fix demo for py3

python/examples/imagenet/image_http_client.py

@@ -17,10 +17,16 @@ import base64
 import json
 import time
 import os
+import sys
+
+py_version = sys.version_info[0]
 
 
 def predict(image_path, server):
+    if py_version == 2:
         image = base64.b64encode(open(image_path).read())
+    else:
+        image = base64.b64encode(open(image_path, "rb").read()).decode("utf-8")
     req = json.dumps({"image": image, "fetch": ["score"]})
     r = requests.post(
         server, data=req, headers={"Content-Type": "application/json"})
@@ -28,15 +34,6 @@ def predict(image_path, server):
     return r
 
 
-def batch_predict(image_path, server):
-    image = base64.b64encode(open(image_path).read())
-    req = json.dumps({"image": [image, image], "fetch": ["score"]})
-    r = requests.post(
-        server, data=req, headers={"Content-Type": "application/json"})
-    print(r.json()["result"][1]["score"][0])
-    return r
-
-
 if __name__ == "__main__":
     server = "http://127.0.0.1:9393/image/prediction"
     image_list = os.listdir("./image_data/n01440764/")

python/examples/imagenet/image_rpc_client.py

@@ -19,16 +19,15 @@ import time
 
 client = Client()
 client.load_client_config(sys.argv[1])
-client.connect(["127.0.0.1:9295"])
+client.connect(["127.0.0.1:9393"])
 reader = ImageReader()
 
 start = time.time()
 for i in range(1000):
-    with open("./data/n01440764_10026.JPEG") as f:
+    with open("./data/n01440764_10026.JPEG", "rb") as f:
         img = f.read()
     img = reader.process_image(img).reshape(-1)
     fetch_map = client.predict(feed={"image": img}, fetch=["score"])
-    print(i)
 end = time.time()
 print(end - start)
 

python/examples/imdb/imdb_reader.py

@@ -19,15 +19,23 @@ import paddle
 import re
 import paddle.fluid.incubate.data_generator as dg
 
+py_version = sys.version_info[0]
+
 
 class IMDBDataset(dg.MultiSlotDataGenerator):
     def load_resource(self, dictfile):
         self._vocab = {}
         wid = 0
+        if py_version == 2:
             with open(dictfile) as f:
                 for line in f:
                     self._vocab[line.strip()] = wid
                     wid += 1
+        else:
+            with open(dictfile, encoding="utf-8") as f:
+                for line in f:
+                    self._vocab[line.strip()] = wid
+                    wid += 1
         self._unk_id = len(self._vocab)
         self._pattern = re.compile(r'(;|,|\.|\?|!|\s|\(|\))')
         self.return_value = ("words", [1, 2, 3, 4, 5, 6]), ("label", [0])