OpenMMLab Model Deployment Framework
 
 
 
 
 
 
Go to file
Li Zhang 792c27b054
[Feature] Ascend backend (#747)
* add acl backend

* support dynamic batch size and dynamic image size

* add preliminary ascend backend

* support dtypes other than float

* support dynamic_dims in SDK

* fix dynamic batch size

* better error handling

* remove debug info

* [WIP] dynamic shape support

* fix static shape

* fix dynamic batch size

* add retinanet support

* fix dynamic image size

* fix dynamic image size

* fix dynamic dims

* fix dynamic dims

* simplify config files

* fix yolox support

* fix negative index

* support faster rcnn

* add seg config

* update benchmark

* fix onnx2ascend dynamic shape

* update docstring and benchmark

* add unit test, update documents

* fix wrapper

* fix ut

* fix for vit

* error handling

* context handling & multi-device support

* build with stub libraries

* add ci

* fix lint

* fix lint

* update doc ref

* fix typo

* down with `target_link_directories`

* setup python

* makedir

* fix ci

* fix ci

* remove verbose logs

* fix UBs

* export Error

* fix lint

* update checkenv

Co-authored-by: grimoire <yaoqian@sensetime.com>
2022-09-05 12:08:36 +08:00
.circleci [Enhancement] build sdk python api in standard-alone manner (#810) 2022-08-02 10:23:48 +08:00
.github [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
cmake [Feature] TorchScript SDK backend (#890) 2022-08-29 18:01:18 +08:00
configs [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
csrc/mmdeploy [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
demo feat(tools/deploy.py): support snpe (#789) 2022-08-01 11:08:55 +08:00
docker improvement(dockerfile): use make -j$(nporc) when build ncnn (#840) 2022-08-05 10:33:14 +08:00
docs [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
mmdeploy [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
requirements [Enhancement] Improve get_started documents and bump version to 0.7.0 (#813) 2022-08-04 14:33:27 +08:00
resources [Doc] How to write a customized TensorRT plugin (#290) 2022-08-22 14:00:28 +08:00
service/snpe feat(tools/deploy.py): support snpe (#789) 2022-08-01 11:08:55 +08:00
tests [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
third_party [Fix] Fix recent build problems (#544) 2022-06-06 11:19:34 +08:00
tools [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
.clang-format
.codespell_ignore.txt [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
.gitignore [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
.gitmodules [Fix] Fix recent build problems (#544) 2022-06-06 11:19:34 +08:00
.pre-commit-config.yaml feat(tools/deploy.py): support snpe (#789) 2022-08-01 11:08:55 +08:00
.pylintrc
.readthedocs.yml
CITATION.cff
CMakeLists.txt [Enhancement] Improve get_started documents and bump version to 0.7.0 (#813) 2022-08-04 14:33:27 +08:00
LICENSE
MANIFEST.in [Enhancement] Install Optimizer by setuptools (#690) 2022-07-25 13:04:27 +08:00
README.md [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
README_zh-CN.md [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
requirements.txt
setup.cfg [Feature] Ascend backend (#747) 2022-09-05 12:08:36 +08:00
setup.py Support setup on environment with no PyTorch (#843) 2022-08-01 17:52:02 +08:00

README.md

 
OpenMMLab website HOT      OpenMMLab platform TRY IT OUT
 

docs badge codecov license issue resolution open issues

English | 简体中文

Introduction

MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project.

Main features

Fully support OpenMMLab models

The currently supported codebases and models are as follows, and more will be included in the future

Multiple inference backends are available

Models can be exported and run in the following backends, and more will be compatible

ONNX Runtime TensorRT ppl.nn ncnn OpenVINO LibTorch snpe Ascend more
✔️ ✔️ ✔️ ✔️ ✔️ ✔️ ✔️ ✔️ benchmark

Efficient and scalable C/C++ SDK Framework

All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on

Documentation

Please read getting_started for the basic usage of MMDeploy. We also provide tutoials about:

Benchmark and Model zoo

You can find the supported models from here and their performance in the benchmark.

Contributing

We appreciate all contributions to MMDeploy. Please refer to CONTRIBUTING.md for the contributing guideline.

Acknowledgement

We would like to sincerely thank the following teams for their contributions to MMDeploy:

Citation

If you find this project useful in your research, please consider citing:

@misc{=mmdeploy,
    title={OpenMMLab's Model Deployment Toolbox.},
    author={MMDeploy Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmdeploy}},
    year={2021}
}

License

This project is released under the Apache 2.0 license.

Projects in OpenMMLab

  • MMCV: OpenMMLab foundational library for computer vision.
  • MIM: MIM installs OpenMMLab packages.
  • MMClassification: OpenMMLab image classification toolbox and benchmark.
  • MMDetection: OpenMMLab detection toolbox and benchmark.
  • MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.
  • MMRotate: OpenMMLab rotated object detection toolbox and benchmark.
  • MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
  • MMOCR: OpenMMLab text detection, recognition, and understanding toolbox.
  • MMPose: OpenMMLab pose estimation toolbox and benchmark.
  • MMHuman3D: OpenMMLab 3D human parametric model toolbox and benchmark.
  • MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
  • MMRazor: OpenMMLab model compression toolbox and benchmark.
  • MMFewShot: OpenMMLab fewshot learning toolbox and benchmark.
  • MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
  • MMTracking: OpenMMLab video perception toolbox and benchmark.
  • MMFlow: OpenMMLab optical flow toolbox and benchmark.
  • MMEditing: OpenMMLab image and video editing toolbox.
  • MMGeneration: OpenMMLab image and video generative models toolbox.
  • MMDeploy: OpenMMLab model deployment framework.