Make paddle.fluid no longer depends on paddle.v2

In this way we can build and test using WITH_FLUID_ONLY flag being set
to ON.

- move paddle.v2.dataset,reader to paddle.dataset,reader
- remove unused code (which depends on v2) in paddle.dataset,reader

python/CMakeLists.txt

@@ -73,12 +73,13 @@ add_custom_target(paddle_python ALL DEPENDS ${paddle_python_deps})
 set(PADDLE_PYTHON_PACKAGE_DIR ${CMAKE_CURRENT_BINARY_DIR}/dist/)
 
 if (WITH_TESTING)
+  add_subdirectory(paddle/reader/tests)
+  add_subdirectory(paddle/dataset/tests)
   if(NOT WITH_FLUID_ONLY)
     add_subdirectory(paddle/trainer_config_helpers/tests)
     if (WITH_SWIG_PY)
       # enable v2 API unittest only when paddle swig api is compiled
       add_subdirectory(paddle/v2/tests)
-      add_subdirectory(paddle/v2/reader/tests)
       add_subdirectory(paddle/v2/plot/tests)
     endif()
   endif()

python/paddle/__init__.py

@@ -14,8 +14,14 @@
 try:
     from version import full_version as __version__
     from version import commit as __git_commit__
+
 except ImportError:
     import sys
     sys.stderr.write('''Warning with import paddle: you should not 
      import paddle from the source directory; please install paddlepaddle*.whl firstly.'''
                      )
+
+import reader
+import dataset
+import batch
+batch = batch.batch

python/paddle/v2/dataset/__init__.py → python/paddle/dataset/__init__.py

@@ -28,6 +28,7 @@ import wmt16
 import mq2007
 import flowers
 import voc2012
+import image
 
 __all__ = [
     'mnist',
@@ -43,4 +44,5 @@ __all__ = [
     'mq2007',
     'flowers',
     'voc2012',
+    'image',
 ]

python/paddle/v2/dataset/cifar.py → python/paddle/dataset/cifar.py

@@ -31,7 +31,7 @@ images per class.
 import cPickle
 import itertools
 import numpy
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import tarfile
 
 __all__ = ['train100', 'test100', 'train10', 'test10', 'convert']
@@ -75,7 +75,7 @@ def train100():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5),
+        paddle.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5),
         'train')
 
 
@@ -90,7 +90,7 @@ def test100():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5),
+        paddle.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5),
         'test')
 
 
@@ -105,7 +105,7 @@ def train10():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5),
+        paddle.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5),
         'data_batch')
 
 
@@ -120,20 +120,20 @@ def test10():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5),
+        paddle.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5),
         'test_batch')
 
 
 def fetch():
-    paddle.v2.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5)
-    paddle.v2.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5)
+    paddle.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5)
+    paddle.dataset.common.download(CIFAR100_URL, 'cifar', CIFAR100_MD5)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, train100(), 1000, "cifar_train100")
-    paddle.v2.dataset.common.convert(path, test100(), 1000, "cifar_test100")
-    paddle.v2.dataset.common.convert(path, train10(), 1000, "cifar_train10")
-    paddle.v2.dataset.common.convert(path, test10(), 1000, "cifar_test10")
+    paddle.dataset.common.convert(path, train100(), 1000, "cifar_train100")
+    paddle.dataset.common.convert(path, test100(), 1000, "cifar_test100")
+    paddle.dataset.common.convert(path, train10(), 1000, "cifar_train10")
+    paddle.dataset.common.convert(path, test10(), 1000, "cifar_test10")

python/paddle/v2/dataset/common.py → python/paddle/dataset/common.py

@@ -19,7 +19,7 @@ import errno
 import shutil
 import sys
 import importlib
-import paddle.v2.dataset
+import paddle.dataset
 import cPickle
 import glob
 import cPickle as pickle
@@ -105,24 +105,24 @@ def download(url, module_name, md5sum, save_name=None):
 
 def fetch_all():
     for module_name in filter(lambda x: not x.startswith("__"),
-                              dir(paddle.v2.dataset)):
+                              dir(paddle.dataset)):
         if "fetch" in dir(
-                importlib.import_module("paddle.v2.dataset.%s" % module_name)):
+                importlib.import_module("paddle.dataset.%s" % module_name)):
             getattr(
-                importlib.import_module("paddle.v2.dataset.%s" % module_name),
+                importlib.import_module("paddle.dataset.%s" % module_name),
                 "fetch")()
 
 
 def fetch_all_recordio(path):
     for module_name in filter(lambda x: not x.startswith("__"),
-                              dir(paddle.v2.dataset)):
+                              dir(paddle.dataset)):
         if "convert" in dir(
-                importlib.import_module("paddle.v2.dataset.%s" % module_name)) and \
+                importlib.import_module("paddle.dataset.%s" % module_name)) and \
                 not module_name == "common":
             ds_path = os.path.join(path, module_name)
             must_mkdirs(ds_path)
             getattr(
-                importlib.import_module("paddle.v2.dataset.%s" % module_name),
+                importlib.import_module("paddle.dataset.%s" % module_name),
                 "convert")(ds_path)
 
 
@@ -130,7 +130,7 @@ def split(reader, line_count, suffix="%05d.pickle", dumper=cPickle.dump):
     """
     you can call the function as:
 
-    split(paddle.v2.dataset.cifar.train10(), line_count=1000,
+    split(paddle.dataset.cifar.train10(), line_count=1000,
         suffix="imikolov-train-%05d.pickle")
 
     the output files as:

python/paddle/v2/dataset/conll05.py → python/paddle/dataset/conll05.py

@@ -23,7 +23,7 @@ to initialize SRL model.
 import tarfile
 import gzip
 import itertools
-import paddle.v2.dataset.common
+import paddle.dataset.common
 
 __all__ = ['test, get_dict', 'get_embedding', 'convert']
 
@@ -203,14 +203,11 @@ def get_dict():
     Get the word, verb and label dictionary of Wikipedia corpus.
     """
     word_dict = load_dict(
-        paddle.v2.dataset.common.download(WORDDICT_URL, 'conll05st',
-                                          WORDDICT_MD5))
+        paddle.dataset.common.download(WORDDICT_URL, 'conll05st', WORDDICT_MD5))
     verb_dict = load_dict(
-        paddle.v2.dataset.common.download(VERBDICT_URL, 'conll05st',
-                                          VERBDICT_MD5))
+        paddle.dataset.common.download(VERBDICT_URL, 'conll05st', VERBDICT_MD5))
     label_dict = load_label_dict(
-        paddle.v2.dataset.common.download(TRGDICT_URL, 'conll05st',
-                                          TRGDICT_MD5))
+        paddle.dataset.common.download(TRGDICT_URL, 'conll05st', TRGDICT_MD5))
     return word_dict, verb_dict, label_dict
 
 
@@ -218,7 +215,7 @@ def get_embedding():
     """
     Get the trained word vector based on Wikipedia corpus.
     """
-    return paddle.v2.dataset.common.download(EMB_URL, 'conll05st', EMB_MD5)
+    return paddle.dataset.common.download(EMB_URL, 'conll05st', EMB_MD5)
 
 
 def test():
@@ -235,23 +232,23 @@ def test():
     """
     word_dict, verb_dict, label_dict = get_dict()
     reader = corpus_reader(
-        paddle.v2.dataset.common.download(DATA_URL, 'conll05st', DATA_MD5),
+        paddle.dataset.common.download(DATA_URL, 'conll05st', DATA_MD5),
         words_name='conll05st-release/test.wsj/words/test.wsj.words.gz',
         props_name='conll05st-release/test.wsj/props/test.wsj.props.gz')
     return reader_creator(reader, word_dict, verb_dict, label_dict)
 
 
 def fetch():
-    paddle.v2.dataset.common.download(WORDDICT_URL, 'conll05st', WORDDICT_MD5)
-    paddle.v2.dataset.common.download(VERBDICT_URL, 'conll05st', VERBDICT_MD5)
-    paddle.v2.dataset.common.download(TRGDICT_URL, 'conll05st', TRGDICT_MD5)
-    paddle.v2.dataset.common.download(EMB_URL, 'conll05st', EMB_MD5)
-    paddle.v2.dataset.common.download(DATA_URL, 'conll05st', DATA_MD5)
+    paddle.dataset.common.download(WORDDICT_URL, 'conll05st', WORDDICT_MD5)
+    paddle.dataset.common.download(VERBDICT_URL, 'conll05st', VERBDICT_MD5)
+    paddle.dataset.common.download(TRGDICT_URL, 'conll05st', TRGDICT_MD5)
+    paddle.dataset.common.download(EMB_URL, 'conll05st', EMB_MD5)
+    paddle.dataset.common.download(DATA_URL, 'conll05st', DATA_MD5)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, test(), 1000, "conl105_train")
-    paddle.v2.dataset.common.convert(path, test(), 1000, "conl105_test")
+    paddle.dataset.common.convert(path, test(), 1000, "conl105_train")
+    paddle.dataset.common.convert(path, test(), 1000, "conl105_test")

python/paddle/v2/dataset/flowers.py → python/paddle/dataset/flowers.py

@@ -34,8 +34,8 @@ import functools
 from common import download
 import tarfile
 import scipy.io as scio
-from paddle.v2.image import *
-from paddle.v2.reader import *
+from paddle.dataset.image import *
+from paddle.reader import *
 import os
 import numpy as np
 from multiprocessing import cpu_count

python/paddle/v2/dataset/imdb.py → python/paddle/dataset/imdb.py

@@ -20,7 +20,7 @@ of 25,000 highly polar movie reviews for training, and 25,000 for testing.
 Besides, this module also provides API for building dictionary.
 """
 
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import collections
 import tarfile
 import re
@@ -37,8 +37,7 @@ def tokenize(pattern):
     Read files that match the given pattern.  Tokenize and yield each file.
     """
 
-    with tarfile.open(paddle.v2.dataset.common.download(URL, 'imdb',
-                                                        MD5)) as tarf:
+    with tarfile.open(paddle.dataset.common.download(URL, 'imdb', MD5)) as tarf:
         # Note that we should use tarfile.next(), which does
         # sequential access of member files, other than
         # tarfile.extractfile, which does random access and might
@@ -136,7 +135,7 @@ def word_dict():
 
 
 def fetch():
-    paddle.v2.dataset.common.download(URL, 'imdb', MD5)
+    paddle.dataset.common.download(URL, 'imdb', MD5)
 
 
 def convert(path):
@@ -144,5 +143,5 @@ def convert(path):
     Converts dataset to recordio format
     """
     w = word_dict()
-    paddle.v2.dataset.common.convert(path, lambda: train(w), 1000, "imdb_train")
-    paddle.v2.dataset.common.convert(path, lambda: test(w), 1000, "imdb_test")
+    paddle.dataset.common.convert(path, lambda: train(w), 1000, "imdb_train")
+    paddle.dataset.common.convert(path, lambda: test(w), 1000, "imdb_test")

python/paddle/v2/dataset/imikolov.py → python/paddle/dataset/imikolov.py

@@ -18,7 +18,7 @@ This module will download dataset from
 http://www.fit.vutbr.cz/~imikolov/rnnlm/ and parse training set and test set
 into paddle reader creators.
 """
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import collections
 import tarfile
 
@@ -54,9 +54,9 @@ def build_dict(min_word_freq=50):
     train_filename = './simple-examples/data/ptb.train.txt'
     test_filename = './simple-examples/data/ptb.valid.txt'
     with tarfile.open(
-            paddle.v2.dataset.common.download(
-                paddle.v2.dataset.imikolov.URL, 'imikolov',
-                paddle.v2.dataset.imikolov.MD5)) as tf:
+            paddle.dataset.common.download(paddle.dataset.imikolov.URL,
+                                           'imikolov',
+                                           paddle.dataset.imikolov.MD5)) as tf:
         trainf = tf.extractfile(train_filename)
         testf = tf.extractfile(test_filename)
         word_freq = word_count(testf, word_count(trainf))
@@ -77,9 +77,9 @@ def build_dict(min_word_freq=50):
 def reader_creator(filename, word_idx, n, data_type):
     def reader():
         with tarfile.open(
-                paddle.v2.dataset.common.download(
-                    paddle.v2.dataset.imikolov.URL, 'imikolov',
-                    paddle.v2.dataset.imikolov.MD5)) as tf:
+                paddle.dataset.common.download(
+                    paddle.dataset.imikolov.URL, 'imikolov',
+                    paddle.dataset.imikolov.MD5)) as tf:
             f = tf.extractfile(filename)
 
             UNK = word_idx['<unk>']
@@ -145,7 +145,7 @@ def test(word_idx, n, data_type=DataType.NGRAM):
 
 
 def fetch():
-    paddle.v2.dataset.common.download(URL, "imikolov", MD5)
+    paddle.dataset.common.download(URL, "imikolov", MD5)
 
 
 def convert(path):
@@ -154,8 +154,7 @@ def convert(path):
     """
     N = 5
     word_dict = build_dict()
-    paddle.v2.dataset.common.convert(path,
-                                     train(word_dict, N), 1000,
-                                     "imikolov_train")
-    paddle.v2.dataset.common.convert(path,
-                                     test(word_dict, N), 1000, "imikolov_test")
+    paddle.dataset.common.convert(path,
+                                  train(word_dict, N), 1000, "imikolov_train")
+    paddle.dataset.common.convert(path,
+                                  test(word_dict, N), 1000, "imikolov_test")

python/paddle/v2/dataset/mnist.py → python/paddle/dataset/mnist.py

@@ -17,7 +17,7 @@ MNIST dataset.
 This module will download dataset from http://yann.lecun.com/exdb/mnist/ and
 parse training set and test set into paddle reader creators.
 """
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import subprocess
 import numpy
 import platform
@@ -85,10 +85,10 @@ def train():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(TRAIN_IMAGE_URL, 'mnist',
-                                          TRAIN_IMAGE_MD5),
-        paddle.v2.dataset.common.download(TRAIN_LABEL_URL, 'mnist',
-                                          TRAIN_LABEL_MD5), 100)
+        paddle.dataset.common.download(TRAIN_IMAGE_URL, 'mnist',
+                                       TRAIN_IMAGE_MD5),
+        paddle.dataset.common.download(TRAIN_LABEL_URL, 'mnist',
+                                       TRAIN_LABEL_MD5), 100)
 
 
 def test():
@@ -102,22 +102,21 @@ def test():
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(TEST_IMAGE_URL, 'mnist',
-                                          TEST_IMAGE_MD5),
-        paddle.v2.dataset.common.download(TEST_LABEL_URL, 'mnist',
-                                          TEST_LABEL_MD5), 100)
+        paddle.dataset.common.download(TEST_IMAGE_URL, 'mnist', TEST_IMAGE_MD5),
+        paddle.dataset.common.download(TEST_LABEL_URL, 'mnist', TEST_LABEL_MD5),
+        100)
 
 
 def fetch():
-    paddle.v2.dataset.common.download(TRAIN_IMAGE_URL, 'mnist', TRAIN_IMAGE_MD5)
-    paddle.v2.dataset.common.download(TRAIN_LABEL_URL, 'mnist', TRAIN_LABEL_MD5)
-    paddle.v2.dataset.common.download(TEST_IMAGE_URL, 'mnist', TEST_IMAGE_MD5)
-    paddle.v2.dataset.common.download(TEST_LABEL_URL, 'mnist', TRAIN_LABEL_MD5)
+    paddle.dataset.common.download(TRAIN_IMAGE_URL, 'mnist', TRAIN_IMAGE_MD5)
+    paddle.dataset.common.download(TRAIN_LABEL_URL, 'mnist', TRAIN_LABEL_MD5)
+    paddle.dataset.common.download(TEST_IMAGE_URL, 'mnist', TEST_IMAGE_MD5)
+    paddle.dataset.common.download(TEST_LABEL_URL, 'mnist', TRAIN_LABEL_MD5)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, train(), 1000, "minist_train")
-    paddle.v2.dataset.common.convert(path, test(), 1000, "minist_test")
+    paddle.dataset.common.convert(path, train(), 1000, "minist_train")
+    paddle.dataset.common.convert(path, test(), 1000, "minist_test")

python/paddle/v2/dataset/movielens.py → python/paddle/dataset/movielens.py

@@ -23,7 +23,7 @@ set and test set into paddle reader creators.
 """
 
 import zipfile
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import re
 import random
 import functools
@@ -100,7 +100,7 @@ USER_INFO = None
 
 
 def __initialize_meta_info__():
-    fn = paddle.v2.dataset.common.download(URL, "movielens", MD5)
+    fn = paddle.dataset.common.download(URL, "movielens", MD5)
     global MOVIE_INFO
     if MOVIE_INFO is None:
         pattern = re.compile(r'^(.*)\((\d+)\)$')
@@ -247,15 +247,15 @@ def unittest():
 
 
 def fetch():
-    paddle.v2.dataset.common.download(URL, "movielens", MD5)
+    paddle.dataset.common.download(URL, "movielens", MD5)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, train(), 1000, "movielens_train")
-    paddle.v2.dataset.common.convert(path, test(), 1000, "movielens_test")
+    paddle.dataset.common.convert(path, train(), 1000, "movielens_train")
+    paddle.dataset.common.convert(path, test(), 1000, "movielens_test")
 
 
 if __name__ == '__main__':

python/paddle/v2/dataset/sentiment.py → python/paddle/dataset/sentiment.py

@@ -26,7 +26,7 @@ from itertools import chain
 import nltk
 from nltk.corpus import movie_reviews
 
-import paddle.v2.dataset.common
+import paddle.dataset.common
 
 __all__ = ['train', 'test', 'get_word_dict', 'convert']
 NUM_TRAINING_INSTANCES = 1600
@@ -39,13 +39,13 @@ def download_data_if_not_yet():
     """
     try:
         # make sure that nltk can find the data
-        if paddle.v2.dataset.common.DATA_HOME not in nltk.data.path:
-            nltk.data.path.append(paddle.v2.dataset.common.DATA_HOME)
+        if paddle.dataset.common.DATA_HOME not in nltk.data.path:
+            nltk.data.path.append(paddle.dataset.common.DATA_HOME)
         movie_reviews.categories()
     except LookupError:
         print "Downloading movie_reviews data set, please wait....."
         nltk.download(
-            'movie_reviews', download_dir=paddle.v2.dataset.common.DATA_HOME)
+            'movie_reviews', download_dir=paddle.dataset.common.DATA_HOME)
         print "Download data set success....."
         print "Path is " + nltk.data.find('corpora/movie_reviews').path
 
@@ -129,13 +129,12 @@ def test():
 
 
 def fetch():
-    nltk.download(
-        'movie_reviews', download_dir=paddle.v2.dataset.common.DATA_HOME)
+    nltk.download('movie_reviews', download_dir=paddle.dataset.common.DATA_HOME)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, train, 1000, "sentiment_train")
-    paddle.v2.dataset.common.convert(path, test, 1000, "sentiment_test")
+    paddle.dataset.common.convert(path, train, 1000, "sentiment_train")
+    paddle.dataset.common.convert(path, test, 1000, "sentiment_test")

python/paddle/dataset/tests/CMakeLists.txt

+py_test(test_image SRCS test_image.py)

python/paddle/v2/dataset/tests/cifar_test.py → python/paddle/dataset/tests/cifar_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.cifar
+import paddle.dataset.cifar
 import unittest
 
 
@@ -29,25 +29,25 @@ class TestCIFAR(unittest.TestCase):
 
     def test_test10(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.cifar.test10())
+            paddle.dataset.cifar.test10())
         self.assertEqual(instances, 10000)
         self.assertEqual(max_label_value, 9)
 
     def test_train10(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.cifar.train10())
+            paddle.dataset.cifar.train10())
         self.assertEqual(instances, 50000)
         self.assertEqual(max_label_value, 9)
 
     def test_test100(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.cifar.test100())
+            paddle.dataset.cifar.test100())
         self.assertEqual(instances, 10000)
         self.assertEqual(max_label_value, 99)
 
     def test_train100(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.cifar.train100())
+            paddle.dataset.cifar.train100())
         self.assertEqual(instances, 50000)
         self.assertEqual(max_label_value, 99)
 

python/paddle/v2/dataset/tests/common_test.py → python/paddle/dataset/tests/common_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.common
+import paddle.dataset.common
 import unittest
 import tempfile
 import glob
@@ -24,14 +24,14 @@ class TestCommon(unittest.TestCase):
         with open(temp_path, 'w') as f:
             f.write("Hello\n")
         self.assertEqual('09f7e02f1290be211da707a266f153b3',
-                         paddle.v2.dataset.common.md5file(temp_path))
+                         paddle.dataset.common.md5file(temp_path))
 
     def test_download(self):
         yi_avatar = 'https://avatars0.githubusercontent.com/u/1548775?v=3&s=460'
         self.assertEqual(
-            paddle.v2.dataset.common.DATA_HOME + '/test/1548775?v=3&s=460',
-            paddle.v2.dataset.common.download(
-                yi_avatar, 'test', 'f75287202d6622414c706c36c16f8e0d'))
+            paddle.dataset.common.DATA_HOME + '/test/1548775?v=3&s=460',
+            paddle.dataset.common.download(yi_avatar, 'test',
+                                           'f75287202d6622414c706c36c16f8e0d'))
 
     def test_split(self):
         def test_reader():
@@ -42,7 +42,7 @@ class TestCommon(unittest.TestCase):
             return reader
 
         _, temp_path = tempfile.mkstemp()
-        paddle.v2.dataset.common.split(
+        paddle.dataset.common.split(
             test_reader(), 4, suffix=temp_path + '/test-%05d.pickle')
         files = glob.glob(temp_path + '/test-%05d.pickle')
         self.assertEqual(len(files), 3)
@@ -52,7 +52,7 @@ class TestCommon(unittest.TestCase):
         for x in xrange(5):
             with open(temp_path + '/%05d.test' % x) as f:
                 f.write('%d\n' % x)
-        reader = paddle.v2.dataset.common.cluster_files_reader(
+        reader = paddle.dataset.common.cluster_files_reader(
             temp_path + '/*.test', 5, 0)
         for idx, e in enumerate(reader()):
             self.assertEqual(e, str("0"))
@@ -69,9 +69,9 @@ class TestCommon(unittest.TestCase):
             return reader
 
         path = tempfile.mkdtemp()
-        paddle.v2.dataset.common.convert(path,
-                                         test_reader(), num_shards,
-                                         'random_images')
+        paddle.dataset.common.convert(path,
+                                      test_reader(), num_shards,
+                                      'random_images')
 
         files = glob.glob(path + '/random_images-*')
         self.assertEqual(len(files), num_shards)

python/paddle/v2/dataset/tests/flowers_test.py → python/paddle/dataset/tests/flowers_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.flowers
+import paddle.dataset.flowers
 import unittest
 
 
@@ -30,19 +30,19 @@ class TestFlowers(unittest.TestCase):
 
     def test_train(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.flowers.train())
+            paddle.dataset.flowers.train())
         self.assertEqual(instances, 6149)
         self.assertEqual(max_label_value, 102)
 
     def test_test(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.flowers.test())
+            paddle.dataset.flowers.test())
         self.assertEqual(instances, 1020)
         self.assertEqual(max_label_value, 102)
 
     def test_valid(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.flowers.valid())
+            paddle.dataset.flowers.valid())
         self.assertEqual(instances, 1020)
         self.assertEqual(max_label_value, 102)
 

python/paddle/v2/dataset/tests/imdb_test.py → python/paddle/dataset/tests/imdb_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.imdb
+import paddle.dataset.imdb
 import unittest
 import re
 
@@ -30,15 +30,13 @@ class TestIMDB(unittest.TestCase):
 
     def test_build_dict(self):
         if self.word_idx == None:
-            self.word_idx = paddle.v2.dataset.imdb.build_dict(TRAIN_PATTERN,
-                                                              150)
+            self.word_idx = paddle.dataset.imdb.build_dict(TRAIN_PATTERN, 150)
 
         self.assertEqual(len(self.word_idx), 7036)
 
     def check_dataset(self, dataset, expected_size):
         if self.word_idx == None:
-            self.word_idx = paddle.v2.dataset.imdb.build_dict(TRAIN_PATTERN,
-                                                              150)
+            self.word_idx = paddle.dataset.imdb.build_dict(TRAIN_PATTERN, 150)
 
         sum = 0
         for l in dataset(self.word_idx):
@@ -47,10 +45,10 @@ class TestIMDB(unittest.TestCase):
         self.assertEqual(sum, expected_size)
 
     def test_train(self):
-        self.check_dataset(paddle.v2.dataset.imdb.train, 25000)
+        self.check_dataset(paddle.dataset.imdb.train, 25000)
 
     def test_test(self):
-        self.check_dataset(paddle.v2.dataset.imdb.test, 25000)
+        self.check_dataset(paddle.dataset.imdb.test, 25000)
 
 
 if __name__ == '__main__':

python/paddle/v2/dataset/tests/imikolov_test.py → python/paddle/dataset/tests/imikolov_test.py

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.imikolov
+import paddle.dataset.imikolov
 import unittest
 
-WORD_DICT = paddle.v2.dataset.imikolov.build_dict()
+WORD_DICT = paddle.dataset.imikolov.build_dict()
 
 
 class TestMikolov(unittest.TestCase):
@@ -25,7 +25,7 @@ class TestMikolov(unittest.TestCase):
 
     def test_train(self):
         n = 5
-        self.check_reader(paddle.v2.dataset.imikolov.train(WORD_DICT, n), n)
+        self.check_reader(paddle.dataset.imikolov.train(WORD_DICT, n), n)
 
         first_line = 'aer banknote berlitz calloway centrust cluett fromstein '\
             'gitano guterman hydro-quebec ipo kia memotec mlx nahb punts '\
@@ -34,16 +34,16 @@ class TestMikolov(unittest.TestCase):
             WORD_DICT.get(ch, WORD_DICT['<unk>'])
             for ch in first_line.split(' ')
         ]
-        for l in paddle.v2.dataset.imikolov.train(
+        for l in paddle.dataset.imikolov.train(
                 WORD_DICT, n=-1,
-                data_type=paddle.v2.dataset.imikolov.DataType.SEQ)():
+                data_type=paddle.dataset.imikolov.DataType.SEQ)():
             read_line = l[0][1:]
             break
         self.assertEqual(first_line, read_line)
 
     def test_test(self):
         n = 5
-        self.check_reader(paddle.v2.dataset.imikolov.test(WORD_DICT, n), n)
+        self.check_reader(paddle.dataset.imikolov.test(WORD_DICT, n), n)
 
         first_line = 'consumers may want to move their telephones a little '\
                 'closer to the tv set'
@@ -51,9 +51,9 @@ class TestMikolov(unittest.TestCase):
             WORD_DICT.get(ch, WORD_DICT['<unk>'])
             for ch in first_line.split(' ')
         ]
-        for l in paddle.v2.dataset.imikolov.test(
+        for l in paddle.dataset.imikolov.test(
                 WORD_DICT, n=-1,
-                data_type=paddle.v2.dataset.imikolov.DataType.SEQ)():
+                data_type=paddle.dataset.imikolov.DataType.SEQ)():
             read_line = l[0][1:]
             break
         self.assertEqual(first_line, read_line)

python/paddle/v2/dataset/tests/mnist_test.py → python/paddle/dataset/tests/mnist_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.mnist
+import paddle.dataset.mnist
 import unittest
 
 
@@ -29,13 +29,13 @@ class TestMNIST(unittest.TestCase):
 
     def test_train(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.mnist.train())
+            paddle.dataset.mnist.train())
         self.assertEqual(instances, 60000)
         self.assertEqual(max_label_value, 9)
 
     def test_test(self):
         instances, max_label_value = self.check_reader(
-            paddle.v2.dataset.mnist.test())
+            paddle.dataset.mnist.test())
         self.assertEqual(instances, 10000)
         self.assertEqual(max_label_value, 9)
 

python/paddle/v2/dataset/tests/mq2007_test.py → python/paddle/dataset/tests/mq2007_test.py

@@ -12,19 +12,19 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.mq2007
+import paddle.dataset.mq2007
 import unittest
 
 
 class TestMQ2007(unittest.TestCase):
     def test_pairwise(self):
-        for label, query_left, query_right in paddle.v2.dataset.mq2007.test(
+        for label, query_left, query_right in paddle.dataset.mq2007.test(
                 format="pairwise"):
             self.assertEqual(query_left.shape(), (46, ))
             self.assertEqual(query_right.shape(), (46, ))
 
     def test_listwise(self):
-        for label_array, query_array in paddle.v2.dataset.mq2007.test(
+        for label_array, query_array in paddle.dataset.mq2007.test(
                 format="listwise"):
             self.assertEqual(len(label_array), len(query_array))
 

python/paddle/v2/tests/test_image.py → python/paddle/dataset/tests/test_image.py

@@ -15,7 +15,7 @@
 import unittest
 import numpy as np
 
-import paddle.v2.image as image
+import paddle.dataset.image as image
 
 
 class Image(unittest.TestCase):

python/paddle/v2/dataset/tests/test_sentiment.py → python/paddle/dataset/tests/test_sentiment.py

@@ -17,7 +17,7 @@
 
 import unittest
 import nltk
-import paddle.v2.dataset.sentiment as st
+import paddle.dataset.sentiment as st
 from nltk.corpus import movie_reviews
 
 

python/paddle/v2/dataset/tests/voc2012_test.py → python/paddle/dataset/tests/voc2012_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.voc2012
+import paddle.dataset.voc2012
 import unittest
 
 
@@ -26,15 +26,15 @@ class TestVOC(unittest.TestCase):
         return sum
 
     def test_train(self):
-        count = self.check_reader(paddle.v2.dataset.voc_seg.train())
+        count = self.check_reader(paddle.dataset.voc_seg.train())
         self.assertEqual(count, 2913)
 
     def test_test(self):
-        count = self.check_reader(paddle.v2.dataset.voc_seg.test())
+        count = self.check_reader(paddle.dataset.voc_seg.test())
         self.assertEqual(count, 1464)
 
     def test_val(self):
-        count = self.check_reader(paddle.v2.dataset.voc_seg.val())
+        count = self.check_reader(paddle.dataset.voc_seg.val())
         self.assertEqual(count, 1449)
 
 

python/paddle/v2/dataset/tests/wmt16_test.py → python/paddle/dataset/tests/wmt16_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2.dataset.wmt16
+import paddle.dataset.wmt16
 import unittest
 
 
@@ -34,28 +34,28 @@ class TestWMT16(unittest.TestCase):
 
     def test_train(self):
         for idx, sample in enumerate(
-                paddle.v2.dataset.wmt16.train(
+                paddle.dataset.wmt16.train(
                     src_dict_size=100000, trg_dict_size=100000)()):
             if idx >= 10: break
             self.checkout_one_sample(sample)
 
     def test_test(self):
         for idx, sample in enumerate(
-                paddle.v2.dataset.wmt16.test(
+                paddle.dataset.wmt16.test(
                     src_dict_size=1000, trg_dict_size=1000)()):
             if idx >= 10: break
             self.checkout_one_sample(sample)
 
     def test_val(self):
         for idx, sample in enumerate(
-                paddle.v2.dataset.wmt16.validation(
+                paddle.dataset.wmt16.validation(
                     src_dict_size=1000, trg_dict_size=1000)()):
             if idx >= 10: break
             self.checkout_one_sample(sample)
 
     def test_get_dict(self):
         dict_size = 1000
-        word_dict = paddle.v2.dataset.wmt16.get_dict("en", dict_size, True)
+        word_dict = paddle.dataset.wmt16.get_dict("en", dict_size, True)
         self.assertEqual(len(word_dict), dict_size)
         self.assertEqual(word_dict[0], "<s>")
         self.assertEqual(word_dict[1], "<e>")

python/paddle/v2/dataset/uci_housing.py → python/paddle/dataset/uci_housing.py

@@ -21,8 +21,7 @@ parse training set and test set into paddle reader creators.
 
 import numpy as np
 import os
-import paddle.v2.dataset.common
-from paddle.v2.parameters import Parameters
+import paddle.dataset.common
 
 __all__ = ['train', 'test']
 
@@ -85,7 +84,7 @@ def train():
     :rtype: callable
     """
     global UCI_TRAIN_DATA
-    load_data(paddle.v2.dataset.common.download(URL, 'uci_housing', MD5))
+    load_data(paddle.dataset.common.download(URL, 'uci_housing', MD5))
 
     def reader():
         for d in UCI_TRAIN_DATA:
@@ -105,7 +104,7 @@ def test():
     :rtype: callable
     """
     global UCI_TEST_DATA
-    load_data(paddle.v2.dataset.common.download(URL, 'uci_housing', MD5))
+    load_data(paddle.dataset.common.download(URL, 'uci_housing', MD5))
 
     def reader():
         for d in UCI_TEST_DATA:
@@ -114,21 +113,13 @@ def test():
     return reader
 
 
-def model():
-    tar_file = paddle.v2.dataset.common.download(URL_MODEL, 'fit_a_line.tar',
-                                                 MD5_MODEL)
-    with open(tar_file, 'r') as f:
-        parameters = Parameters.from_tar(f)
-    return parameters
-
-
 def fetch():
-    paddle.v2.dataset.common.download(URL, 'uci_housing', MD5)
+    paddle.dataset.common.download(URL, 'uci_housing', MD5)
 
 
 def convert(path):
     """
     Converts dataset to recordio format
     """
-    paddle.v2.dataset.common.convert(path, train(), 1000, "uci_housing_train")
-    paddle.v2.dataset.common.convert(path, test(), 1000, "uci_houseing_test")
+    paddle.dataset.common.convert(path, train(), 1000, "uci_housing_train")
+    paddle.dataset.common.convert(path, test(), 1000, "uci_houseing_test")

python/paddle/v2/dataset/voc2012.py → python/paddle/dataset/voc2012.py

@@ -22,8 +22,8 @@ with segmentation has been increased from 7,062 to 9,993.
 import tarfile
 import io
 import numpy as np
-from paddle.v2.dataset.common import download
-from paddle.v2.image import *
+from paddle.dataset.common import download
+from paddle.dataset.image import *
 from PIL import Image
 
 __all__ = ['train', 'test', 'val']

python/paddle/v2/dataset/wmt14.py → python/paddle/dataset/wmt14.py

@@ -22,8 +22,7 @@ parse training set and test set into paddle reader creators.
 import tarfile
 import gzip
 
-import paddle.v2.dataset.common
-from paddle.v2.parameters import Parameters
+import paddle.dataset.common
 
 __all__ = [
     'train',
@@ -123,7 +122,7 @@ def train(dict_size):
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
+        paddle.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
         'train/train', dict_size)
 
 
@@ -139,27 +138,20 @@ def test(dict_size):
     :rtype: callable
     """
     return reader_creator(
-        paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
+        paddle.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
         'test/test', dict_size)
 
 
 def gen(dict_size):
     return reader_creator(
-        paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
+        paddle.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
         'gen/gen', dict_size)
 
 
-def model():
-    tar_file = paddle.v2.dataset.common.download(URL_MODEL, 'wmt14', MD5_MODEL)
-    with gzip.open(tar_file, 'r') as f:
-        parameters = Parameters.from_tar(f)
-    return parameters
-
-
 def get_dict(dict_size, reverse=True):
     # if reverse = False, return dict = {'a':'001', 'b':'002', ...}
     # else reverse = true, return dict = {'001':'a', '002':'b', ...}
-    tar_file = paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN)
+    tar_file = paddle.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN)
     src_dict, trg_dict = __read_to_dict(tar_file, dict_size)
     if reverse:
         src_dict = {v: k for k, v in src_dict.items()}
@@ -168,8 +160,8 @@ def get_dict(dict_size, reverse=True):
 
 
 def fetch():
-    paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN)
-    paddle.v2.dataset.common.download(URL_MODEL, 'wmt14', MD5_MODEL)
+    paddle.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN)
+    paddle.dataset.common.download(URL_MODEL, 'wmt14', MD5_MODEL)
 
 
 def convert(path):
@@ -177,6 +169,5 @@ def convert(path):
     Converts dataset to recordio format
     """
     dict_size = 30000
-    paddle.v2.dataset.common.convert(path,
-                                     train(dict_size), 1000, "wmt14_train")
-    paddle.v2.dataset.common.convert(path, test(dict_size), 1000, "wmt14_test")
+    paddle.dataset.common.convert(path, train(dict_size), 1000, "wmt14_train")
+    paddle.dataset.common.convert(path, test(dict_size), 1000, "wmt14_test")

python/paddle/v2/dataset/wmt16.py → python/paddle/dataset/wmt16.py

@@ -33,7 +33,7 @@ import tarfile
 import gzip
 from collections import defaultdict
 
-import paddle.v2.dataset.common
+import paddle.dataset.common
 
 __all__ = [
     "train",
@@ -76,7 +76,7 @@ def __build_dict(tar_file, dict_size, save_path, lang):
 
 
 def __load_dict(tar_file, dict_size, lang, reverse=False):
-    dict_path = os.path.join(paddle.v2.dataset.common.DATA_HOME,
+    dict_path = os.path.join(paddle.dataset.common.DATA_HOME,
                              "wmt16/%s_%d.dict" % (lang, dict_size))
     if not os.path.exists(dict_path) or (
             len(open(dict_path, "r").readlines()) != dict_size):
@@ -178,8 +178,8 @@ def train(src_dict_size, trg_dict_size, src_lang="en"):
                                                    src_lang)
 
     return reader_creator(
-        tar_file=paddle.v2.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
-                                                   "wmt16.tar.gz"),
+        tar_file=paddle.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
+                                                "wmt16.tar.gz"),
         file_name="wmt16/train",
         src_dict_size=src_dict_size,
         trg_dict_size=trg_dict_size,
@@ -227,8 +227,8 @@ def test(src_dict_size, trg_dict_size, src_lang="en"):
                                                    src_lang)
 
     return reader_creator(
-        tar_file=paddle.v2.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
-                                                   "wmt16.tar.gz"),
+        tar_file=paddle.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
+                                                "wmt16.tar.gz"),
         file_name="wmt16/test",
         src_dict_size=src_dict_size,
         trg_dict_size=trg_dict_size,
@@ -274,8 +274,8 @@ def validation(src_dict_size, trg_dict_size, src_lang="en"):
                                                    src_lang)
 
     return reader_creator(
-        tar_file=paddle.v2.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
-                                                   "wmt16.tar.gz"),
+        tar_file=paddle.dataset.common.download(DATA_URL, "wmt16", DATA_MD5,
+                                                "wmt16.tar.gz"),
         file_name="wmt16/val",
         src_dict_size=src_dict_size,
         trg_dict_size=trg_dict_size,
@@ -303,12 +303,12 @@ def get_dict(lang, dict_size, reverse=False):
     if lang == "en": dict_size = min(dict_size, TOTAL_EN_WORDS)
     else: dict_size = min(dict_size, TOTAL_DE_WORDS)
 
-    dict_path = os.path.join(paddle.v2.dataset.common.DATA_HOME,
+    dict_path = os.path.join(paddle.dataset.common.DATA_HOME,
                              "wmt16/%s_%d.dict" % (lang, dict_size))
     assert os.path.exists(dict_path), "Word dictionary does not exist. "
     "Please invoke paddle.dataset.wmt16.train/test/validation first "
     "to build the dictionary."
-    tar_file = os.path.join(paddle.v2.dataset.common.DATA_HOME, "wmt16.tar.gz")
+    tar_file = os.path.join(paddle.dataset.common.DATA_HOME, "wmt16.tar.gz")
     return __load_dict(tar_file, dict_size, lang, reverse)
 
 
@@ -323,7 +323,7 @@ def convert(path, src_dict_size, trg_dict_size, src_lang):
     """Converts dataset to recordio format.
     """
 
-    paddle.v2.dataset.common.convert(
+    paddle.dataset.common.convert(
         path,
         train(
             src_dict_size=src_dict_size,
@@ -331,7 +331,7 @@ def convert(path, src_dict_size, trg_dict_size, src_lang):
             src_lang=src_lang),
         1000,
         "wmt16_train")
-    paddle.v2.dataset.common.convert(
+    paddle.dataset.common.convert(
         path,
         test(
             src_dict_size=src_dict_size,
@@ -339,7 +339,7 @@ def convert(path, src_dict_size, trg_dict_size, src_lang):
             src_lang=src_lang),
         1000,
         "wmt16_test")
-    paddle.v2.dataset.common.convert(
+    paddle.dataset.common.convert(
         path,
         validation(
             src_dict_size=src_dict_size,

python/paddle/fluid/tests/book/notest_rnn_encoder_decoer.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.framework as framework

python/paddle/fluid/tests/book/test_fit_a_line.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import contextlib
 import numpy

python/paddle/fluid/tests/book/test_image_classification.py

@@ -14,7 +14,7 @@
 
 from __future__ import print_function
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import contextlib
 import math

python/paddle/fluid/tests/book/test_label_semantic_roles.py

@@ -15,8 +15,8 @@
 import math
 
 import numpy as np
-import paddle.v2 as paddle
-import paddle.v2.dataset.conll05 as conll05
+import paddle
+import paddle.dataset.conll05 as conll05
 import paddle.fluid as fluid
 from paddle.fluid.initializer import init_on_cpu
 import contextlib

python/paddle/fluid/tests/book/test_machine_translation.py

@@ -14,7 +14,7 @@
 import contextlib
 
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import paddle.fluid.framework as framework
 import paddle.fluid.layers as pd

python/paddle/fluid/tests/book/test_recognize_digits.py

@@ -14,7 +14,7 @@
 from __future__ import print_function
 import argparse
 import paddle.fluid as fluid
-import paddle.v2 as paddle
+import paddle
 import sys
 import numpy
 import unittest

python/paddle/fluid/tests/book/test_recommender_system.py

@@ -16,7 +16,7 @@ import math
 import sys
 import os
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import paddle.fluid.framework as framework
 import paddle.fluid.layers as layers

python/paddle/fluid/tests/book/test_understand_sentiment.py

@@ -15,7 +15,7 @@ from __future__ import print_function
 
 import unittest
 import paddle.fluid as fluid
-import paddle.v2 as paddle
+import paddle
 import contextlib
 import math
 import numpy as np

python/paddle/fluid/tests/book/test_word2vec.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import unittest
 import os

python/paddle/fluid/tests/book_memory_optimization/test_memopt_fit_a_line.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import math
 import sys

python/paddle/fluid/tests/book_memory_optimization/test_memopt_image_classification_train.py

@@ -16,7 +16,7 @@ from __future__ import print_function
 
 import sys
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import math
 import sys

python/paddle/fluid/tests/book_memory_optimization/test_memopt_machine_translation.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.framework as framework

python/paddle/fluid/tests/demo/fc_gan.py

@@ -19,7 +19,7 @@ import os
 import matplotlib
 import numpy
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 
 matplotlib.use('Agg')

python/paddle/fluid/tests/test_cpp_reader.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 import numpy as np
 import sys

python/paddle/fluid/tests/test_error_clip.py

@@ -14,7 +14,7 @@
 
 from __future__ import print_function
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 
 BATCH_SIZE = 128

python/paddle/fluid/tests/test_gradient_clip.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import numpy as np
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid as fluid
 
 BATCH_SIZE = 128

python/paddle/fluid/tests/test_mnist_if_else_op.py

@@ -12,12 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import paddle
 import paddle.fluid.layers as layers
 from paddle.fluid.framework import Program, program_guard, default_main_program, default_startup_program
 from paddle.fluid.executor import Executor
 from paddle.fluid.optimizer import MomentumOptimizer
 import paddle.fluid.core as core
-import paddle.v2 as paddle
 import unittest
 import numpy as np
 

python/paddle/fluid/tests/unittests/test_dyn_rnn.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
+import paddle
 import unittest
 import numpy
 

python/paddle/fluid/tests/unittests/test_dynrnn_static_input.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import unittest
-import paddle.v2 as paddle
+import paddle
 import paddle.fluid.core as core
 import paddle.fluid as fluid
 from paddle.fluid.backward import append_backward

python/paddle/fluid/tests/unittests/test_multi_pass_reader.py

@@ -15,8 +15,8 @@
 import unittest
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
-import paddle.v2.dataset.mnist as mnist
+import paddle
+import paddle.dataset.mnist as mnist
 
 
 class TestMultipleReader(unittest.TestCase):

python/paddle/fluid/tests/unittests/test_multiple_reader.py

@@ -15,8 +15,8 @@
 import unittest
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
-import paddle.v2.dataset.mnist as mnist
+import paddle
+import paddle.dataset.mnist as mnist
 from shutil import copyfile
 
 

python/paddle/fluid/tests/unittests/test_parallel_executor.py

@@ -16,9 +16,9 @@ import numpy
 import unittest
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
-import paddle.v2.dataset.mnist as mnist
-import paddle.v2.dataset.wmt16 as wmt16
+import paddle
+import paddle.dataset.mnist as mnist
+import paddle.dataset.wmt16 as wmt16
 
 
 def simple_fc_net():

python/paddle/fluid/tests/unittests/test_recordio_reader.py

@@ -15,8 +15,8 @@
 import unittest
 
 import paddle.fluid as fluid
-import paddle.v2 as paddle
-import paddle.v2.dataset.mnist as mnist
+import paddle
+import paddle.dataset.mnist as mnist
 
 
 class TestRecordIO(unittest.TestCase):

python/paddle/v2/reader/creator.py → python/paddle/reader/creator.py

@@ -16,7 +16,7 @@ Creator package contains some simple reader creator, which could
 be used in user program.
 """
 
-__all__ = ['np_array', 'text_file', 'recordio', 'cloud_reader']
+__all__ = ['np_array', 'text_file', 'recordio']
 
 
 def np_array(x):
@@ -66,7 +66,7 @@ def recordio(paths, buf_size=100):
     """
 
     import recordio as rec
-    import paddle.v2.reader.decorator as dec
+    import paddle.reader.decorator as dec
     import cPickle as pickle
 
     def reader():
@@ -83,48 +83,3 @@ def recordio(paths, buf_size=100):
         f.close()
 
     return dec.buffered(reader, buf_size)
-
-
-pass_num = 0
-
-
-def cloud_reader(paths, etcd_endpoints, timeout_sec=5, buf_size=64):
-    """
-    Create a data reader that yield a record one by one from
-        the paths:
-    :paths: path of recordio files, can be a string or a string list.
-    :etcd_endpoints: the endpoints for etcd cluster
-    :returns: data reader of recordio files.
-
-    ..  code-block:: python
-        from paddle.v2.reader.creator import cloud_reader
-        etcd_endpoints = "http://127.0.0.1:2379"
-        trainer.train.(
-            reader=cloud_reader(["/work/dataset/uci_housing/uci_housing*"], etcd_endpoints),
-        )
-    """
-    import os
-    import cPickle as pickle
-    import paddle.v2.master as master
-    c = master.client(etcd_endpoints, timeout_sec, buf_size)
-
-    if isinstance(paths, basestring):
-        path = [paths]
-    else:
-        path = paths
-    c.set_dataset(path)
-
-    def reader():
-        global pass_num
-        c.paddle_start_get_records(pass_num)
-        pass_num += 1
-
-        while True:
-            r, e = c.next_record()
-            if not r:
-                if e != -2:
-                    print "get record error: ", e
-                break
-            yield pickle.loads(r)
-
-    return reader

python/paddle/v2/reader/tests/creator_test.py → python/paddle/reader/tests/creator_test.py

@@ -28,14 +28,14 @@
 import os
 import unittest
 import numpy as np
-import paddle.v2.reader.creator
+import paddle.reader.creator
 
 
 class TestNumpyArray(unittest.TestCase):
     def test_numpy_array(self):
         l = [[1, 2, 3], [4, 5, 6]]
         x = np.array(l, np.int32)
-        reader = paddle.v2.reader.creator.np_array(x)
+        reader = paddle.reader.creator.np_array(x)
         for idx, e in enumerate(reader()):
             self.assertItemsEqual(e, l[idx])
 
@@ -43,14 +43,14 @@ class TestNumpyArray(unittest.TestCase):
 class TestTextFile(unittest.TestCase):
     def test_text_file(self):
         path = os.path.join(os.path.dirname(__file__), "test_data_creator.txt")
-        reader = paddle.v2.reader.creator.text_file(path)
+        reader = paddle.reader.creator.text_file(path)
         for idx, e in enumerate(reader()):
             self.assertEqual(e, str(idx * 2) + " " + str(idx * 2 + 1))
 
 
 class TestRecordIO(unittest.TestCase):
     def do_test(self, path):
-        reader = paddle.v2.reader.creator.recordio(path)
+        reader = paddle.reader.creator.recordio(path)
         idx = 0
         for e in reader():
             if idx == 0:

python/paddle/v2/reader/tests/decorator_test.py → python/paddle/reader/tests/decorator_test.py

@@ -15,7 +15,7 @@
 import time
 import unittest
 
-import paddle.v2.reader
+import paddle.reader
 
 
 def reader_creator_10(dur):
@@ -39,7 +39,7 @@ class TestMap(unittest.TestCase):
             yield "h"
             yield "i"
 
-        r = paddle.v2.reader.map_readers(tokenize, read)
+        r = paddle.reader.map_readers(tokenize, read)
         for i, e in enumerate(r()):
             self.assertEqual(e, i)
 
@@ -47,7 +47,7 @@ class TestMap(unittest.TestCase):
 class TestBuffered(unittest.TestCase):
     def test_read(self):
         for size in range(20):
-            b = paddle.v2.reader.buffered(reader_creator_10(0), size)
+            b = paddle.reader.buffered(reader_creator_10(0), size)
             c = 0
             for i in b():
                 self.assertEqual(i, c)
@@ -56,7 +56,7 @@ class TestBuffered(unittest.TestCase):
 
     def test_buffering(self):
         # read have 30ms delay.
-        b = paddle.v2.reader.buffered(reader_creator_10(0.03), 10)
+        b = paddle.reader.buffered(reader_creator_10(0.03), 10)
         last_time = time.time()
         for idx, i in enumerate(b()):
             elapsed_time = time.time() - last_time
@@ -70,17 +70,17 @@ class TestBuffered(unittest.TestCase):
 
 class TestCompose(unittest.TestCase):
     def test_compse(self):
-        reader = paddle.v2.reader.compose(
+        reader = paddle.reader.compose(
             reader_creator_10(0), reader_creator_10(0))
         for idx, e in enumerate(reader()):
             self.assertEqual(e, (idx, idx))
 
     def test_compose_not_aligned(self):
         total = 0
-        reader = paddle.v2.reader.compose(
-            paddle.v2.reader.chain(reader_creator_10(0), reader_creator_10(0)),
+        reader = paddle.reader.compose(
+            paddle.reader.chain(reader_creator_10(0), reader_creator_10(0)),
             reader_creator_10(0))
-        with self.assertRaises(paddle.v2.reader.ComposeNotAligned):
+        with self.assertRaises(paddle.reader.ComposeNotAligned):
             for e in reader():
                 total += 1
         # expecting 10, not 20
@@ -88,8 +88,8 @@ class TestCompose(unittest.TestCase):
 
     def test_compose_not_aligned_no_check(self):
         total = 0
-        reader = paddle.v2.reader.compose(
-            paddle.v2.reader.chain(reader_creator_10(0), reader_creator_10(0)),
+        reader = paddle.reader.compose(
+            paddle.reader.chain(reader_creator_10(0), reader_creator_10(0)),
             reader_creator_10(0),
             check_alignment=False)
         for e in reader():
@@ -100,7 +100,7 @@ class TestCompose(unittest.TestCase):
 
 class TestChain(unittest.TestCase):
     def test_chain(self):
-        c = paddle.v2.reader.chain(reader_creator_10(0), reader_creator_10(0))
+        c = paddle.reader.chain(reader_creator_10(0), reader_creator_10(0))
         idx = 0
         for e in c():
             self.assertEqual(e, idx % 10)
@@ -113,7 +113,7 @@ class TestShuffle(unittest.TestCase):
         case = [(0, True), (1, True), (10, False), (100, False)]
         a = reader_creator_10(0)
         for size, checkEq in case:
-            s = paddle.v2.reader.shuffle(a, size)
+            s = paddle.reader.shuffle(a, size)
             total = 0
             for idx, e in enumerate(s()):
                 if checkEq:
@@ -133,9 +133,9 @@ class TestXmap(unittest.TestCase):
         for order in orders:
             for tNum in thread_nums:
                 for size in buffered_size:
-                    reader = paddle.v2.reader.xmap_readers(mapper,
-                                                           reader_creator_10(0),
-                                                           tNum, size, order)
+                    reader = paddle.reader.xmap_readers(mapper,
+                                                        reader_creator_10(0),
+                                                        tNum, size, order)
                     for n in xrange(3):
                         result = []
                         for i in reader():
@@ -150,7 +150,7 @@ class TestPipeReader(unittest.TestCase):
     def test_pipe_reader(self):
         def example_reader(myfiles):
             for f in myfiles:
-                pr = paddle.v2.reader.PipeReader("cat %s" % f, bufsize=128)
+                pr = paddle.reader.PipeReader("cat %s" % f, bufsize=128)
                 for l in pr.get_line():
                     yield l
 

python/paddle/v2/__init__.py

@@ -22,17 +22,13 @@ import data_type
 import topology
 import networks
 import evaluator
-from . import dataset
-from . import reader
 from . import plot
 import attr
 import op
 import pooling
 import inference
 import networks
-import minibatch
 import plot
-import image
 import paddle.trainer.config_parser as cp
 
 __all__ = [
@@ -48,14 +44,11 @@ __all__ = [
     'data_type',
     'attr',
     'pooling',
-    'dataset',
-    'reader',
     'topology',
     'networks',
     'infer',
     'plot',
     'evaluator',
-    'image',
     'master',
 ]
 
@@ -153,4 +146,3 @@ def init(**kwargs):
 
 
 infer = inference.infer
-batch = minibatch.batch

python/paddle/v2/inference.py

@@ -15,7 +15,7 @@
 import numpy
 import collections
 import topology
-import minibatch
+import paddle
 import cPickle
 
 __all__ = ['infer', 'Inference']
@@ -80,7 +80,7 @@ class Inference(object):
             for each_sample in input:
                 yield each_sample
 
-        reader = minibatch.batch(__reader_impl__, batch_size=batch_size)
+        reader = paddle.batch(__reader_impl__, batch_size=batch_size)
 
         self.__gradient_machine__.start()
         for data_batch in reader():

python/paddle/v2/layer.py

@@ -20,7 +20,7 @@ The primary usage shows below.
 
 ..  code-block:: python
 
-    import paddle.v2 as paddle
+    import paddle
 
     img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
     hidden = paddle.layer.fc(input=img, size=200)

python/paddle/v2/tests/CMakeLists.txt

 py_test(test_op SRCS test_op.py)
-py_test(test_image SRCS test_image.py)
 py_test(test_layer SRCS test_layer.py)
 py_test(test_topology SRCS test_topology.py)
 py_test(test_rnn_layer SRCS test_rnn_layer.py)

python/paddle/v2/tests/test_paramconf_order.py

@@ -27,6 +27,7 @@
 # limitations under the License.
 import unittest
 import math
+import paddle.dataset as dataset
 import paddle.v2 as paddle
 
 
@@ -40,7 +41,7 @@ def wordemb(inlayer):
 
 
 def train():
-    word_dict = paddle.dataset.imikolov.build_dict()
+    word_dict = dataset.imikolov.build_dict()
     dict_size = len(word_dict)
     # Every layer takes integer value of range [0, dict_size)
     firstword = paddle.layer.data(

python/setup.py.in

@@ -63,6 +63,8 @@ write_version_py(filename='@PADDLE_SOURCE_DIR@/python/paddle/version.py')
 
 packages=['paddle',
           'paddle.utils',
+          'paddle.dataset',
+          'paddle.reader',
           'paddle.fluid',
           'paddle.fluid.proto',
           'paddle.fluid.proto.profiler',
@@ -73,8 +75,6 @@ if '${WITH_FLUID_ONLY}'== 'OFF':
                'paddle.trainer',
                'paddle.trainer_config_helpers',
                'paddle.v2',
-               'paddle.v2.dataset',
-               'paddle.v2.reader',
                'paddle.v2.master',
                'paddle.v2.plot',
                'py_paddle']