From b598b6cee23cd395e360eeee583de5aac7f6dbf7 Mon Sep 17 00:00:00 2001 From: zhangjun Date: Thu, 22 Apr 2021 16:30:23 +0000 Subject: [PATCH] add resnet50 int8 example --- .../examples/low_precision/resnet50/README.md | 28 +++++++++++++++ .../low_precision/resnet50/README_CN.md | 27 +++++++++++++++ .../examples/low_precision/resnet50/daisy.jpg | Bin 0 -> 39696 bytes .../low_precision/resnet50/resnet50_client.py | 32 ++++++++++++++++++ 4 files changed, 87 insertions(+) create mode 100644 python/examples/low_precision/resnet50/README.md create mode 100644 python/examples/low_precision/resnet50/README_CN.md create mode 100644 python/examples/low_precision/resnet50/daisy.jpg create mode 100644 python/examples/low_precision/resnet50/resnet50_client.py diff --git a/python/examples/low_precision/resnet50/README.md b/python/examples/low_precision/resnet50/README.md new file mode 100644 index 00000000..9e1ff16c --- /dev/null +++ b/python/examples/low_precision/resnet50/README.md @@ -0,0 +1,28 @@ +# resnet50 int8 example +(English|[简体中文](./README_CN.md)) + +## Obtain the quantized model through PaddleSlim tool +Train the low-precision models please refer to [PaddleSlim](https://paddleslim.readthedocs.io/zh_CN/latest/tutorials/quant/overview.html). + +## Deploy the quantized model from PaddleSlim using Paddle Serving with Nvidia TensorRT int8 mode + +Firstly, download the [Resnet50 int8 model](https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz) and convert to Paddle Serving's saved model。 +``` +wget https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz +tar zxvf ResNet50_quant.tar.gz + +python -m paddle_serving_client.convert --dirname ResNet50_quant +``` +Start RPC service, specify the GPU id and precision mode +``` +python -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 +``` +Request the serving service with Client +``` +python resnet50_client.py +``` + +## Reference +* [PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim) +* [Deploy the quantized model Using Paddle Inference on Intel CPU](https://paddle-inference.readthedocs.io/en/latest/optimize/paddle_x86_cpu_int8.html) +* [Deploy the quantized model Using Paddle Inference on Nvidia GPU](https://paddle-inference.readthedocs.io/en/latest/optimize/paddle_trt.html) diff --git a/python/examples/low_precision/resnet50/README_CN.md b/python/examples/low_precision/resnet50/README_CN.md new file mode 100644 index 00000000..1c1a3be1 --- /dev/null +++ b/python/examples/low_precision/resnet50/README_CN.md @@ -0,0 +1,27 @@ +# resnet50 int8示例 +(简体中文|[English](./README.md)) + +## 通过PaddleSlim量化生成低精度模型 +详细见[PaddleSlim量化](https://paddleslim.readthedocs.io/zh_CN/latest/tutorials/quant/overview.html) + +## 使用TensorRT int8加载PaddleSlim Int8量化模型进行部署 +首先下载Resnet50 [PaddleSlim量化模型](https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz),并转换为Paddle Serving支持的部署模型格式。 +``` +wget https://paddle-inference-dist.bj.bcebos.com/inference_demo/python/resnet50/ResNet50_quant.tar.gz +tar zxvf ResNet50_quant.tar.gz + +python -m paddle_serving_client.convert --dirname ResNet50_quant +``` +启动rpc服务, 设定所选GPU id、部署模型精度 +``` +python -m paddle_serving_server.serve --model serving_server --port 9393 --gpu_ids 0 --use_trt --precision int8 +``` +使用client进行请求 +``` +python resnet50_client.py +``` + +## 参考文档 +* [PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim) +* PaddleInference Intel CPU部署量化模型[文档](https://paddle-inference.readthedocs.io/en/latest/optimize/paddle_x86_cpu_int8.html) +* PaddleInference NV GPU部署量化模型[文档](https://paddle-inference.readthedocs.io/en/latest/optimize/paddle_trt.html) diff --git a/python/examples/low_precision/resnet50/daisy.jpg b/python/examples/low_precision/resnet50/daisy.jpg new file mode 100644 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All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# 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 paddle_serving_client import Client +from paddle_serving_app.reader import Sequential, File2Image, Resize, CenterCrop +from paddle_serving_app.reader import RGB2BGR, Transpose, Div, Normalize + +client = Client() +client.load_client_config( + "serving_client/serving_client_conf.prototxt") +client.connect(["127.0.0.1:9303"]) + +seq = Sequential([ + File2Image(), Resize(256), CenterCrop(224), RGB2BGR(), Transpose((2, 0, 1)), + Div(255), Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225], True) +]) + +image_file = "daisy.jpg" +img = seq(image_file) +fetch_map = client.predict(feed={"image": img}, fetch=["save_infer_model/scale_0.tmp_0"]) +print(fetch_map["save_infer_model/scale_0.tmp_0"].reshape(-1)) -- GitLab