Merge pull request #11402 from chengduoZH/refine_batch_func

Change drop_last defalut value

python/paddle/batch.py

@@ -15,7 +15,7 @@
 __all__ = ['batch']
 
 
-def batch(reader, batch_size, drop_last=False):
+def batch(reader, batch_size, drop_last=True):
     """
     Create a batched reader.
 

python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py

@@ -96,10 +96,11 @@ def train(use_cuda, train_program, params_dirname):
     train_reader = paddle.batch(
         paddle.reader.shuffle(
             cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10),
-        batch_size=BATCH_SIZE)
+        batch_size=BATCH_SIZE,
+        drop_last=False)
 
     test_reader = paddle.batch(
-        paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE)
+        paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE, drop_last=False)
 
     def event_handler(event):
         if isinstance(event, fluid.EndStepEvent):

python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py

@@ -73,10 +73,11 @@ def train(use_cuda, train_program, params_dirname):
     train_reader = paddle.batch(
         paddle.reader.shuffle(
             cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10),
-        batch_size=BATCH_SIZE)
+        batch_size=BATCH_SIZE,
+        drop_last=False)
 
     test_reader = paddle.batch(
-        paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE)
+        paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE, drop_last=False)
 
     def event_handler(event):
         if isinstance(event, fluid.EndStepEvent):

python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py

@@ -87,7 +87,9 @@ def train(use_cuda, train_program, params_dirname):
     def event_handler(event):
         if isinstance(event, fluid.EndEpochEvent):
             test_reader = paddle.batch(
-                paddle.dataset.imdb.test(word_dict), batch_size=BATCH_SIZE)
+                paddle.dataset.imdb.test(word_dict),
+                batch_size=BATCH_SIZE,
+                drop_last=False)
             avg_cost, acc = trainer.test(
                 reader=test_reader, feed_order=['words', 'label'])
 
@@ -113,7 +115,8 @@ def train(use_cuda, train_program, params_dirname):
     train_reader = paddle.batch(
         paddle.reader.shuffle(
             paddle.dataset.imdb.train(word_dict), buf_size=25000),
-        batch_size=BATCH_SIZE)
+        batch_size=BATCH_SIZE,
+        drop_last=False)
 
     trainer.train(
         num_epochs=1,

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

@@ -56,7 +56,7 @@ BATCH_SIZE = 200
 
 # fix the order of training data
 train_reader = paddle.batch(
-    paddle.dataset.uci_housing.train(), batch_size=BATCH_SIZE)
+    paddle.dataset.uci_housing.train(), batch_size=BATCH_SIZE, drop_last=False)
 
 # train_reader = paddle.batch(
 #     paddle.reader.shuffle(

python/paddle/v2/minibatch.py

@@ -15,7 +15,7 @@
 __all__ = ['batch']
 
 
-def batch(reader, batch_size, drop_last=False):
+def batch(reader, batch_size, drop_last=True):
     """
     Create a batched reader.