diff --git a/python/examples/bert/bert_client.py b/python/examples/bert/bert_client.py index a6471c7d554f505c1f369787ef17855cb64541d9..d0f8b0aad19b78e6235a3dd0403f20324b4681b4 100644 --- a/python/examples/bert/bert_client.py +++ b/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) diff --git a/python/examples/criteo_ctr/test_client.py b/python/examples/criteo_ctr/test_client.py index 2beac850228291c49d56c1180365fdd8e627ffc0..ecb2fc376c0d3a8c7174c9f2ab093b25c8ac4791 100644 --- a/python/examples/criteo_ctr/test_client.py +++ b/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) diff --git a/python/examples/faster_rcnn_model/test_client.py b/python/examples/faster_rcnn_model/test_client.py index ce577a3c4396d33af33e45694a573f8b1cbcb52b..baa0be88e9f39db5457dda28cfc2c7176480e3bd 100755 --- a/python/examples/faster_rcnn_model/test_client.py +++ b/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) diff --git a/python/examples/fit_a_line/test_client.py b/python/examples/fit_a_line/test_client.py index 985a639945fab98c822ab79148af17d07ddfd47b..41a037decb6109337bebda4927eba4ea46121b87 100644 --- a/python/examples/fit_a_line/test_client.py +++ b/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])) diff --git a/python/examples/imdb/benchmark.py b/python/examples/imdb/benchmark.py index d226efbfbc5317db81039bc6a778498cdf853854..87e7bd22f11511b1b004036c2d048d827c1b12c1 100644 --- a/python/examples/imdb/benchmark.py +++ b/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: diff --git a/python/examples/pipeline/imdb_model_ensemble/config.yml b/python/examples/pipeline/imdb_model_ensemble/config.yml index a89f171f9847f5572d8e12f487ccd52138cbc48a..0853033fdccc643c459e19e2e0a573c3091ba9a9 100644 --- a/python/examples/pipeline/imdb_model_ensemble/config.yml +++ b/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 diff --git a/python/examples/yolov4/test_client.py b/python/examples/yolov4/test_client.py index 2616e55766192fca676e58efc4f0a2a3d634f1d3..8356a1685c8cea687eab7640432665618a8986c7 100644 --- a/python/examples/yolov4/test_client.py +++ b/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) diff --git a/python/pipeline/operator.py b/python/pipeline/operator.py index 866150dc7b2eb23c7ace13c6f91c6cfd058e59be..3af58a84ee0acd2b0161e37fe799ede5b053172e 100644 --- a/python/pipeline/operator.py +++ b/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()