@ -32,10 +32,10 @@ gram_matrix = fluid.layers.matmul(tensor, fluid.layers.transpose(tensor, [1, 0])
 import numpy as np
 import matplotlib.pyplot as plt
 
-from hapi.model import Model, Loss
+from paddle.incubate.hapi.model import Model, Loss
 
-from hapi.vision.models import vgg16
-from hapi.vision.transforms import transforms
+from paddle.incubate.hapi.vision.models import vgg16
+from paddle.incubate.hapi.vision.transforms import transforms
 from paddle import fluid
 from paddle.fluid.io import Dataset
 
diff --git a/examples/style-transfer/style_transfer.py b/examples/style-transfer/style_transfer.py
index ad0716f7a164a6961df224e2528a13b96194cf6f..854ca9c77b009d8254822556eb56f2967c8efbf7 100644
--- a/examples/style-transfer/style_transfer.py
+++ b/examples/style-transfer/style_transfer.py
@@ -3,10 +3,10 @@ import argparse
 import numpy as np
 import matplotlib.pyplot as plt
 
-from hapi.model import Model, Loss
+from paddle.incubate.hapi.model import Model, Loss
 
-from hapi.vision.models import vgg16
-from hapi.vision.transforms import transforms
+from paddle.incubate.hapi.vision.models import vgg16
+from paddle.incubate.hapi.vision.transforms import transforms
 from paddle import fluid
 from paddle.fluid.io import Dataset
 
diff --git a/examples/transformer/predict.py b/examples/transformer/predict.py
index f99bf774cb2c9d6ceaa5b4cf69b941f9b2558358..5521d6c78478cf72a7a78d91d508a061b4f39cc3 100644
--- a/examples/transformer/predict.py
+++ b/examples/transformer/predict.py
@@ -25,7 +25,7 @@ from paddle.fluid.layers.utils import flatten
 from utils.configure import PDConfig
 from utils.check import check_gpu, check_version
 
-from hapi.model import Input, set_device
+from paddle.incubate.hapi.model import Input, set_device
 from reader import prepare_infer_input, Seq2SeqDataset, Seq2SeqBatchSampler
 from transformer import InferTransformer
 
diff --git a/examples/transformer/train.py b/examples/transformer/train.py
index 39bee1dea46ce459c5f9388ce1d0e08fce914ac4..90f54d01a85e811bee7c5cc6411277466639f4be 100644
--- a/examples/transformer/train.py
+++ b/examples/transformer/train.py
@@ -23,8 +23,8 @@ from paddle.io import DataLoader
 from utils.configure import PDConfig
 from utils.check import check_gpu, check_version
 
-from hapi.model import Input, set_device
-from hapi.callbacks import ProgBarLogger
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.callbacks import ProgBarLogger
 from reader import create_data_loader
 from transformer import Transformer, CrossEntropyCriterion
 
diff --git a/examples/transformer/transformer.py b/examples/transformer/transformer.py
index 30bb931d28c3b52467f484f4cb14b5d5601c76d9..02405d0aa3bf048b3c9442f27a4d5fceac5a7639 100644
--- a/examples/transformer/transformer.py
+++ b/examples/transformer/transformer.py
@@ -20,8 +20,8 @@ import paddle.fluid as fluid
 import paddle.fluid.layers as layers
 from paddle.fluid.dygraph import Embedding, LayerNorm, Linear, Layer, to_variable
 from paddle.fluid.dygraph.learning_rate_scheduler import LearningRateDecay
-from hapi.model import Model, CrossEntropy, Loss
-from hapi.text import TransformerBeamSearchDecoder, DynamicDecode
+from paddle.incubate.hapi.model import Model, CrossEntropy, Loss
+from paddle.incubate.hapi.text import TransformerBeamSearchDecoder, DynamicDecode
 
 
 def position_encoding_init(n_position, d_pos_vec):
diff --git a/examples/tsm/infer.py b/examples/tsm/infer.py
index cac9745fc8ddc1ad33dc3e95dd82e8f2dbe24277..2351eb2890d9588f40a2c5f9b7e9be7f5f958c6e 100644
--- a/examples/tsm/infer.py
+++ b/examples/tsm/infer.py
@@ -19,8 +19,8 @@ import os
 import argparse
 import numpy as np
 
-from hapi.model import Input, set_device
-from hapi.vision.transforms import Compose
+from paddle.incubate.hapi.model import Input, set_device
+from paddle.incubate.hapi.vision.transforms import Compose
 
 from check import check_gpu, check_version
 from modeling import tsm_resnet50
@@ -36,18 +36,16 @@ def main():
     device = set_device(FLAGS.device)
     fluid.enable_dygraph(device) if FLAGS.dynamic else None
 
-    transform = Compose([GroupScale(),
-                         GroupCenterCrop(),
-                         NormalizeImage()])
+    transform = Compose([GroupScale(), GroupCenterCrop(), NormalizeImage()])
     dataset = KineticsDataset(
-            pickle_file=FLAGS.infer_file,
-            label_list=FLAGS.label_list,
-            mode='test',
-            transform=transform)
+        pickle_file=FLAGS.infer_file,
+        label_list=FLAGS.label_list,
+        mode='test',
+        transform=transform)
     labels = dataset.label_list
 
-    model = tsm_resnet50(num_classes=len(labels),
-                         pretrained=FLAGS.weights is None)
+    model = tsm_resnet50(
+        num_classes=len(labels), pretrained=FLAGS.weights is None)
 
     inputs = [Input([None, 8, 3, 224, 224], 'float32', name='image')]
 
@@ -66,19 +64,23 @@ def main():
 if __name__ == '__main__':
     parser = argparse.ArgumentParser("CNN training on TSM")
     parser.add_argument(
-        "--data", type=str, default='dataset/kinetics',
+        "--data",
+        type=str,
+        default='dataset/kinetics',
         help="path to dataset root directory")
     parser.add_argument(
-        "--device", type=str, default='gpu',
-        help="device to use, gpu or cpu")
+        "--device", type=str, default='gpu', help="device to use, gpu or cpu")
     parser.add_argument(
-        "-d", "--dynamic", action='store_true',
-        help="enable dygraph mode")
+        "-d", "--dynamic", action='store_true', help="enable dygraph mode")
     parser.add_argument(
-        "--label_list", type=str, default=None,
+        "--label_list",
+        type=str,
+        default=None,
         help="path to category index label list file")
     parser.add_argument(
-        "--infer_file", type=str, default=None,
+        "--infer_file",
+        type=str,
+        default=None,
         help="path to pickle file for inference")
     parser.add_argument(
         "-w",
diff --git a/examples/tsm/main.py b/examples/tsm/main.py
index deef9f6b8349033f2d7ce83b40f583ca24a56a7e..d292d7d99d2f5114f81116d302cd3af0478617f3 100644
--- a/examples/tsm/main.py
+++ b/examples/tsm/main.py
@@ -22,10 +22,10 @@ import numpy as np
 from paddle import fluid
 from paddle.fluid.dygraph.parallel import ParallelEnv
 
-from hapi.model import Model, Input, set_device
-from hapi.loss import CrossEntropy
-from hapi.metrics import Accuracy
-from hapi.vision.transforms import Compose
+from paddle.incubate.hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.loss import CrossEntropy
+from paddle.incubate.hapi.metrics import Accuracy
+from paddle.incubate.hapi.vision.transforms import Compose
 
 from modeling import tsm_resnet50
 from check import check_gpu, check_version
diff --git a/examples/tsm/modeling.py b/examples/tsm/modeling.py
index aafd6a4557e01222bf672f6bde47dcdbeee06ce3..a42f4265e09d8f53d207013d801dab11a94ef992 100644
--- a/examples/tsm/modeling.py
+++ b/examples/tsm/modeling.py
@@ -17,8 +17,8 @@ import paddle.fluid as fluid
 from paddle.fluid.layer_helper import LayerHelper
 from paddle.fluid.dygraph.nn import Conv2D, Pool2D, BatchNorm, Linear
 
-from hapi.model import Model
-from hapi.download import get_weights_path_from_url
+from paddle.incubate.hapi.model import Model
+from paddle.incubate.hapi.download import get_weights_path_from_url
 
 __all__ = ["TSM_ResNet", "tsm_resnet50"]
 
diff --git a/examples/yolov3/infer.py b/examples/yolov3/infer.py
index 7b6976c89dcd5d6efb39d7143656761dffb03350..a2640fec1f1bb1d9844a10df79910b8e62408091 100644
--- a/examples/yolov3/infer.py
+++ b/examples/yolov3/infer.py
@@ -18,13 +18,13 @@ from __future__ import print_function
 import os
 import argparse
 import numpy as np
-from PIL import Image 
+from PIL import Image
 
 from paddle import fluid
 from paddle.fluid.optimizer import Momentum
 from paddle.io import DataLoader
 
-from hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.model import Model, Input, set_device
 
 from modeling import yolov3_darknet53, YoloLoss
 from transforms import *
@@ -64,16 +64,20 @@ def load_labels(label_list, with_background=True):
 def main():
     device = set_device(FLAGS.device)
     fluid.enable_dygraph(device) if FLAGS.dynamic else None
-    
-    inputs = [Input([None, 1], 'int64', name='img_id'),
-              Input([None, 2], 'int32', name='img_shape'),
-              Input([None, 3, None, None], 'float32', name='image')]
+
+    inputs = [
+        Input(
+            [None, 1], 'int64', name='img_id'), Input(
+                [None, 2], 'int32', name='img_shape'), Input(
+                    [None, 3, None, None], 'float32', name='image')
+    ]
 
     cat2name = load_labels(FLAGS.label_list, with_background=False)
 
-    model = yolov3_darknet53(num_classes=len(cat2name),
-                             model_mode='test',
-                             pretrained=FLAGS.weights is None)
+    model = yolov3_darknet53(
+        num_classes=len(cat2name),
+        model_mode='test',
+        pretrained=FLAGS.weights is None)
 
     model.prepare(inputs=inputs, device=FLAGS.device)
 
@@ -82,7 +86,7 @@ def main():
 
     # image preprocess
     orig_img = Image.open(FLAGS.infer_image).convert('RGB')
-    w, h  = orig_img.size
+    w, h = orig_img.size
     img = orig_img.resize((608, 608), Image.BICUBIC)
     img = np.array(img).astype('float32') / 255.0
     img -= np.array(IMAGE_MEAN)
@@ -106,19 +110,33 @@ if __name__ == '__main__':
     parser.add_argument(
         "-d", "--dynamic", action='store_true', help="enable dygraph mode")
     parser.add_argument(
-        "--label_list", type=str, default=None,
+        "--label_list",
+        type=str,
+        default=None,
         help="path to category label list file")
     parser.add_argument(
-        "-t", "--draw_threshold", type=float, default=0.5,
+        "-t",
+        "--draw_threshold",
+        type=float,
+        default=0.5,
         help="threshold to reserve the result for visualization")
     parser.add_argument(
-        "-i", "--infer_image", type=str, default=None,
+        "-i",
+        "--infer_image",
+        type=str,
+        default=None,
         help="image path for inference")
     parser.add_argument(
-        "-o", "--output_dir", type=str, default='output',
+        "-o",
+        "--output_dir",
+        type=str,
+        default='output',
         help="directory to save inference result if --visualize is set")
     parser.add_argument(
-        "-w", "--weights", default=None, type=str,
+        "-w",
+        "--weights",
+        default=None,
+        type=str,
         help="path to weights for inference")
     FLAGS = parser.parse_args()
     print_arguments(FLAGS)
diff --git a/examples/yolov3/main.py b/examples/yolov3/main.py
index e3c773fbc40e8afd19c568d993d903f6a52240dd..f90ae4fe11a18fa040b7c0492eda930a242253aa 100644
--- a/examples/yolov3/main.py
+++ b/examples/yolov3/main.py
@@ -25,9 +25,9 @@ from paddle import fluid
 from paddle.fluid.optimizer import Momentum
 from paddle.io import DataLoader
 
-from hapi.model import Model, Input, set_device
-from hapi.distributed import DistributedBatchSampler
-from hapi.vision.transforms import Compose, BatchCompose
+from paddle.incubate.hapi.model import Model, Input, set_device
+from paddle.incubate.hapi.distributed import DistributedBatchSampler
+from paddle.incubate.hapi.vision.transforms import Compose, BatchCompose
 
 from modeling import yolov3_darknet53, YoloLoss
 from coco import COCODataset
diff --git a/examples/yolov3/modeling.py b/examples/yolov3/modeling.py
index 982c0beae8f215a0bc00441895e8c9bd883b83cb..3beb977849787d007418599a95e6ae5539212bae 100644
--- a/examples/yolov3/modeling.py
+++ b/examples/yolov3/modeling.py
@@ -23,7 +23,7 @@ from paddle.fluid.regularizer import L2Decay
 from hapi.model import Model
 from hapi.loss import Loss
 from hapi.download import get_weights_path_from_url
-from hapi.vision.models import darknet53
+from darknet import darknet53
 
 __all__ = ['YoloLoss', 'YOLOv3', 'yolov3_darknet53']