diff --git a/python/examples/bert/bert_client.py b/python/examples/bert/bert_client.py index 8928d7c0a6459da57831dc3a82d55a5e3ff55b72..399ce32e594cab96275f4bc950c31dd153bdcd96 100644 --- a/python/examples/bert/bert_client.py +++ b/python/examples/bert/bert_client.py @@ -23,7 +23,7 @@ args = benchmark_args() reader = ChineseBertReader({"max_seq_len": 128}) fetch = ["pooled_output"] -endpoint_list = ["127.0.0.1:9292"] +endpoint_list = [':8861'] client = Client() client.load_client_config(args.model) client.connect(endpoint_list) @@ -35,3 +35,4 @@ for line in sys.stdin: #print(feed_dict) result = client.predict(feed=feed_dict, fetch=fetch) print(result) +print(result) diff --git a/python/examples/bert/bert_web_service.py b/python/examples/bert/bert_web_service.py index b1898b2cc0ee690dd075958944a56fed27dce29a..e3985c9da6c90bb349cc76cba038abd3fe9359c5 100644 --- a/python/examples/bert/bert_web_service.py +++ b/python/examples/bert/bert_web_service.py @@ -13,10 +13,11 @@ # See the License for the specific language governing permissions and # limitations under the License. # pylint: disable=doc-string-missing -from paddle_serving_server_gpu.web_service import WebService +from paddle_serving_server.web_service import WebService from paddle_serving_app.reader import ChineseBertReader import sys import os +import numpy as np class BertService(WebService): @@ -27,18 +28,20 @@ class BertService(WebService): }) def preprocess(self, feed=[], fetch=[]): - feed_res = [ - self.reader.process(ins["words"].encode("utf-8")) for ins in feed - ] + feed_res = [] + for ins in feed: + feed_dict = self.reader.process(ins["words"].encode("utf-8")) + for key in feed_dict.keys(): + feed_dict[key] = np.array(feed_dict[key]).reshape( + (1, len(feed_dict[key]), 1)) + feed_res.append(feed_dict) return feed_res, fetch bert_service = BertService(name="bert") bert_service.load() bert_service.load_model_config(sys.argv[1]) -gpu_ids = os.environ["CUDA_VISIBLE_DEVICES"] -bert_service.set_gpus(gpu_ids) bert_service.prepare_server( - workdir="workdir", port=int(sys.argv[2]), device="gpu") + workdir="workdir", port=int(sys.argv[2]), device="cpu") bert_service.run_rpc_service() bert_service.run_web_service() diff --git a/python/examples/faster_rcnn_model/test_client.py b/python/examples/faster_rcnn_model/test_client.py index ce577a3c4396d33af33e45694a573f8b1cbcb52b..847a5476ce817b8bc51eacc1de500a849a67abe7 100755 --- a/python/examples/faster_rcnn_model/test_client.py +++ b/python/examples/faster_rcnn_model/test_client.py @@ -27,7 +27,7 @@ postprocess = RCNNPostprocess("label_list.txt", "output") client = Client() client.load_client_config(sys.argv[1]) -client.connect(['127.0.0.1:9494']) +client.connect([':8870']) im = preprocess(sys.argv[3]) fetch_map = client.predict( diff --git a/python/examples/imagenet/resnet50_web_service.py b/python/examples/imagenet/resnet50_web_service.py index e7d1914973f2aeb58a912f7d85e35f85718d7a9b..faf2feabf997a3d3c85456955f48f0ae57951f9c 100644 --- a/python/examples/imagenet/resnet50_web_service.py +++ b/python/examples/imagenet/resnet50_web_service.py @@ -14,7 +14,7 @@ import sys from paddle_serving_client import Client from paddle_serving_app.reader import Sequential, URL2Image, Resize, CenterCrop, RGB2BGR, Transpose, Div, Normalize - +import numpy as np if len(sys.argv) != 4: print("python resnet50_web_service.py model device port") sys.exit(-1) @@ -47,7 +47,7 @@ class ImageService(WebService): if "image" not in ins: raise ("feed data error!") img = self.seq(ins["image"]) - feed_batch.append({"image": img}) + feed_batch.append({"image": img[np.newaxis, :]}) return feed_batch, fetch def postprocess(self, feed=[], fetch=[], fetch_map={}): diff --git a/python/examples/imdb/text_classify_service.py b/python/examples/imdb/text_classify_service.py index 24d7f33898fa4495be933630825e3ccddeafa3da..7b1f200e152da37c57cc8b2f7cd233531e5dd445 100755 --- a/python/examples/imdb/text_classify_service.py +++ b/python/examples/imdb/text_classify_service.py @@ -16,6 +16,7 @@ from paddle_serving_server.web_service import WebService from paddle_serving_app.reader import IMDBDataset import sys +import numpy as np class IMDBService(WebService): @@ -26,15 +27,15 @@ class IMDBService(WebService): self.dataset.load_resource(args["dict_file_path"]) def preprocess(self, feed={}, fetch=[]): - res_feed = [{ - "words": self.dataset.get_words_only(ins["words"]) - } for ins in feed] - - feed = { - "words": np.array(word_ids).reshape(word_len, 1), - "words.lod": [0, word_len] - } - return res_feed, fetch + feed_batch = [] + words_lod = [0] + for ins in feed: + words = self.dataset.get_words_only(ins["words"]) + words = np.array(words).reshape(len(words), 1) + words_lod.append(words_lod[-1] + len(words)) + feed_batch.append(words) + feed = {"words": np.concatenate(feed_batch), "words.lod": words_lod} + return feed, fetch imdb_service = IMDBService(name="imdb") diff --git a/python/examples/lac/lac_client.py b/python/examples/lac/lac_client.py index 568b08d8b3af86fd7aa7b20660aeb4acbf060e04..ab560532fe56e2c749f44ed4e1f86e43358d8706 100644 --- a/python/examples/lac/lac_client.py +++ b/python/examples/lac/lac_client.py @@ -22,8 +22,8 @@ import io import numpy as np client = Client() -client.load_client_config(sys.argv[1]) -client.connect(["127.0.0.1:9292"]) +client.connect([':8868']) +client.connect([':8868']) reader = LACReader() for line in sys.stdin: diff --git a/python/examples/lac/lac_web_service.py b/python/examples/lac/lac_web_service.py index bed89f54b626c0cce55767f8edacc3dd33f0104c..13b78f0adfc1d27dd1d1f792ca14ac436cc46571 100644 --- a/python/examples/lac/lac_web_service.py +++ b/python/examples/lac/lac_web_service.py @@ -15,6 +15,7 @@ from paddle_serving_server.web_service import WebService import sys from paddle_serving_app.reader import LACReader +import numpy as np class LACService(WebService): @@ -23,13 +24,17 @@ class LACService(WebService): def preprocess(self, feed={}, fetch=[]): feed_batch = [] + words_lod = [0] for ins in feed: if "words" not in ins: raise ("feed data error!") feed_data = self.reader.process(ins["words"]) - feed_batch.append({"words": feed_data}) + words_lod.append(words_lod[-1] + len(feed_data)) + feed_batch.append(np.array(feed_data).reshape(len(feed_data), 1)) + words = np.concatenate(feed_batch, axis=0) + fetch = ["crf_decode"] - return feed_batch, fetch + return {"words": words, "words.lod": words_lod}, fetch def postprocess(self, feed={}, fetch=[], fetch_map={}): batch_ret = [] diff --git a/python/examples/senta/senta_web_service.py b/python/examples/senta/senta_web_service.py index 25c880ef8877aed0f3f9d394d1780855130f365b..477064f3988a1c8152f77ce7fe068eb0a2181198 100644 --- a/python/examples/senta/senta_web_service.py +++ b/python/examples/senta/senta_web_service.py @@ -18,7 +18,7 @@ from paddle_serving_client import Client from paddle_serving_app.reader import LACReader, SentaReader import os import sys - +import numpy as np #senta_web_service.py from paddle_serving_server.web_service import WebService from paddle_serving_client import Client @@ -36,26 +36,42 @@ class SentaService(WebService): #定义senta模型预测服务的预处理，调用顺序：lac reader->lac模型预测->预测结果后处理->senta reader def preprocess(self, feed=[], fetch=[]): - feed_data = [{ - "words": self.lac_reader.process(x["words"]) - } for x in feed] - lac_result = self.lac_client.predict( - feed=feed_data, fetch=["crf_decode"]) feed_batch = [] + words_lod = [0] + for ins in feed: + if "words" not in ins: + raise ("feed data error!") + feed_data = self.lac_reader.process(ins["words"]) + words_lod.append(words_lod[-1] + len(feed_data)) + feed_batch.append(np.array(feed_data).reshape(len(feed_data), 1)) + words = np.concatenate(feed_batch, axis=0) + + lac_result = self.lac_client.predict( + feed={"words": words, + "words.lod": words_lod}, + fetch=["crf_decode"], + batch=True) result_lod = lac_result["crf_decode.lod"] + feed_batch = [] + words_lod = [0] for i in range(len(feed)): segs = self.lac_reader.parse_result( feed[i]["words"], lac_result["crf_decode"][result_lod[i]:result_lod[i + 1]]) feed_data = self.senta_reader.process(segs) - feed_batch.append({"words": feed_data}) - return feed_batch, fetch + feed_batch.append(np.array(feed_data).reshape(len(feed_data), 1)) + words_lod.append(words_lod[-1] + len(feed_data)) + return { + "words": np.concatenate(feed_batch), + "words.lod": words_lod + }, fetch senta_service = SentaService(name="senta") senta_service.load_model_config("senta_bilstm_model") senta_service.prepare_server(workdir="workdir") senta_service.init_lac_client( - lac_port=9300, lac_client_config="lac_model/serving_server_conf.prototxt") + lac_port=9300, + lac_client_config="lac/lac_model/serving_server_conf.prototxt") senta_service.run_rpc_service() senta_service.run_web_service()