diff --git a/README.md b/README.md index 297a6cf7901d0f18418b573a622a55f33bbed2cc..8aa899a3d1db797ea1a38476e5d56c425501f23e 100644 --- a/README.md +++ b/README.md @@ -154,10 +154,87 @@ curl -H "Content-Type:application/json" -X POST -d '{"url": "https://paddle-serv {"label":"daisy","prob":0.9341403245925903} ``` +

More Demos

+| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | Bert-Base-Baike | +| URL | [https://paddle-serving.bj.bcebos.com/bert_example/bert_seq128.tar.gz](https://paddle-serving.bj.bcebos.com/bert_example%2Fbert_seq128.tar.gz) | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/bert | +| Description | Get semantic representation from a Chinese Sentence | +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | Resnet50-Imagenet | +| URL | [https://paddle-serving.bj.bcebos.com/imagenet-example/ResNet50_vd.tar.gz](https://paddle-serving.bj.bcebos.com/imagenet-example%2FResNet50_vd.tar.gz) | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/imagenet | +| Description | Get image semantic representation from an image | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | Resnet101-Imagenet | +| URL | https://paddle-serving.bj.bcebos.com/imagenet-example/ResNet101_vd.tar.gz | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/imagenet | +| Description | Get image semantic representation from an image | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | CNN-IMDB | +| URL | https://paddle-serving.bj.bcebos.com/imdb-demo/imdb_model.tar.gz | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/imdb | +| Description | Get category probability from an English Sentence | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | LSTM-IMDB | +| URL | https://paddle-serving.bj.bcebos.com/imdb-demo/imdb_model.tar.gz | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/imdb | +| Description | Get category probability from an English Sentence | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | BOW-IMDB | +| URL | https://paddle-serving.bj.bcebos.com/imdb-demo/imdb_model.tar.gz | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/imdb | +| Description | Get category probability from an English Sentence | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | Jieba-LAC | +| URL | https://paddle-serving.bj.bcebos.com/lac/lac_model.tar.gz | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/lac | +| Description | Get word segmentation from a Chinese Sentence | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | DNN-CTR | +| URL | None(Get model by [local_train.py](./python/examples/criteo_ctr/local_train.py)) | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/criteo_ctr | +| Description | Get click probability from a feature vector of item | + + + +| Key | Value | +| :----------------- | :----------------------------------------------------------- | +| Model Name | DNN-CTR(with cube) | +| URL | None(Get model by [local_train.py](python/examples/criteo_ctr_with_cube/local_train.py)) | +| Client/Server Code | https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/criteo_ctr_with_cube | +| Description | Get click probability from a feature vector of item | +

Document

### New to Paddle Serving diff --git a/doc/RUN_IN_DOCKER.md b/doc/RUN_IN_DOCKER.md index edfd914123b2262b36e85552b179a0e412b68413..972de2d951e602d025fb5fcb8b3229dcc300f696 100644 --- a/doc/RUN_IN_DOCKER.md +++ b/doc/RUN_IN_DOCKER.md @@ -147,7 +147,7 @@ tar -xzf uci_housing.tar.gz Running on the Server side (inside the container): ```bash - python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --name uci + python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --name uci --gpu_ids 0 ``` Running on the Client side (inside or outside the container): @@ -161,7 +161,7 @@ tar -xzf uci_housing.tar.gz Running on the Server side (inside the container): ```bash - python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 + python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --gpu_ids 0 ``` Running following Python code on the Client side (inside or outside the container, The `paddle-serving-client` package needs to be installed): diff --git a/doc/RUN_IN_DOCKER_CN.md b/doc/RUN_IN_DOCKER_CN.md index 47914a2fdd6aa78956b783ab813edb5d3a587b7d..17bdd30adbcbecd971904011208fe01d1d08f5ba 100644 --- a/doc/RUN_IN_DOCKER_CN.md +++ b/doc/RUN_IN_DOCKER_CN.md @@ -145,7 +145,7 @@ tar -xzf uci_housing.tar.gz 在Server端（容器内）运行： ```bash - python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --name uci + python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --name uci --gpu_ids 0 ``` 在Client端（容器内或容器外）运行： @@ -159,7 +159,7 @@ tar -xzf uci_housing.tar.gz 在Server端（容器内）运行： ```bash - python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 + python -m paddle_serving_server_gpu.serve --model uci_housing_model --thread 10 --port 9292 --gpu_ids 0 ``` 在Client端（容器内或容器外，需要安装`paddle-serving-client`包）运行下面Python代码： diff --git a/python/examples/bert/benchmark_batch.py b/python/examples/bert/benchmark_batch.py index 265521d484259b0e6ea2b182dbf61e2a5cf43b8d..872799e64ea599554e42264c37ab5f574c0acb13 100644 --- a/python/examples/bert/benchmark_batch.py +++ b/python/examples/bert/benchmark_batch.py @@ -57,7 +57,8 @@ def single_func(idx, resource): os.getpid(), int(round(b_start * 1000000)), int(round(b_end * 1000000)))) - result = client.predict(feed_batch=feed_batch, fetch=fetch) + result = client.batch_predict( + feed_batch=feed_batch, fetch=fetch) else: print("unsupport batch size {}".format(args.batch_size)) diff --git a/python/examples/criteo_ctr/test_client.py b/python/examples/criteo_ctr/test_client.py index 9b3681c4117d123abd490668f44e43ab9f1e855f..d53c5541c36f4eb52618e3498eda571dd2bcab53 100644 --- a/python/examples/criteo_ctr/test_client.py +++ b/python/examples/criteo_ctr/test_client.py @@ -21,6 +21,10 @@ import time import criteo_reader as criteo from paddle_serving_client.metric import auc +import sys + +py_version = sys.version_info[0] + client = Client() client.load_client_config(sys.argv[1]) client.connect(["127.0.0.1:9292"]) @@ -39,7 +43,10 @@ label_list = [] prob_list = [] start = time.time() for ei in range(1000): - data = reader().next() + if py_version == 2: + data = reader().next() + else: + data = reader().__next__() feed_dict = {} for i in range(1, 27): feed_dict["sparse_{}".format(i - 1)] = data[0][i] diff --git a/python/examples/imagenet/image_http_client.py b/python/examples/imagenet/image_http_client.py index c567b9003bfe87f9ddd20c3553b9e2d400bce4b9..2a2e9ea20d7e428cfe42393e2fee60035c33283d 100644 --- a/python/examples/imagenet/image_http_client.py +++ b/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): - image = base64.b64encode(open(image_path).read()) + 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"}) @@ -28,18 +34,8 @@ 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_path = "./data/n01440764_10026.JPEG" image_list = os.listdir("./image_data/n01440764/") start = time.time() for img in image_list: diff --git a/python/examples/imagenet/image_rpc_client.py b/python/examples/imagenet/image_rpc_client.py index 2367f509cece4d37d61d4a2ff2c2bfb831112e5a..76f3a043474bf75e1e96a44f18ac7dfe3da11f78 100644 --- a/python/examples/imagenet/image_rpc_client.py +++ b/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) diff --git a/python/examples/imdb/imdb_reader.py b/python/examples/imdb/imdb_reader.py index 38a46c5cf3cc3d7216c47c290876951e99253115..a4ef3e163a50b0dc244ac2653df1e38d7f91699b 100644 --- a/python/examples/imdb/imdb_reader.py +++ b/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 - with open(dictfile) as f: - for line in f: - self._vocab[line.strip()] = wid - wid += 1 + 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]) diff --git a/python/paddle_serving_client/metric/__init__.py b/python/paddle_serving_client/metric/__init__.py index 4f173887755e5aef5c6917fa604012cf0c1d86f0..245e740dae2e713fde3237c26d6815b4528f90d7 100644 --- a/python/paddle_serving_client/metric/__init__.py +++ b/python/paddle_serving_client/metric/__init__.py @@ -11,5 +11,5 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -from auc import auc -from acc import acc +from .auc import auc +from .acc import acc diff --git a/python/paddle_serving_server_gpu/serve.py b/python/paddle_serving_server_gpu/serve.py index 9c8d10e4b36a7830aed25996a309cb4163ca126c..2cce4d4b1615584fc02aba4d70e1928083ddde62 100644 --- a/python/paddle_serving_server_gpu/serve.py +++ b/python/paddle_serving_server_gpu/serve.py @@ -71,7 +71,7 @@ def start_multi_card(args): # pylint: disable=doc-string-missing else: gpus = args.gpu_ids.split(",") if len(gpus) <= 0: - start_gpu_card_model(-1, args) + start_gpu_card_model(-1, 0, args) else: gpu_processes = [] for i, gpu_id in enumerate(gpus): diff --git a/python/setup.py.client.in b/python/setup.py.client.in index 86b3c331babccd06bdc6e206866a1c43da7b27d7..381fb2a8853cc4d5494e3eac520ab183db6eab09 100644 --- a/python/setup.py.client.in +++ b/python/setup.py.client.in @@ -18,6 +18,7 @@ from __future__ import print_function import platform import os +import sys from setuptools import setup, Distribution, Extension from setuptools import find_packages @@ -25,6 +26,7 @@ from setuptools import setup from paddle_serving_client.version import serving_client_version from pkg_resources import DistributionNotFound, get_distribution +py_version = sys.version_info[0] def python_version(): return [int(v) for v in platform.python_version().split(".")] @@ -37,8 +39,9 @@ def find_package(pkgname): return False def copy_lib(): + lib_list = ['libpython2.7.so.1.0', 'libssl.so.10', 'libcrypto.so.10'] if py_version == 2 else ['libpython3.6m.so.1.0', 'libssl.so.10', 'libcrypto.so.10'] os.popen('mkdir -p paddle_serving_client/lib') - for lib in ['libpython2.7.so.1.0', 'libssl.so.10', 'libcrypto.so.10']: + for lib in lib_list: r = os.popen('whereis {}'.format(lib)) text = r.read() os.popen('cp {} ./paddle_serving_client/lib'.format(text.strip().split(' ')[1]))