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FastDeploy/tools/README.md
yunyaoXYY 8dec2115d5 [Quantization] Remove extra requirements for fd-auto-compress package (#582) 
* Add PaddleOCR Support

* Add PaddleOCR Support

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Support

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Supports

* Add PaddleOCRv3 Suport

* Fix Rec diff

* Remove useless functions

* Remove useless comments

* Add PaddleOCRv2 Support

* Add PaddleOCRv3 & PaddleOCRv2 Support

* remove useless parameters

* Add utils of sorting det boxes

* Fix code naming convention

* Fix code naming convention

* Fix code naming convention

* Fix bug in the Classify process

* Imporve OCR Readme

* Fix diff in Cls model

* Update Model Download Link in Readme

* Fix diff in PPOCRv2

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* Add readme for OCRResult

* Improve OCR readme

* Add OCRResult readme

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* Improve OCR readme

* Add Model Quantization Demo

* Fix Model Quantization Readme

* Fix Model Quantization Readme

* Add the function to do PTQ quantization

* Improve quant tools readme

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* Add PaddleInference-GPU for OCR Rec model

* Add QAT method to fastdeploy-quantization tool

* Remove examples/slim for now

* Move configs folder

* Add Quantization Support for Classification Model

* Imporve ways of importing preprocess

* Upload YOLO Benchmark on readme

* Upload YOLO Benchmark on readme

* Upload YOLO Benchmark on readme

* Improve Quantization configs and readme

* Add support for multi-inputs model

* Add backends and params file for YOLOv7

* Add quantized model deployment support for YOLO series

* Fix YOLOv5 quantize readme

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* Fix bug, change Fronted to ModelFormat

* Change Fronted to ModelFormat

* Add examples to deploy quantized paddleclas models

* Fix readme

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* Add quantize Readme

* Modify readme of quantization tools

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* Improve quantization tools readme

* Improve quantization readme

* Improve PaddleClas quantized model deployment  readme

* Add PPYOLOE-l quantized deployment examples

* Improve quantization tools readme

* Improve Quantize Readme

* Fix conflicts

* Fix conflicts

* improve readme

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* Improve quantization tools and readme

* Add quantized deployment examples for PaddleSeg model

* Fix cpp readme

* Fix memory leak of reader_wrapper function

* Fix model file name in PaddleClas quantization examples

* Update Runtime and E2E benchmark

* Update Runtime and E2E benchmark

* Rename quantization tools to auto compression tools

* Remove PPYOLOE data when deployed on MKLDNN

* Fix readme

* Support PPYOLOE with OR without NMS and update readme

* Update Readme

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* Update configs and readme

* Add Paddle-TensorRT backend in quantized model deploy examples

* Support PPYOLOE+ series

* Add reused_input_tensors for PPYOLOE

* Improve fastdeploy tools usage

* improve fastdeploy tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* remove modify

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Improve fastdeploy auto compression tool

* Remove extra requirements for fd-auto-compress package
2022-11-14 16:39:31 +08:00

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FastDeploy 工具包

FastDeploy提供了一系列高效易用的工具优化部署体验, 提升推理性能. 例如, FastDeploy基于PaddleSlim的Auto Compression Toolkit(ACT), 给用户提供了一键模型自动化压缩的工具, 用户可以轻松地通过一行命令对模型进行自动化压缩, 并在FastDeploy上部署压缩后的模型, 提升推理速度. 本文档将以FastDeploy一键模型自动化压缩工具为例, 介绍如何安装此工具, 并提供相应的使用文档.

FastDeploy一键模型自动化压缩工具

环境准备

1.用户参考PaddlePaddle官网, 安装develop版本

https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html

2.安装PaddleSlim develop版本

git clone https://github.com/PaddlePaddle/PaddleSlim.git & cd PaddleSlim
python setup.py install

3.安装fd-auto-compress一键模型自动化压缩工具

# 通过pip安装fd-auto-compress.
# FastDeploy的python包已包含此工具, 不需重复安装.
pip install fd-auto-compress==0.0.1

# 在当前目录执行以下命令
python setup.py install

一键模型自动化压缩工具的使用

按照以上步骤成功安装后,即可使用FastDeploy一键模型自动化压缩工具, 示例如下.

fastdeploy --auto_compress --config_path=./configs/detection/yolov5s_quant.yaml --method='PTQ' --save_dir='./yolov5s_ptq_model/'

详细使用文档请参考FastDeploy一键模型自动化压缩工具

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