update code for v1.6 (#3621)

PaddleNLP/sentiment_classification/README.md

@@ -29,7 +29,7 @@
 
 1. PaddlePaddle 安装
 
-   本项目依赖于 PaddlePaddle Fluid 1.3.2 及以上版本，请参考 [安装指南](http://www.paddlepaddle.org/#quick-start) 进行安装
+   本项目依赖于 PaddlePaddle Fluid 1.6 及以上版本，请参考 [安装指南](http://www.paddlepaddle.org/#quick-start) 进行安装
 
 2. 代码安装
 
@@ -42,7 +42,7 @@
 
 3. 环境依赖
 
-   请参考 PaddlePaddle [安装说明](https://www.paddlepaddle.org.cn/documentation/docs/zh/1.5/beginners_guide/install/index_cn.html) 部分的内容
+   Python 2 的版本要求 2.7.15+，Python 3 的版本要求 3.5.1+/3.6/3.7，其它环境请参考 PaddlePaddle [安装说明](https://www.paddlepaddle.org.cn/documentation/docs/zh/1.5/beginners_guide/install/index_cn.html) 部分的内容
 
 ### 代码结构说明
 

PaddleNLP/sentiment_classification/reader.py

@@ -72,12 +72,12 @@ class SentaProcessor(object):
         Generate data for train, dev or infer
         """
         if phase == "train":
-            return paddle.batch(self.get_train_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
+            return fluid.io.batch(self.get_train_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
             #return self.get_train_examples(self.data_dir, epoch, self.max_seq_len)
         elif phase == "dev":
-            return paddle.batch(self.get_dev_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
+            return fluid.io.batch(self.get_dev_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
         elif phase == "infer":
-            return paddle.batch(self.get_test_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
+            return fluid.io.batch(self.get_test_examples(self.data_dir, epoch, self.max_seq_len), batch_size)
         else:
             raise ValueError(
                 "Unknown phase, which should be in ['train', 'dev', 'infer'].")

PaddleNLP/sentiment_classification/run_classifier.py

@@ -21,6 +21,7 @@ from nets import cnn_net
 from nets import bilstm_net
 from nets import gru_net
 from models.model_check import check_cuda
+from models.model_check import check_version
 from config import PDConfig
 
 import paddle
@@ -39,11 +40,11 @@ def create_model(args,
     """
     
     data = fluid.layers.data(
-            name="src_ids", shape=[-1, args.max_seq_len, 1], dtype='int64')
+            name="src_ids", shape=[-1, args.max_seq_len], dtype='int64')
     label = fluid.layers.data(
             name="label", shape=[-1, 1], dtype="int64")
     seq_len = fluid.layers.data(
-            name="seq_len", shape=[-1, 1], dtype="int64")
+            name="seq_len", shape=[-1], dtype="int64")
     
     data_reader = fluid.io.PyReader(feed_list=[data, label, seq_len], 
         capacity=4, iterable=False)

PaddleNLP/sentiment_classification/run_ernie_classifier.py

@@ -48,16 +48,21 @@ def ernie_pyreader(args, pyreader_name):
     labels = fluid.layers.data(
         name="labels", shape=[-1, 1], dtype="int64")
     seq_lens = fluid.layers.data(
-        name="seq_lens", shape=[-1, 1], dtype="int64")
+        name="seq_lens", shape=[-1], dtype="int64")
+    
+    pyreader = fluid.io.DataLoader.from_generator(
+        feed_list=[src_ids, sent_ids, pos_ids, input_mask, labels, seq_lens],
+        capacity=50,
+        iterable=False,
+        use_double_buffer=True)
     
-    pyreader = fluid.io.PyReader(feed_list=[src_ids, sent_ids, pos_ids, input_mask, labels, seq_lens],
-        capacity=4, iterable=False)
     ernie_inputs = {
         "src_ids": src_ids,
         "sent_ids": sent_ids,
         "pos_ids": pos_ids,
         "input_mask": input_mask,
         "seq_lens": seq_lens}
+    
     return pyreader, ernie_inputs, labels
 
 def create_model(args,
@@ -299,15 +304,15 @@ def main(args):
 
     if args.do_train:
         train_exe = exe
-        train_pyreader.decorate_batch_generator(train_data_generator)
+        train_pyreader.set_batch_generator(train_data_generator)
     else:
         train_exe = None
     if args.do_val:
         test_exe = exe
-        test_pyreader.decorate_batch_generator(test_data_generator)
+        test_pyreader.set_batch_generator(test_data_generator)
     if args.do_infer:
         test_exe = exe
-        infer_pyreader.decorate_batch_generator(infer_data_generator)
+        infer_pyreader.set_batch_generator(infer_data_generator)
 
     if args.do_train:
         train_pyreader.start()