``` shell -> python -m paddle_serving_app.package -get_model resnet_v2_50_imagenet +> python -m paddle_serving_app.package --get_model resnet_v2_50_imagenet > tar -xzf resnet_v2_50_imagenet.tar.gz > python resnet50_imagenet_classify.py resnet50_serving_model & > curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"image": "https://paddle-serving.bj.bcebos.com/imagenet-example/daisy.jpg"}], "fetch": ["score"]}' http://127.0.0.1:9292/image/prediction @@ -111,9 +111,9 @@ python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --po | `port` | int | `9292` | Exposed port of current service to users| | `name` | str | `""` | Service name, can be used to generate HTTP request url | | `model` | str | `""` | Path of paddle model directory to be served | -| `mem_optim` | bool | `False` | Enable memory / graphic memory optimization | -| `ir_optim` | bool | `False` | Enable analysis and optimization of calculation graph | -| `use_mkl` (Only for cpu version) | bool | `False` | Run inference with MKL | +| `mem_optim` | - | - | Enable memory / graphic memory optimization | +| `ir_optim` | - | - | Enable analysis and optimization of calculation graph | +| `use_mkl` (Only for cpu version) | - | - | Run inference with MKL | Here, we use `curl` to send a HTTP POST request to the service we just started. Users can use any python library to send HTTP POST as well, e.g, [requests](https://requests.readthedocs.io/en/master/). @@ -170,13 +170,13 @@ Here, `client.predict` function has two arguments. `feed` is a `python dict` wit ### About Efficiency - [How to profile Paddle Serving latency?](python/examples/util) -- [How to optimize performance?(Chinese)](doc/PERFORMANCE_OPTIM_CN.md) +- [How to optimize performance?](doc/PERFORMANCE_OPTIM.md) - [Deploy multi-services on one GPU(Chinese)](doc/MULTI_SERVICE_ON_ONE_GPU_CN.md) - [CPU Benchmarks(Chinese)](doc/BENCHMARKING.md) - [GPU Benchmarks(Chinese)](doc/GPU_BENCHMARKING.md) ### FAQ -- [FAQ(Chinese)](doc/deprecated/FAQ.md) +- [FAQ(Chinese)](doc/FAQ.md) ### Design diff --git a/README_CN.md b/README_CN.md index 05d3ad210..7a42e6cd9 100644 --- a/README_CN.md +++ b/README_CN.md @@ -62,9 +62,9 @@ Paddle Serving安装包支持Centos 6/7和Ubuntu 16/18，或者您可以使用HT
``` shell -> python -m paddle_serving_app.package -get_model resnet_v2_50_imagenet +> python -m paddle_serving_app.package --get_model resnet_v2_50_imagenet > tar -xzf resnet_v2_50_imagenet.tar.gz > python resnet50_imagenet_classify.py resnet50_serving_model & > curl -H "Content-Type:application/json" -X POST -d '{"feed":[{"image": "https://paddle-serving.bj.bcebos.com/imagenet-example/daisy.jpg"}], "fetch": ["score"]}' http://127.0.0.1:9292/image/prediction @@ -115,9 +115,9 @@ python -m paddle_serving_server.serve --model uci_housing_model --thread 10 --po | `port` | int | `9292` | Exposed port of current service to users| | `name` | str | `""` | Service name, can be used to generate HTTP request url | | `model` | str | `""` | Path of paddle model directory to be served | -| `mem_optim` | bool | `False` | Enable memory optimization | -| `ir_optim` | bool | `False` | Enable analysis and optimization of calculation graph | -| `use_mkl` (Only for cpu version) | bool | `False` | Run inference with MKL | +| `mem_optim` | - | - | Enable memory optimization | +| `ir_optim` | - | - | Enable analysis and optimization of calculation graph | +| `use_mkl` (Only for cpu version) | - | - | Run inference with MKL | 我们使用 `curl` 命令来发送HTTP POST请求给刚刚启动的服务。用户也可以调用python库来发送HTTP POST请求，请参考英文文档 [requests](https://requests.readthedocs.io/en/master/)。 @@ -181,7 +181,7 @@ print(fetch_map) - [GPU版Benchmarks](doc/GPU_BENCHMARKING.md) ### FAQ -- [常见问答](doc/deprecated/FAQ.md) +- [常见问答](doc/FAQ.md) ### 设计文档 - [Paddle Serving设计文档](doc/DESIGN_DOC_CN.md) diff --git a/doc/BERT_10_MINS.md b/doc/BERT_10_MINS.md index 71f6f065f..53e51768d 100644 --- a/doc/BERT_10_MINS.md +++ b/doc/BERT_10_MINS.md @@ -59,7 +59,7 @@ the script of client side bert_client.py is as follow: import os import sys from paddle_serving_client import Client -from paddle_serving_app import ChineseBertReader +from paddle_serving_app.reader import ChineseBertReader reader = ChineseBertReader() fetch = ["pooled_output"] diff --git a/doc/BERT_10_MINS_CN.md b/doc/BERT_10_MINS_CN.md index b7a5180da..e4904d86b 100644 --- a/doc/BERT_10_MINS_CN.md +++ b/doc/BERT_10_MINS_CN.md @@ -52,7 +52,7 @@ pip install paddle_serving_app ``` python import sys from paddle_serving_client import Client -from paddle_serving_app import ChineseBertReader +from paddle_serving_app.reader import ChineseBertReader reader = ChineseBertReader() fetch = ["pooled_output"] diff --git a/doc/FAQ.md b/doc/FAQ.md new file mode 100644 index 000000000..3bdd2dfd4 --- /dev/null +++ b/doc/FAQ.md @@ -0,0 +1,15 @@ +# FAQ + +- Q：如何调整RPC服务的等待时间，避免超时？ + + A：使用set_rpc_timeout_ms设置更长的等待时间，单位为毫秒，默认时间为20秒。 + + 示例： + ``` + from paddle_serving_client import Client + + client = Client() + client.load_client_config(sys.argv[1]) + client.set_rpc_timeout_ms(100000) + client.connect(["127.0.0.1:9393"]) + ``` diff --git a/doc/IMDB_GO_CLIENT_CN.md b/doc/IMDB_GO_CLIENT_CN.md index 86355bd53..5067d1ef7 100644 --- a/doc/IMDB_GO_CLIENT_CN.md +++ b/doc/IMDB_GO_CLIENT_CN.md @@ -99,7 +99,7 @@ func main() { ### 基于IMDB测试集的预测 ```python -go run imdb_client.go serving_client_conf / serving_client_conf.stream.prototxt test.data> result +go run imdb_client.go serving_client_conf/serving_client_conf.stream.prototxt test.data> result ``` ### 计算精度 diff --git a/doc/PERFORMANCE_OPTIM.md b/doc/PERFORMANCE_OPTIM.md index eae128c40..651be1c13 100644 --- a/doc/PERFORMANCE_OPTIM.md +++ b/doc/PERFORMANCE_OPTIM.md @@ -16,5 +16,5 @@ Parameters for performance optimization: | Parameters | Type | Default | Description | | ---------- | ---- | ------- | ------------------------------------------------------------ | -| mem_optim | bool | False | Enable memory / graphic memory optimization | -| ir_optim | bool | Fasle | Enable analysis and optimization of calculation graph,including OP fusion, etc | +| mem_optim | - | - | Enable memory / graphic memory optimization | +| ir_optim | - | - | Enable analysis and optimization of calculation graph,including OP fusion, etc | diff --git a/doc/PERFORMANCE_OPTIM_CN.md b/doc/PERFORMANCE_OPTIM_CN.md index 1a2c38409..c35ea7a11 100644 --- a/doc/PERFORMANCE_OPTIM_CN.md +++ b/doc/PERFORMANCE_OPTIM_CN.md @@ -16,5 +16,5 @@ | 参数 | 类型 | 默认值 | 含义 | | --------- | ---- | ------ | -------------------------------- | -| mem_optim | bool | False | 开启内存/显存优化 | -| ir_optim | bool | Fasle | 开启计算图分析优化，包括OP融合等 | +| mem_optim | - | - | 开启内存/显存优化 | +| ir_optim | - | - | 开启计算图分析优化，包括OP融合等 | diff --git a/python/paddle_serving_server/serve.py b/python/paddle_serving_server/serve.py index 894b0c5b1..e75240dfa 100644 --- a/python/paddle_serving_server/serve.py +++ b/python/paddle_serving_server/serve.py @@ -40,10 +40,14 @@ def parse_args(): # pylint: disable=doc-string-missing parser.add_argument( "--device", type=str, default="cpu", help="Type of device") parser.add_argument( - "--mem_optim", type=bool, default=False, help="Memory optimize") + "--mem_optim", + default=False, + action="store_true", + help="Memory optimize") parser.add_argument( - "--ir_optim", type=bool, default=False, help="Graph optimize") - parser.add_argument("--use_mkl", type=bool, default=False, help="Use MKL") + "--ir_optim", default=False, action="store_true", help="Graph optimize") + parser.add_argument( + "--use_mkl", default=False, action="store_true", help="Use MKL") parser.add_argument( "--max_body_size", type=int, diff --git a/python/paddle_serving_server_gpu/__init__.py b/python/paddle_serving_server_gpu/__init__.py index e40c0fa48..ace490553 100644 --- a/python/paddle_serving_server_gpu/__init__.py +++ b/python/paddle_serving_server_gpu/__init__.py @@ -47,9 +47,12 @@ def serve_args(): parser.add_argument( "--name", type=str, default="None", help="Default service name") parser.add_argument( - "--mem_optim", type=bool, default=False, help="Memory optimize") + "--mem_optim", + default=False, + action="store_true", + help="Memory optimize") parser.add_argument( - "--ir_optim", type=bool, default=False, help="Graph optimize") + "--ir_optim", default=False, action="store_true", help="Graph optimize") parser.add_argument( "--max_body_size", type=int,