Fix write bytes in dataset download

python/paddle/dataset/cifar.py

@@ -59,6 +59,11 @@ def reader_creator(filename, sub_name, cycle=False):
 
             while True:
                 for name in names:
+                    import sys
+                    print(name)
+                    sys.stdout.flush()
+                    print(f.extractfile(name))
+                    sys.stdout.flush()
                     batch = pickle.load(f.extractfile(name))
                     for item in read_batch(batch):
                         yield item

python/paddle/dataset/common.py

@@ -86,15 +86,21 @@ def download(url, module_name, md5sum, save_name=None):
         total_length = r.headers.get('content-length')
 
         if total_length is None:
-            with open(filename, 'w') as f:
-                shutil.copyfileobj(r.raw, f)
+            with open(filename, 'wb') as f:
+                import sys
+                print("write follow block")
+                sys.stdout.flush()
+                shutil.copyfileobj(cpt.to_bytes(r.raw), f)
         else:
-            with open(filename, 'w') as f:
+            with open(filename, 'wb') as f:
+                import sys
+                print("write follow length")
+                sys.stdout.flush()
                 dl = 0
                 total_length = int(total_length)
                 for data in r.iter_content(chunk_size=4096):
                     dl += len(data)
-                    f.write(cpt.to_literal_str(data))
+                    f.write(cpt.to_bytes(data))
                     done = int(50 * dl / total_length)
                     sys.stdout.write("\r[%s%s]" % ('=' * done,
                                                    ' ' * (50 - done)))

python/paddle/dataset/conll05.py

@@ -24,19 +24,20 @@ import tarfile
 import gzip
 import itertools
 import paddle.dataset.common
+import paddle.fluid.compat as cpt
 from six.moves import zip, range
 
 __all__ = ['test, get_dict', 'get_embedding', 'convert']
 
 DATA_URL = 'http://www.cs.upc.edu/~srlconll/conll05st-tests.tar.gz'
 DATA_MD5 = '387719152ae52d60422c016e92a742fc'
-WORDDICT_URL = 'http://paddlepaddle.bj.bcebos.com/demo/srl_dict_and_embedding/wordDict.txt'
+WORDDICT_URL = 'http://paddlemodels.bj.bcebos.com/conll05st/wordDict.txt'
 WORDDICT_MD5 = 'ea7fb7d4c75cc6254716f0177a506baa'
-VERBDICT_URL = 'http://paddlepaddle.bj.bcebos.com/demo/srl_dict_and_embedding/verbDict.txt'
+VERBDICT_URL = 'http://paddlemodels.bj.bcebos.com/conll05st/verbDict.txt'
 VERBDICT_MD5 = '0d2977293bbb6cbefab5b0f97db1e77c'
-TRGDICT_URL = 'http://paddlepaddle.bj.bcebos.com/demo/srl_dict_and_embedding/targetDict.txt'
+TRGDICT_URL = 'http://paddlemodels.bj.bcebos.com/conll05st/targetDict.txt'
 TRGDICT_MD5 = 'd8c7f03ceb5fc2e5a0fa7503a4353751'
-EMB_URL = 'http://paddlepaddle.bj.bcebos.com/demo/srl_dict_and_embedding/emb'
+EMB_URL = 'http://paddlemodels.bj.bcebos.com/conll05st/emb'
 EMB_MD5 = 'bf436eb0faa1f6f9103017f8be57cdb7'
 
 UNK_IDX = 0
@@ -89,8 +90,8 @@ def corpus_reader(data_path, words_name, props_name):
             labels = []
             one_seg = []
             for word, label in zip(words_file, props_file):
-                word = word.strip()
-                label = label.strip().split()
+                word = cpt.to_literal_str(word.strip())
+                label = cpt.to_literal_str(label.strip().split())
 
                 if len(label) == 0:  # end of sentence
                     for i in range(len(one_seg[0])):

python/paddle/fluid/executor.py

@@ -320,7 +320,7 @@ class Executor(object):
         # append fetch_operators
         if not has_fetch_operators(global_block, fetch_list, fetch_var_name):
             for i, var in enumerate(fetch_list):
-                assert isinstance(var, Variable) or isinstance(var, str), (
+                assert isinstance(var, Variable) or isinstance(var, six.text_type), (
                     "Wrong type for fetch_list[%s]: %s" % (i, type(var)))
                 global_block.append_op(
                     type='fetch',

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

@@ -55,7 +55,7 @@ def resnet_cifar10(input, depth=32):
         return tmp
 
     assert (depth - 2) % 6 == 0
-    n = (depth - 2) / 6
+    n = (depth - 2) // 6
     conv1 = conv_bn_layer(
         input=input, ch_out=16, filter_size=3, stride=1, padding=1)
     res1 = layer_warp(basicblock, conv1, 16, 16, n, 1)