format code

doc/api/v2/data.rst

 ==================================
-Data Reader Inferface and DataSets 
+Data Reader Inferface and DataSets
 ==================================
 
 
@@ -78,7 +78,7 @@ imikolov
     :noindex:
 
 movielens
-+++++++++    
++++++++++
 
 ..  automodule:: paddle.v2.dataset.movielens
     :members:

doc/api/v2/run_logic.rst

@@ -20,11 +20,12 @@ Event
 =====
 
 ..  automodule:: paddle.v2.event
-    :members: 
+    :members:
     :noindex:
 
 Inference
 =========
 
 ..  autofunction:: paddle.v2.infer
-    :noindex:
\ No newline at end of file
+    :noindex:
+    
\ No newline at end of file

python/paddle/v2/dataset/cifar.py

@@ -17,11 +17,11 @@ CIFAR dataset.
 This module will download dataset from https://www.cs.toronto.edu/~kriz/cifar.html and
 parse train/test set into paddle reader creators.
 
-The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 
+The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000
 images per class. There are 50000 training images and 10000 test images.
 
-The CIFAR-100 dataset is just like the CIFAR-10, except it has 100 classes containing 
-600 images each. There are 500 training images and 100 testing images per class. 
+The CIFAR-100 dataset is just like the CIFAR-10, except it has 100 classes containing
+600 images each. There are 500 training images and 100 testing images per class.
 
 """
 

python/paddle/v2/dataset/conll05.py

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-Conll05 dataset.  
-Paddle semantic role labeling Book and demo use this dataset as an example. Because 
-Conll05 is not free in public, the default downloaded URL is test set of 
-Conll05 (which is public). Users can change URL and MD5 to their Conll dataset. 
+Conll05 dataset.
+Paddle semantic role labeling Book and demo use this dataset as an example. Because
+Conll05 is not free in public, the default downloaded URL is test set of
+Conll05 (which is public). Users can change URL and MD5 to their Conll dataset.
 And a pre-trained word vector model based on Wikipedia corpus is used to initialize SRL model.
 """
 
@@ -200,7 +200,7 @@ def test():
     Conll05 test set creator.
 
     Because the train dataset is not free, the test dataset is used for training.
-    It returns a reader creator, each sample in the reader is nine features, including sentence 
+    It returns a reader creator, each sample in the reader is nine features, including sentence
     sequence, predicate, predicate context, predicate context flag and tagged sequence.
 
     :return: Train reader creator

python/paddle/v2/dataset/imdb.py

@@ -14,10 +14,10 @@
 """
 IMDB dataset.
 
-This module download IMDB dataset from 
-http://ai.stanford.edu/%7Eamaas/data/sentiment/, which contains a set of 25,000 
-highly polar movie reviews for training, and 25,000 for testing. Besides, this 
-module also provides API for build dictionary and parse train set and test set 
+This module download IMDB dataset from
+http://ai.stanford.edu/%7Eamaas/data/sentiment/, which contains a set of 25,000
+highly polar movie reviews for training, and 25,000 for testing. Besides, this
+module also provides API for build dictionary and parse train set and test set
 into paddle reader creators.
 """
 
@@ -122,7 +122,7 @@ def train(word_idx):
     """
     IMDB train set creator.
 
-    It returns a reader creator, each sample in the reader is an index 
+    It returns a reader creator, each sample in the reader is an index
     sequence and label in [0, 1].
 
     :param word_idx: word dictionary
@@ -139,7 +139,7 @@ def test(word_idx):
     """
     IMDB test set creator.
 
-    It returns a reader creator, each sample in the reader is an index 
+    It returns a reader creator, each sample in the reader is an index
     sequence and label in [0, 1].
 
     :param word_idx: word dictionary

python/paddle/v2/dataset/imikolov.py

@@ -91,7 +91,7 @@ def train(word_idx, n):
     """
     imikolov train set creator.
 
-    It returns a reader creator, each sample in the reader is an index 
+    It returns a reader creator, each sample in the reader is an index
     tuple.
 
     :param word_idx: word dictionary
@@ -108,7 +108,7 @@ def test(word_idx, n):
     """
     imikolov test set creator.
 
-    It returns a reader creator, each sample in the reader is an index 
+    It returns a reader creator, each sample in the reader is an index
     tuple.
 
     :param word_idx: word dictionary

python/paddle/v2/dataset/movielens.py

@@ -14,9 +14,9 @@
 """
 Movielens 1-M dataset.
 
-Movielens 1-M dataset contains 1 million ratings from 6000 users on 4000 movies, which was 
-collected by GroupLens Research. This module will download Movielens 1-M dataset from 
-http://files.grouplens.org/datasets/movielens/ml-1m.zip and parse train/test set 
+Movielens 1-M dataset contains 1 million ratings from 6000 users on 4000 movies, which was
+collected by GroupLens Research. This module will download Movielens 1-M dataset from
+http://files.grouplens.org/datasets/movielens/ml-1m.zip and parse train/test set
 into paddle reader creators.
 
 """

python/paddle/v2/dataset/uci_housing.py

@@ -14,7 +14,7 @@
 """
 UCI Housing dataset.
 
-This module will download dataset from 
+This module will download dataset from
 https://archive.ics.uci.edu/ml/machine-learning-databases/housing/ and
 parse train/test set into paddle reader creators.
 """
@@ -75,7 +75,7 @@ def train():
     """
     UCI_HOUSING train set creator.
 
-    It returns a reader creator, each sample in the reader is features after normalization 
+    It returns a reader creator, each sample in the reader is features after normalization
     and price number.
 
     :return: Train reader creator

python/paddle/v2/dataset/wmt14.py

@@ -14,7 +14,7 @@
 """
 WMT14 dataset.
 The original WMT14 dataset is too large and a small set of data for set is provided.
-This module will download dataset from 
+This module will download dataset from
 http://paddlepaddle.cdn.bcebos.com/demo/wmt_shrinked_data/wmt14.tgz and
 parse train/test set into paddle reader creators.
 
@@ -102,7 +102,7 @@ def train(dict_size):
     """
     WMT14 train set creator.
 
-    It returns a reader creator, each sample in the reader is source language word index 
+    It returns a reader creator, each sample in the reader is source language word index
     sequence, target language word index sequence and next word index sequence.
 
     :return: Train reader creator
@@ -116,7 +116,7 @@ def test(dict_size):
     """
     WMT14 test set creator.
 
-    It returns a reader creator, each sample in the reader is source language word index 
+    It returns a reader creator, each sample in the reader is source language word index
     sequence, target language word index sequence and next word index sequence.
 
     :return: Train reader creator

python/paddle/v2/inference.py

@@ -49,7 +49,7 @@ class Inference(object):
     def iter_infer_field(self, field, **kwargs):
         for result in self.iter_infer(**kwargs):
             yield [each_result[field] for each_result in result]
- 
+
     def infer(self, field='value', **kwargs):
         retv = None
         for result in self.iter_infer_field(field=field, **kwargs):

python/paddle/v2/optimizer.py

@@ -195,7 +195,7 @@ class AdaDelta(Optimizer):
     :param epsilon: :math:`\\rho` in equation
     :type epsilon: float
     """
-    
+
     def __init__(self, rho=0.95, epsilon=1e-06, **kwargs):
         learning_method = v1_optimizers.AdaDeltaOptimizer(
             rho=rho, epsilon=epsilon)

python/paddle/v2/trainer.py

@@ -130,7 +130,7 @@ class SGD(object):
         Testing method. Will test input data.
 
         :param reader: A reader that reads and yeilds data items.
-        :type reader: collections.Iterable      
+        :type reader: collections.Iterable  
         :param feeding: Feeding is a map of neural network input name and array
                         index that reader returns.
         :type feeding: dict