fix web service

python/examples/bert/bert_web_service.py

@@ -24,7 +24,9 @@ class BertService(WebService):
         self.reader = BertReader(vocab_file="vocab.txt", max_seq_len=128)
 
     def preprocess(self, feed={}, fetch=[]):
-        feed_res = self.reader.process(feed["words"].encode("utf-8"))
+        feed_res = [{
+            "words": self.reader.process(ins["words"].encode("utf-8"))
+        } for ins in feed]
         return feed_res, fetch
 
 

python/examples/imagenet/image_classification_service.py

@@ -23,23 +23,14 @@ from paddle_serving_app import ImageReader
 class ImageService(WebService):
     def preprocess(self, feed={}, fetch=[]):
         reader = ImageReader()
-        if "image" not in feed:
-            raise ("feed data error!")
-        if isinstance(feed["image"], list):
-            feed_batch = []
-            for image in feed["image"]:
-                sample = base64.b64decode(image)
-                img = reader.process_image(sample)
-                res_feed = {}
-                res_feed["image"] = img
-                feed_batch.append(res_feed)
-            return feed_batch, fetch
-        else:
-            sample = base64.b64decode(feed["image"])
+        feed_batch = []
+        for ins in feed:
+            if "image" not in ins:
+                raise ("feed data error!")
+            sample = base64.b64decode(ins["image"])
             img = reader.process_image(sample)
-            res_feed = {}
-            res_feed["image"] = img
-            return res_feed, fetch
+            feed_batch.append({"image": img})
+        return feed_batch, fetch
 
 
 image_service = ImageService(name="image")

python/examples/imagenet/image_classification_service_gpu.py

@@ -23,24 +23,14 @@ from paddle_serving_server_gpu.web_service import WebService
 class ImageService(WebService):
     def preprocess(self, feed={}, fetch=[]):
         reader = ImageReader()
-        if "image" not in feed:
-            raise ("feed data error!")
-        print(type(feed["image"]), isinstance(feed["image"], list))
-        if isinstance(feed["image"], list):
-            feed_batch = []
-            for image in feed["image"]:
-                sample = base64.b64decode(image)
-                img = reader.process_image(sample)
-                res_feed = {}
-                res_feed["image"] = img
-                feed_batch.append(res_feed)
-            return feed_batch, fetch
-        else:
-            sample = base64.b64decode(feed["image"])
+        feed_batch = []
+        for ins in feed:
+            if "image" not in ins:
+                raise ("feed data error!")
+            sample = base64.b64decode(ins["image"])
             img = reader.process_image(sample)
-            res_feed = {}
-            res_feed["image"] = img
-            return res_feed, fetch
+            feed_batch.append({"image": img})
+        return feed_batch, fetch
 
 
 image_service = ImageService(name="image")

python/examples/imdb/text_classify_service.py

@@ -26,10 +26,9 @@ class IMDBService(WebService):
         self.dataset.load_resource(args["dict_file_path"])
 
     def preprocess(self, feed={}, fetch=[]):
-        if "words" not in feed:
-            exit(-1)
-        res_feed = {}
-        res_feed["words"] = self.dataset.get_words_only(feed["words"])
+        res_feed = [{
+            "words": self.dataset.get_words_only(ins["words"])
+        } for ins in feed]
         return res_feed, fetch
 
 

python/examples/lac/lac_web_service.py

@@ -22,15 +22,22 @@ class LACService(WebService):
         self.reader = LACReader("lac_dict")
 
     def preprocess(self, feed={}, fetch=[]):
-        if "words" not in feed:
-            raise ("feed data error!")
-        feed_data = self.reader.process(feed["words"])
+        batch_feed = []
+        for ins in feed:
+            if "words" not in ins:
+                raise ("feed data error!")
+            feed_data = self.reader.process(ins["words"])
+            batch_feed.append({"words": feed_data})
         fetch = ["crf_decode"]
-        return {"words": feed_data}, fetch
+        return batch_feed, fetch
 
     def postprocess(self, feed={}, fetch=[], fetch_map={}):
-        segs = self.reader.parse_result(feed["words"], fetch_map["crf_decode"])
-        return {"word_seg": "|".join(segs)}
+        ret = []
+        for idx, ins in enumerate(feed):
+            segs = self.reader.parse_result(ins["words"],
+                                            fetch_map[idx]["crf_decode"])
+            ret.append({"word_seg": "|".join(segs)})
+        return ret
 
 
 lac_service = LACService(name="lac")

python/examples/senta/senta_web_service.py

@@ -87,7 +87,7 @@ class SentaService(WebService):
         if self.show:
             print("---- senta reader ----")
             print("feed_data", feed_data)
-        return {"words": feed_data}, fetch
+        return [{"words": feed_data}], fetch
 
 
 senta_service = SentaService(name="senta")