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[Feature] Add detection distill algorithm LAD #436

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Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.

Motivation

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Modification

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Does the modification introduce changes that break the backward compatibility of the downstream repositories?
If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.

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  • Bug fixes are fully covered by unit tests, the case that causes the bug should be added in the unit tests.
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@pppppM pppppM changed the title add lad to distill configs [Feature] Add detection distill algorithm LAD Jan 12, 2023
@LiuQQQQQQQ LiuQQQQQQQ closed this Jan 12, 2023
@LiuQQQQQQQ LiuQQQQQQQ reopened this Jan 12, 2023
@pppppM pppppM requested a review from wilxy February 3, 2023 03:05
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Thanks for your constructive PR, it is a great application example of the delivery module.
Please make further modifications based on my comments to merge this PR into MMRazor.


| Teacher | Student | Training schedule | AP (val) | Config | Download |
| :-----: | :-----: | :---------------: | :------: | :----------: | :----------------------: |
| -- | R-50 | 1x | 40.4 | [config](<>) | [model](<>) \| [log](<>) |
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Maybe can add the paths of config, model and log for the two baselines from MMClassification.

| -- | R-50 | 1x | 40.4 | [config](<>) | [model](<>) \| [log](<>) |
| -- | R-101 | 1x | 42.6 | [config](<>) | [model](<>) \| [log](<>) |
| R-101 | R-50 | 1x | 41.4 | [config](<>) | [model](<>) \| [log](<>) |
| R-50 | R-101 | 1x | 43.2 | [config](<>) | [model](<>) \| [log](<>) |
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Please add the config of this distillation (lad_ppa_r50_ppa_r101_1x_coco.py).
And contact with @pppppM to upload the files (model and log) after training.

@@ -0,0 +1,30 @@
_base_ = ['mmdet::paa/paa_r101_fpn_1x_coco.py']
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Backbone of the student model should be r50.

humu789 pushed a commit to humu789/mmrazor that referenced this pull request Feb 13, 2023
* refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils

* refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils

* refactor(onnx2ncnn.cpp): split code

* refactor(net_module.cpp): fix build error

* ci(test_onnx2ncnn.py): add generate model adn run

* ci(onnx2ncnn): add ncnn backend

* ci(test_onnx2ncnn): add converted onnx model`

* ci(onnx2ncnn): fix ncnn tar

* ci(backed-ncnn): simplify dependency install

* ci(onnx2ncnn): fix apt install

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* Update backend-ncnn.yml

* fix(ci): add include algorithm

* Update build.yml

* parent aa85760
author q.yao <streetyao@live.com> 1651287879 +0800
committer tpoisonooo <khj.application@aliyun.com> 1652169959 +0800

[Fix] Fix ci (open-mmlab#426)

* fix ci

* add nvidia key

* remote torch

* recover pytorch

refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils

* fix(onnx2ncnn): review

* fix(onnx2ncnn): build error

Co-authored-by: q.yao <streetyao@live.com>
@pppppM pppppM requested a review from HIT-cwh April 10, 2023 05:10
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Hi @LiuQQQQQQQ !We are grateful for your efforts in helping improve this open-source project during your personal time.

Welcome to join OpenMMLab Special Interest Group (SIG) private channel on Discord, where you can share your experiences, ideas, and build connections with like-minded peers. To join the SIG channel, simply message moderator— OpenMMLab on Discord or briefly share your open-source contributions in the #introductions channel and we will assist you. Look forward to seeing you there! Join us :https://discord.gg/UjgXkPWNqA
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Thank you again for your contribution❤

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3 participants