fix for iPipe2

python/examples/bert/bert_client.py

@@ -34,7 +34,4 @@ for line in sys.stdin:
         feed_dict[key] = np.array(feed_dict[key]).reshape((128, 1))
     #print(feed_dict)
     result = client.predict(feed=feed_dict, fetch=fetch)
-    print(result)
-print(result)
-print(result)
 print(result)

python/examples/criteo_ctr/test_client.py

@@ -20,7 +20,7 @@ import os
 import time
 import criteo_reader as criteo
 from paddle_serving_client.metric import auc
-
+import numpy as np
 import sys
 
 py_version = sys.version_info[0]
@@ -49,7 +49,8 @@ for ei in range(1000):
         data = reader().__next__()
     feed_dict = {}
     for i in range(1, 27):
-        feed_dict["sparse_{}".format(i - 1)] = data[0][i]
+        feed_dict["sparse_{}".format(i - 1)] = np.array(data[0][i]).reshape(-1)
+        feed_dict["sparse_{}.lod".format(i - 1)] = [0, len(data[0][i])]
     fetch_map = client.predict(feed=feed_dict, fetch=["prob"])
 end = time.time()
 print(end - start)

python/examples/faster_rcnn_model/test_client.py

@@ -36,6 +36,6 @@ fetch_map = client.predict(
         "im_info": np.array(list(im.shape[1:]) + [1.0]),
         "im_shape": np.array(list(im.shape[1:]) + [1.0])
     },
-    fetch=["multiclass_nms"])
+    fetch=["multiclass_nms"], batch=False)
 fetch_map["image"] = sys.argv[3]
 postprocess(fetch_map)

python/examples/fit_a_line/test_client.py

@@ -28,10 +28,8 @@ test_reader = paddle.batch(
 
 for data in test_reader():
     import numpy as np
-    new_data = np.zeros((2, 1, 13)).astype("float32")
+    new_data = np.zeros((1, 1, 13)).astype("float32")
     new_data[0] = data[0][0]
-    new_data[1] = data[0][0]
-    print(new_data)
     fetch_map = client.predict(
         feed={"x": new_data}, fetch=["price"], batch=True)
     print("{} {}".format(fetch_map["price"][0], data[0][1][0]))

python/examples/imdb/benchmark.py

@@ -17,6 +17,7 @@ import os
 import sys
 import time
 import requests
+import numpy as np
 from paddle_serving_app.reader import IMDBDataset
 from paddle_serving_client import Client
 from paddle_serving_client.utils import MultiThreadRunner
@@ -47,11 +48,13 @@ def single_func(idx, resource):
         for i in range(1000):
             if args.batch_size >= 1:
                 feed_batch = []
+                feed = {"words": [], "words.lod":[0]}
                 for bi in range(args.batch_size):
-                    word_ids, label = imdb_dataset.get_words_and_label(dataset[
-                        bi])
-                    feed_batch.append({"words": word_ids})
-                result = client.predict(feed=feed_batch, fetch=["prediction"])
+                    word_ids, label = imdb_dataset.get_words_and_label(dataset[bi])
+                    feed["words.lod"].append(feed["words.lod"][-1] + len(word_ids))
+                    feed["words"].extend(word_ids)
+                feed["words"] = np.array(feed["words"]).reshape(len(feed["words"]), 1)
+                result = client.predict(feed=feed, fetch=["prediction"], batch=True)
                 if result is None:
                     raise ("predict failed.")
             else:

python/examples/pipeline/imdb_model_ensemble/config.yml

@@ -10,5 +10,13 @@ op:
         concurrency: 2
         remote_service_conf:
             client_type: brpc
-            model_config: ocr_det_model
+            model_config: imdb_bow_model
             devices: ""
+            rpc_port : 9393 
+    cnn:
+        concurrency: 2
+        remote_service_conf:
+            client_type: brpc
+            model_config: imdb_cnn_model
+            devices: ""
+            rpc_port : 9292

python/examples/yolov4/test_client.py

@@ -35,6 +35,6 @@ fetch_map = client.predict(
         "image": im,
         "im_size": np.array(list(im.shape[1:])),
     },
-    fetch=["save_infer_model/scale_0.tmp_0"])
+    fetch=["save_infer_model/scale_0.tmp_0"], batch=False)
 fetch_map["image"] = sys.argv[1]
 postprocess(fetch_map)

python/pipeline/operator.py

@@ -835,8 +835,7 @@ class Op(object):
                     self.concurrency_idx = None
                     # init client
                     self.client = self.init_client(self._client_config,
-                                                   self._server_endpoints,
-                                                   self._fetch_names)
+                                                   self._server_endpoints)
                     # user defined
                     self.init_op()
                     self._succ_init_op = True
@@ -845,7 +844,7 @@ class Op(object):
             self.concurrency_idx = concurrency_idx
             # init client
             self.client = self.init_client(
-                self._client_config, self._server_endpoints, self._fetch_names)
+                self._client_config, self._server_endpoints)
             # user defined
             self.init_op()