diff --git a/configs/slim/README.md b/configs/slim/README.md index 728c2f3760ffb7355e0ac3627ff3cfd193bd2b82..67ba7158502c2e4108521d249a0729ca5bf7dc18 100755 --- a/configs/slim/README.md +++ b/configs/slim/README.md @@ -4,33 +4,11 @@ - [剪裁](prune) - [量化](quant) +- [蒸馏](distill) +- [联合策略](extensions) 推荐您使用剪裁和蒸馏联合训练，或者使用剪裁和量化，进行检测模型压缩。 下面以YOLOv3为例，进行剪裁、蒸馏和量化实验。 -## Benchmark - -### 剪裁 - -#### Pascal VOC上benchmark - -| 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延（SD855）| Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | -| :----------------| :-------: | :------------: | :-------------: | :------: | :--------: | :------: | :-----------------------------------------------------: |:-------------: | :------: | -| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 289.9ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | -| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 77.6(+2.5) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/slim/prune/yolov3_prune_l1_norm.yml) | - -### 量化 - -#### COCO上benchmark - -| 模型 | 压缩策略 | 输入尺寸 | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | -| ------------------ | ------------ | -------- | :---------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 27.5 (-1.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | -| YOLOv3-MobileNetV3 | baseline | 608 | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | -| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 29.0 (-2.4) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | - -- SD855预测时延为使用PaddleLite部署，使用arm8架构并使用4线程(4 Threads)推理时延 - ## 实验环境 - Python 3.7+ @@ -39,6 +17,8 @@ - CUDA 9.0+ - cuDNN >=7.5 +**注意：** 量化训练需要依赖Paddle develop分支，可在[PaddlePaddle每日版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev)中下载安装合适的PaddlePaddle版本。 + ## 快速开始 ### 训练 @@ -84,3 +64,56 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ - `-c`: 指定模型配置文件。 - `--slim_config`: 指定压缩策略配置文件。 - `-o weights`: 指定压缩算法训好的模型路径。 + + +## Benchmark + +### 剪裁 + +#### Pascal VOC上benchmark + +| 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延（SD855）| Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | +| :----------------| :-------: | :------------: | :-------------: | :------: | :--------: | :------: | :-----------------------------------------------------: |:-------------: | :------: | +| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 289.9ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | +| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 77.6(+2.5) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/slim/prune/yolov3_prune_l1_norm.yml) | + +- 目前剪裁支持YOLO系列、SSD、TTFNet、BlazeFace，其余模型正在开发支持中。 +- SD855预测时延为使用PaddleLite部署，使用arm8架构并使用4线程(4 Threads)推理时延。 + +### 量化 + +#### COCO上benchmark + +| 模型 | 压缩策略 | 输入尺寸 | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | +| ------------------ | ------------ | -------- | :---------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | +| YOLOv3-MobileNetV1 | baseline | 608 | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 30.3 (+1.5) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | +| YOLOv3-MobileNetV3 | baseline | 608 | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | +| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 29.5 (-1.9) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | +| YOLOv3-DarkNet53 | baseline | 608 | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | +| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 38.7 (-0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_darknet_qat.yml) | +| SSD-MobileNet_v1 | baseline | 300 | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - | +| SSD-MobileNet_v1 | 普通在线量化 | 300 | 73.1(-0.7) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ssd_mobilenet_v1_qat.yml) | +| Mask-ResNet50-FPN | baseline | (800, 1333) | 39.2/35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - | +| Mask-ResNet50-FPN | 普通在线量化 | (800, 1333) | 39.7(+0.5)/35.9(+0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) | + + +### 蒸馏 + +#### COCO上benchmark + +| 模型 | 压缩策略 | 输入尺寸 | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | +| ------------------ | ------------ | -------- | :---------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | +| YOLOv3-MobileNetV1 | baseline | 608 | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 蒸馏 | 608 | 29.0 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) | + +- 具体蒸馏方法请参考[蒸馏策略文档](distill/README.md) + +### 蒸馏剪裁联合策略 + +#### COCO上benchmark + +| 模型 | 压缩策略 | 输入尺寸 | GFLOPs | 模型体积(MB) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | +| ------------------ | ------------ | -------- | :---------: |:---------: | :---------: |:----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | +| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.6 | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 蒸馏+剪裁 | 608 | 7.54(-69.4%) | 32.0(-66.0%) | 28.7(-0.1) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) | diff --git a/configs/slim/distill/README.md b/configs/slim/distill/README.md new file mode 100644 index 0000000000000000000000000000000000000000..da5795764cec02ea384f8e063f918b56b4f2b9bb --- /dev/null +++ b/configs/slim/distill/README.md @@ -0,0 +1,18 @@ +# Distillation(蒸馏) + +## YOLOv3模型蒸馏 +以YOLOv3-MobileNetV1为例，使用YOLOv3-ResNet34作为蒸馏训练的teacher网络, 对YOLOv3-MobileNetV1结构的student网络进行蒸馏。 +COCO数据集作为目标检测任务的训练目标难度更大，意味着teacher网络会预测出更多的背景bbox，如果直接用teacher的预测输出作为student学习的`soft label`会有严重的类别不均衡问题。解决这个问题需要引入新的方法，详细背景请参考论文:[Object detection at 200 Frames Per Second](https://arxiv.org/abs/1805.06361)。 +为了确定蒸馏的对象，我们首先需要找到student和teacher网络得到的`x,y,w,h,cls,objness`等Tensor，用teacher得到的结果指导student训练。具体实现可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/ppdet/slim/distill.py) + +## Citations +``` +@article{mehta2018object, + title={Object detection at 200 Frames Per Second}, + author={Rakesh Mehta and Cemalettin Ozturk}, + year={2018}, + eprint={1805.06361}, + archivePrefix={arXiv}, + primaryClass={cs.CV} +} +``` diff --git a/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml b/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml new file mode 100644 index 0000000000000000000000000000000000000000..9998dec5620adac38fd8a487f7ad1ec6aeb055dd --- /dev/null +++ b/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml @@ -0,0 +1,12 @@ +_BASE_: [ + '../../yolov3/yolov3_r34_270e_coco.yml', +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams + + +slim: Distill +distill_loss: DistillYOLOv3Loss + +DistillYOLOv3Loss: + weight: 1000 diff --git a/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml b/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml new file mode 100644 index 0000000000000000000000000000000000000000..f86fac5e9ed0f291c5b3f9b6266ac5755807422c --- /dev/null +++ b/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml @@ -0,0 +1,24 @@ +_BASE_: [ + '../../yolov3/yolov3_r34_270e_coco.yml', +] + +pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams + +slim: DistillPrune + +distill_loss: DistillYOLOv3Loss + +DistillYOLOv3Loss: + weight: 1000 + +pruner: Pruner + +Pruner: + criterion: l1_norm + pruned_params: ['conv2d_27.w_0', 'conv2d_28.w_0', 'conv2d_29.w_0', + 'conv2d_30.w_0', 'conv2d_31.w_0', 'conv2d_32.w_0', + 'conv2d_34.w_0', 'conv2d_35.w_0', 'conv2d_36.w_0', + 'conv2d_37.w_0', 'conv2d_38.w_0', 'conv2d_39.w_0', + 'conv2d_41.w_0', 'conv2d_42.w_0', 'conv2d_43.w_0', + 'conv2d_44.w_0', 'conv2d_45.w_0', 'conv2d_46.w_0'] + pruned_ratios: [0.5,0.5,0.5,0.5,0.5,0.5,0.7,0.7,0.7,0.7,0.7,0.7,0.8,0.8,0.8,0.8,0.8,0.8] diff --git a/configs/slim/prune/yolov3_prune_fpgm.yml b/configs/slim/prune/yolov3_prune_fpgm.yml index ed9495a73e4fbacbe20bbeb3093f2a7a406ea9e6..8d99997ef8ef547196d5c140705f21132ff41f8f 100644 --- a/configs/slim/prune/yolov3_prune_fpgm.yml +++ b/configs/slim/prune/yolov3_prune_fpgm.yml @@ -5,11 +5,11 @@ slim: Pruner Pruner: criterion: fpgm - pruned_params: ['yolo_block.0.0.0.conv.weights', 'yolo_block.0.0.1.conv.weights', 'yolo_block.0.1.0.conv.weights', - 'yolo_block.0.1.1.conv.weights', 'yolo_block.0.2.conv.weights', 'yolo_block.0.tip.conv.weights', - 'yolo_block.1.0.0.conv.weights', 'yolo_block.1.0.1.conv.weights', 'yolo_block.1.1.0.conv.weights', - 'yolo_block.1.1.1.conv.weights', 'yolo_block.1.2.conv.weights', 'yolo_block.1.tip.conv.weights', - 'yolo_block.2.0.0.conv.weights', 'yolo_block.2.0.1.conv.weights', 'yolo_block.2.1.0.conv.weights', - 'yolo_block.2.1.1.conv.weights', 'yolo_block.2.2.conv.weights', 'yolo_block.2.tip.conv.weights'] + pruned_params: ['conv2d_27.w_0', 'conv2d_28.w_0', 'conv2d_29.w_0', + 'conv2d_30.w_0', 'conv2d_31.w_0', 'conv2d_32.w_0', + 'conv2d_34.w_0', 'conv2d_35.w_0', 'conv2d_36.w_0', + 'conv2d_37.w_0', 'conv2d_38.w_0', 'conv2d_39.w_0', + 'conv2d_41.w_0', 'conv2d_42.w_0', 'conv2d_43.w_0', + 'conv2d_44.w_0', 'conv2d_45.w_0', 'conv2d_46.w_0'] pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3] print_params: False diff --git a/configs/slim/prune/yolov3_prune_l1_norm.yml b/configs/slim/prune/yolov3_prune_l1_norm.yml index db2a616daab7087e4b02c76c72df34c3a6a7937f..757117e387817a401dd8aa8b969c183053b41982 100644 --- a/configs/slim/prune/yolov3_prune_l1_norm.yml +++ b/configs/slim/prune/yolov3_prune_l1_norm.yml @@ -5,11 +5,11 @@ slim: Pruner Pruner: criterion: l1_norm - pruned_params: ['yolo_block.0.0.0.conv.weights', 'yolo_block.0.0.1.conv.weights', 'yolo_block.0.1.0.conv.weights', - 'yolo_block.0.1.1.conv.weights', 'yolo_block.0.2.conv.weights', 'yolo_block.0.tip.conv.weights', - 'yolo_block.1.0.0.conv.weights', 'yolo_block.1.0.1.conv.weights', 'yolo_block.1.1.0.conv.weights', - 'yolo_block.1.1.1.conv.weights', 'yolo_block.1.2.conv.weights', 'yolo_block.1.tip.conv.weights', - 'yolo_block.2.0.0.conv.weights', 'yolo_block.2.0.1.conv.weights', 'yolo_block.2.1.0.conv.weights', - 'yolo_block.2.1.1.conv.weights', 'yolo_block.2.2.conv.weights', 'yolo_block.2.tip.conv.weights'] + pruned_params: ['conv2d_27.w_0', 'conv2d_28.w_0', 'conv2d_29.w_0', + 'conv2d_30.w_0', 'conv2d_31.w_0', 'conv2d_32.w_0', + 'conv2d_34.w_0', 'conv2d_35.w_0', 'conv2d_36.w_0', + 'conv2d_37.w_0', 'conv2d_38.w_0', 'conv2d_39.w_0', + 'conv2d_41.w_0', 'conv2d_42.w_0', 'conv2d_43.w_0', + 'conv2d_44.w_0', 'conv2d_45.w_0', 'conv2d_46.w_0'] pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3] print_params: False diff --git a/configs/yolov3/README.md b/configs/yolov3/README.md index 97465271518066b886ed023372afbde7b267cd03..b27673d9cf21907c1f6b92dd44218c6fae9915d1 100644 --- a/configs/yolov3/README.md +++ b/configs/yolov3/README.md @@ -9,27 +9,30 @@ | DarkNet53(paper) | 608 | 8 | 270e | ---- | 33.0 | - | - | | DarkNet53(paper) | 416 | 8 | 270e | ---- | 31.0 | - | - | | DarkNet53(paper) | 320 | 8 | 270e | ---- | 28.2 | - | - | -| DarkNet53 | 608 | 8 | 270e | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| DarkNet53 | 416 | 8 | 270e | ---- | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| DarkNet53 | 320 | 8 | 270e | ---- | 34.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| ResNet50_vd | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | -| MobileNet-V1 | 608 | 8 | 270e | ---- | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V1 | 416 | 8 | 270e | ---- | 28.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V1 | 320 | 8 | 270e | ---- | 26.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | -| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | -| MobileNet-V3 | 320 | 8 | 270e | ---- | 26.9 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| DarkNet53 | 608 | 8 | 270e | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| DarkNet53 | 416 | 8 | 270e | ---- | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| DarkNet53 | 320 | 8 | 270e | ---- | 34.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| ResNet50_vd | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | +| ResNet34 | 608 | 8 | 270e | ---- | 36.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | +| ResNet34 | 416 | 8 | 270e | ---- | 34.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | +| ResNet34 | 320 | 8 | 270e | ---- | 31.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | +| MobileNet-V1 | 608 | 8 | 270e | ---- | 28.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V1 | 416 | 8 | 270e | ---- | 28.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V1 | 320 | 8 | 270e | ---- | 26.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| MobileNet-V3 | 320 | 8 | 270e | ---- | 26.9 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | ### YOLOv3 on Pasacl VOC | 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 | 配置文件 | | :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | -| MobileNet-V1 | 608 | 8 | 270e | - | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V1 | 416 | 8 | 270e | - | 76.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V1 | 320 | 8 | 270e | - | 73.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | -| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | -| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V1 | 608 | 8 | 270e | - | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V1 | 416 | 8 | 270e | - | 76.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V1 | 320 | 8 | 270e | - | 73.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | **注意：** YOLOv3均使用8GPU训练，训练270个epoch diff --git a/configs/yolov3/_base_/yolov3_r34.yml b/configs/yolov3/_base_/yolov3_r34.yml new file mode 100644 index 0000000000000000000000000000000000000000..c2d1489f07ba65240e5b545662b8c1672750b705 --- /dev/null +++ b/configs/yolov3/_base_/yolov3_r34.yml @@ -0,0 +1,41 @@ +architecture: YOLOv3 +pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams +norm_type: sync_bn + +YOLOv3: + backbone: ResNet + neck: YOLOv3FPN + yolo_head: YOLOv3Head + post_process: BBoxPostProcess + +ResNet: + depth: 34 + return_idx: [1, 2, 3] + freeze_at: -1 + freeze_norm: false + norm_decay: 0. + +YOLOv3Head: + anchors: [[10, 13], [16, 30], [33, 23], + [30, 61], [62, 45], [59, 119], + [116, 90], [156, 198], [373, 326]] + anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]] + loss: YOLOv3Loss + +YOLOv3Loss: + ignore_thresh: 0.7 + downsample: [32, 16, 8] + label_smooth: false + +BBoxPostProcess: + decode: + name: YOLOBox + conf_thresh: 0.005 + downsample_ratio: 32 + clip_bbox: true + nms: + name: MultiClassNMS + keep_top_k: 100 + score_threshold: 0.01 + nms_threshold: 0.45 + nms_top_k: 1000 diff --git a/configs/yolov3/yolov3_r34_270e_coco.yml b/configs/yolov3/yolov3_r34_270e_coco.yml new file mode 100644 index 0000000000000000000000000000000000000000..8653b06161b9145dbd23e00878d5c056986db5ec --- /dev/null +++ b/configs/yolov3/yolov3_r34_270e_coco.yml @@ -0,0 +1,10 @@ +_BASE_: [ + '../datasets/coco_detection.yml', + '../runtime.yml', + '_base_/optimizer_270e.yml', + '_base_/yolov3_r34.yml', + '_base_/yolov3_reader.yml', +] + +snapshot_epoch: 5 +weights: output/yolov3_r34_270e_coco/model_final diff --git a/ppdet/engine/callbacks.py b/ppdet/engine/callbacks.py index ca4ad613616056f41842f2dd2e9f1341bb556e4e..410de77447f990a84a42e4a4660056017ba5d4be 100644 --- a/ppdet/engine/callbacks.py +++ b/ppdet/engine/callbacks.py @@ -146,13 +146,17 @@ class Checkpointer(Callback): self.use_ema = ('use_ema' in cfg and cfg['use_ema']) self.save_dir = os.path.join(self.model.cfg.save_dir, self.model.cfg.filename) + if hasattr(self.model.model, 'student_model'): + self.weight = self.model.model.student_model + else: + self.weight = self.model.model if self.use_ema: self.ema = ModelEMA( - cfg['ema_decay'], self.model.model, use_thres_step=True) + cfg['ema_decay'], self.weight, use_thres_step=True) def on_step_end(self, status): if self.use_ema: - self.ema.update(self.model.model) + self.ema.update(self.weight) def on_epoch_end(self, status): # Checkpointer only performed during training @@ -169,7 +173,7 @@ class Checkpointer(Callback): if self.use_ema: weight = self.ema.apply() else: - weight = self.model.model + weight = self.weight elif mode == 'eval': if 'save_best_model' in status and status['save_best_model']: for metric in self.model._metrics: @@ -181,7 +185,7 @@ class Checkpointer(Callback): if self.use_ema: weight = self.ema.apply() else: - weight = self.model.model + weight = self.weight logger.info("Best test {} ap is {:0.3f}.".format( key, self.best_ap)) if weight: diff --git a/ppdet/engine/trainer.py b/ppdet/engine/trainer.py index f6b10b144675b0664c72320fa8e402e5a17ffa47..be2c14e68f6d7c0eefd0a084c3b7faf4c2fc73c2 100644 --- a/ppdet/engine/trainer.py +++ b/ppdet/engine/trainer.py @@ -52,17 +52,14 @@ class Trainer(object): "mode should be 'train', 'eval' or 'test'" self.mode = mode.lower() self.optimizer = None - self.slim = None + self.is_loaded_weights = False # build model - self.model = create(cfg.architecture) - - # model slim build - if 'slim' in cfg and cfg.slim: - if self.mode == 'train': - self.load_weights(cfg.pretrain_weights) - self.slim = create(cfg.slim) - self.slim(self.model) + if 'model' not in self.cfg: + self.model = create(cfg.architecture) + else: + self.model = self.cfg.model + self.is_loaded_weights = True # build data loader self.dataset = cfg['{}Dataset'.format(self.mode.capitalize())] @@ -192,12 +189,19 @@ class Trainer(object): self._metrics.extend(metrics) def load_weights(self, weights): + if self.is_loaded_weights: + return self.start_epoch = 0 load_pretrain_weight(self.model, weights) logger.debug("Load weights {} to start training".format(weights)) def resume_weights(self, weights): - self.start_epoch = load_weight(self.model, weights, self.optimizer) + # support Distill resume weights + if hasattr(self.model, 'student_model'): + self.start_epoch = load_weight(self.model.student_model, weights, + self.optimizer) + else: + self.start_epoch = load_weight(self.model, weights, self.optimizer) logger.debug("Resume weights of epoch {}".format(self.start_epoch)) def train(self, validate=False): @@ -419,7 +423,7 @@ class Trainer(object): }] # dy2st and save model - if self.slim is None or self.cfg['slim'] != 'QAT': + if 'slim' not in self.cfg or self.cfg['slim'] != 'QAT': static_model = paddle.jit.to_static( self.model, input_spec=input_spec) # NOTE: dy2st do not pruned program, but jit.save will prune program @@ -433,7 +437,7 @@ class Trainer(object): input_spec=pruned_input_spec) logger.info("Export model and saved in {}".format(save_dir)) else: - self.slim.save_quantized_model( + self.cfg.slim.save_quantized_model( self.model, os.path.join(save_dir, 'model'), input_spec=input_spec) diff --git a/ppdet/modeling/backbones/darknet.py b/ppdet/modeling/backbones/darknet.py index 7981306a912b7d893e9c63b76b0aee9247019ba0..ab748c66b9d525082b11adb1c498f5b6603be0ba 100755 --- a/ppdet/modeling/backbones/darknet.py +++ b/ppdet/modeling/backbones/darknet.py @@ -46,7 +46,6 @@ class ConvBNLayer(nn.Layer): stride=stride, padding=padding, groups=groups, - weight_attr=ParamAttr(name=name + '.conv.weights'), data_format=data_format, bias_attr=False) self.batch_norm = batch_norm( diff --git a/ppdet/modeling/backbones/mobilenet_v1.py b/ppdet/modeling/backbones/mobilenet_v1.py index 5b4d1287847808f0e4c0d20b7809a1efee3cd82b..cecc6a5b5e79db265936fa149019ac9323811eaf 100644 --- a/ppdet/modeling/backbones/mobilenet_v1.py +++ b/ppdet/modeling/backbones/mobilenet_v1.py @@ -55,14 +55,11 @@ class ConvBNLayer(nn.Layer): weight_attr=ParamAttr( learning_rate=conv_lr, initializer=KaimingNormal(), - regularizer=L2Decay(conv_decay), - name=name + "_weights"), + regularizer=L2Decay(conv_decay)), bias_attr=False) - param_attr = ParamAttr( - name=name + "_bn_scale", regularizer=L2Decay(norm_decay)) - bias_attr = ParamAttr( - name=name + "_bn_offset", regularizer=L2Decay(norm_decay)) + param_attr = ParamAttr(regularizer=L2Decay(norm_decay)) + bias_attr = ParamAttr(regularizer=L2Decay(norm_decay)) if norm_type == 'sync_bn': self._batch_norm = nn.SyncBatchNorm( out_channels, weight_attr=param_attr, bias_attr=bias_attr) @@ -72,9 +69,7 @@ class ConvBNLayer(nn.Layer): act=None, param_attr=param_attr, bias_attr=bias_attr, - use_global_stats=False, - moving_mean_name=name + '_bn_mean', - moving_variance_name=name + '_bn_variance') + use_global_stats=False) def forward(self, x): x = self._conv(x) diff --git a/ppdet/modeling/backbones/resnet.py b/ppdet/modeling/backbones/resnet.py index e59f1761464a59538b692e5413292577175b2be9..f642764ad73b65ba69b374b05ff715d9586c364b 100755 --- a/ppdet/modeling/backbones/resnet.py +++ b/ppdet/modeling/backbones/resnet.py @@ -64,7 +64,7 @@ class ConvNormLayer(nn.Layer): padding=(filter_size - 1) // 2, groups=groups, weight_attr=paddle.ParamAttr( - learning_rate=lr, name=name + "_weights"), + learning_rate=lr, ), bias_attr=False) else: self.conv = DeformableConvV2( @@ -75,7 +75,7 @@ class ConvNormLayer(nn.Layer): padding=(filter_size - 1) // 2, groups=groups, weight_attr=paddle.ParamAttr( - learning_rate=lr, name=name + '_weights'), + learning_rate=lr, ), bias_attr=False, name=name) @@ -84,12 +84,10 @@ class ConvNormLayer(nn.Layer): param_attr = paddle.ParamAttr( learning_rate=norm_lr, regularizer=L2Decay(norm_decay), - name=bn_name + "_scale", trainable=False if freeze_norm else True) bias_attr = paddle.ParamAttr( learning_rate=norm_lr, regularizer=L2Decay(norm_decay), - name=bn_name + "_offset", trainable=False if freeze_norm else True) global_stats = True if freeze_norm else False @@ -102,9 +100,7 @@ class ConvNormLayer(nn.Layer): act=None, param_attr=param_attr, bias_attr=bias_attr, - use_global_stats=global_stats, - moving_mean_name=bn_name + '_mean', - moving_variance_name=bn_name + '_variance') + use_global_stats=global_stats) norm_params = self.norm.parameters() if freeze_norm: diff --git a/ppdet/modeling/heads/yolo_head.py b/ppdet/modeling/heads/yolo_head.py index 723bf4fc6e541021a3d0f7c3a782f843b4272fff..3516da4108ddac38c93480c401c6b40af5b9ef05 100644 --- a/ppdet/modeling/heads/yolo_head.py +++ b/ppdet/modeling/heads/yolo_head.py @@ -56,9 +56,7 @@ class YOLOv3Head(nn.Layer): stride=1, padding=0, data_format=data_format, - weight_attr=ParamAttr(name=name + '.conv.weights'), - bias_attr=ParamAttr( - name=name + '.conv.bias', regularizer=L2Decay(0.)))) + bias_attr=ParamAttr(regularizer=L2Decay(0.)))) self.yolo_outputs.append(yolo_output) def parse_anchor(self, anchors, anchor_masks): diff --git a/ppdet/modeling/losses/fcos_loss.py b/ppdet/modeling/losses/fcos_loss.py index 350011accd0dce47177f744665791afa9eccb5a0..201786c9a559206fcbf8176d025b72a5334b0237 100644 --- a/ppdet/modeling/losses/fcos_loss.py +++ b/ppdet/modeling/losses/fcos_loss.py @@ -20,6 +20,7 @@ import paddle import paddle.nn as nn import paddle.nn.functional as F from ppdet.core.workspace import register +from ppdet.modeling import ops INF = 1e8 __all__ = ['FCOSLoss'] @@ -44,19 +45,6 @@ def flatten_tensor(inputs, channel_first=False): return output_channel_last -def sigmoid_cross_entropy_with_logits_loss(inputs, - label, - ignore_index=-100, - normalize=False): - output = F.binary_cross_entropy_with_logits(inputs, label, reduction='none') - mask_tensor = paddle.cast(label != ignore_index, 'float32') - output = paddle.multiply(output, mask_tensor) - if normalize: - sum_valid_mask = paddle.sum(mask_tensor) - output = output / sum_valid_mask - return output - - @register class FCOSLoss(nn.Layer): """ @@ -226,8 +214,8 @@ class FCOSLoss(nn.Layer): # 3. centerness: sigmoid_cross_entropy_with_logits_loss centerness_flatten = paddle.squeeze(centerness_flatten, axis=-1) - ctn_loss = sigmoid_cross_entropy_with_logits_loss(centerness_flatten, - tag_center_flatten) + ctn_loss = ops.sigmoid_cross_entropy_with_logits(centerness_flatten, + tag_center_flatten) ctn_loss = ctn_loss * mask_positive_float / num_positive_fp32 loss_all = { diff --git a/ppdet/modeling/losses/yolo_loss.py b/ppdet/modeling/losses/yolo_loss.py index e460d2e2866d26afa5ca49a4823f2a696ba2e947..9579acf9f9a1d6f27bed7431e6dbe769ce7edbf6 100644 --- a/ppdet/modeling/losses/yolo_loss.py +++ b/ppdet/modeling/losses/yolo_loss.py @@ -54,6 +54,7 @@ class YOLOv3Loss(nn.Layer): self.scale_x_y = scale_x_y self.iou_loss = iou_loss self.iou_aware_loss = iou_aware_loss + self.distill_pairs = [] def obj_loss(self, pbox, gbox, pobj, tobj, anchor, downsample): # pbox @@ -108,6 +109,7 @@ class YOLOv3Loss(nn.Layer): x, y = p[:, :, :, :, 0:1], p[:, :, :, :, 1:2] w, h = p[:, :, :, :, 2:3], p[:, :, :, :, 3:4] obj, pcls = p[:, :, :, :, 4:5], p[:, :, :, :, 5:] + self.distill_pairs.append([x, y, w, h, obj, pcls]) t = t.transpose((0, 1, 3, 4, 2)) tx, ty = t[:, :, :, :, 0:1], t[:, :, :, :, 1:2] @@ -173,6 +175,7 @@ class YOLOv3Loss(nn.Layer): gt_targets = [targets['target{}'.format(i)] for i in range(np)] gt_box = targets['gt_bbox'] yolo_losses = dict() + self.distill_pairs.clear() for x, t, anchor, downsample in zip(inputs, gt_targets, anchors, self.downsample): yolo_loss = self.yolov3_loss(x, t, gt_box, anchor, downsample, diff --git a/ppdet/modeling/ops.py b/ppdet/modeling/ops.py index ef961dd1c220f8cee5a46745259add9a3d0cbbe1..cbef3d6b401ace03c83a0354692b311a729e938b 100644 --- a/ppdet/modeling/ops.py +++ b/ppdet/modeling/ops.py @@ -59,11 +59,8 @@ def batch_norm(ch, return batch_norm( ch, weight_attr=ParamAttr( - name=bn_name + '.scale', - initializer=initializer, - regularizer=L2Decay(norm_decay)), - bias_attr=ParamAttr( - name=bn_name + '.offset', regularizer=L2Decay(norm_decay)), + initializer=initializer, regularizer=L2Decay(norm_decay)), + bias_attr=ParamAttr(regularizer=L2Decay(norm_decay)), data_format=data_format) @@ -1558,7 +1555,6 @@ def sigmoid_cross_entropy_with_logits(input, output = F.binary_cross_entropy_with_logits(input, label, reduction='none') mask_tensor = paddle.cast(label != ignore_index, 'float32') output = paddle.multiply(output, mask_tensor) - output = paddle.reshape(output, shape=[output.shape[0], -1]) if normalize: sum_valid_mask = paddle.sum(mask_tensor) output = output / sum_valid_mask diff --git a/ppdet/slim/__init__.py b/ppdet/slim/__init__.py index 7a58bf591c895d699301c0f88dd55268552581e5..ebd64c0e582bb91df474ce5a89f74574f3f01828 100644 --- a/ppdet/slim/__init__.py +++ b/ppdet/slim/__init__.py @@ -14,6 +14,47 @@ from . import prune from . import quant +from . import distill from .prune import * from .quant import * +from .distill import * + +import yaml +from ppdet.core.workspace import load_config +from ppdet.utils.checkpoint import load_pretrain_weight + + +def build_slim_model(cfg, slim_cfg, mode='train'): + with open(slim_cfg) as f: + slim_load_cfg = yaml.load(f, Loader=yaml.Loader) + if mode != 'train' and slim_load_cfg['slim'] == 'Distill': + return cfg + + if slim_load_cfg['slim'] == 'Distill': + model = DistillModel(cfg, slim_cfg) + cfg['model'] = model + elif slim_load_cfg['slim'] == 'DistillPrune': + if mode == 'train': + model = DistillModel(cfg, slim_cfg) + pruner = create(cfg.pruner) + pruner(model.student_model) + else: + model = create(cfg.architecture) + weights = cfg.weights + load_config(slim_cfg) + pruner = create(cfg.pruner) + model = pruner(model) + load_pretrain_weight(model, weights) + cfg['model'] = model + else: + load_config(slim_cfg) + model = create(cfg.architecture) + if mode == 'train': + load_pretrain_weight(model, cfg.pretrain_weights) + slim = create(cfg.slim) + cfg['model'] = slim(model) + if mode != 'train': + load_pretrain_weight(cfg['model'], cfg.weights) + + return cfg diff --git a/ppdet/slim/distill.py b/ppdet/slim/distill.py new file mode 100644 index 0000000000000000000000000000000000000000..d5c9d72669a601ce331afde69ce92ca6642fb3d2 --- /dev/null +++ b/ppdet/slim/distill.py @@ -0,0 +1,110 @@ +# Copyright (c) 2021 PaddlePaddle Authors. 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 __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import paddle +import paddle.nn as nn +import paddle.nn.functional as F + +from ppdet.core.workspace import register, serializable, load_config +from ppdet.core.workspace import create +from ppdet.utils.logger import setup_logger +from ppdet.modeling import ops +from ppdet.utils.checkpoint import load_pretrain_weight +from ppdet.modeling.losses import YOLOv3Loss +logger = setup_logger(__name__) + + +class DistillModel(nn.Layer): + def __init__(self, cfg, slim_cfg): + super(DistillModel, self).__init__() + + self.student_model = create(cfg.architecture) + logger.debug('Load student model pretrain_weights:{}'.format( + cfg.pretrain_weights)) + load_pretrain_weight(self.student_model, cfg.pretrain_weights) + + slim_cfg = load_config(slim_cfg) + self.teacher_model = create(slim_cfg.architecture) + self.distill_loss = create(slim_cfg.distill_loss) + logger.debug('Load teacher model pretrain_weights:{}'.format( + slim_cfg.pretrain_weights)) + load_pretrain_weight(self.teacher_model, slim_cfg.pretrain_weights) + + for param in self.teacher_model.parameters(): + param.trainable = False + + def parameters(self): + return self.student_model.parameters() + + def forward(self, inputs): + if self.training: + teacher_loss = self.teacher_model(inputs) + student_loss = self.student_model(inputs) + loss = self.distill_loss(self.teacher_model, self.student_model) + student_loss['distill_loss'] = loss + student_loss['teacher_loss'] = teacher_loss['loss'] + student_loss['loss'] += student_loss['distill_loss'] + return student_loss + else: + return self.student_model(inputs) + + +@register +class DistillYOLOv3Loss(nn.Layer): + def __init__(self, weight=1000): + super(DistillYOLOv3Loss, self).__init__() + self.weight = weight + + def obj_weighted_reg(self, sx, sy, sw, sh, tx, ty, tw, th, tobj): + loss_x = ops.sigmoid_cross_entropy_with_logits(sx, F.sigmoid(tx)) + loss_y = ops.sigmoid_cross_entropy_with_logits(sy, F.sigmoid(ty)) + loss_w = paddle.abs(sw - tw) + loss_h = paddle.abs(sh - th) + loss = paddle.add_n([loss_x, loss_y, loss_w, loss_h]) + weighted_loss = paddle.mean(loss * F.sigmoid(tobj)) + return weighted_loss + + def obj_weighted_cls(self, scls, tcls, tobj): + loss = ops.sigmoid_cross_entropy_with_logits(scls, F.sigmoid(tcls)) + weighted_loss = paddle.mean(paddle.multiply(loss, F.sigmoid(tobj))) + return weighted_loss + + def obj_loss(self, sobj, tobj): + obj_mask = paddle.cast(tobj > 0., dtype="float32") + obj_mask.stop_gradient = True + loss = paddle.mean( + ops.sigmoid_cross_entropy_with_logits(sobj, obj_mask)) + return loss + + def forward(self, teacher_model, student_model): + teacher_distill_pairs = teacher_model.yolo_head.loss.distill_pairs + student_distill_pairs = student_model.yolo_head.loss.distill_pairs + distill_reg_loss, distill_cls_loss, distill_obj_loss = [], [], [] + for s_pair, t_pair in zip(student_distill_pairs, teacher_distill_pairs): + distill_reg_loss.append( + self.obj_weighted_reg(s_pair[0], s_pair[1], s_pair[2], s_pair[ + 3], t_pair[0], t_pair[1], t_pair[2], t_pair[3], t_pair[4])) + distill_cls_loss.append( + self.obj_weighted_cls(s_pair[5], t_pair[5], t_pair[4])) + distill_obj_loss.append(self.obj_loss(s_pair[4], t_pair[4])) + distill_reg_loss = paddle.add_n(distill_reg_loss) + distill_cls_loss = paddle.add_n(distill_cls_loss) + distill_obj_loss = paddle.add_n(distill_obj_loss) + loss = (distill_reg_loss + distill_cls_loss + distill_obj_loss + ) * self.weight + return loss diff --git a/ppdet/utils/checkpoint.py b/ppdet/utils/checkpoint.py index f70cad4fce8c6bb32bde9ae577621e1b69b25334..d491976f58c6d1e63e6901c793d95e9c9e25f888 100644 --- a/ppdet/utils/checkpoint.py +++ b/ppdet/utils/checkpoint.py @@ -178,6 +178,38 @@ def load_pretrain_weight(model, pretrain_weight): logger.info('Finish loading model weights: {}'.format(weights_path)) +def load_static_pretrain_weight(model, pretrain_weight): + + if is_url(pretrain_weight): + pretrain_weight = get_weights_path_dist(pretrain_weight) + + path = _strip_postfix(pretrain_weight) + if not (os.path.isdir(path) or os.path.isfile(path) or + os.path.exists(path + '.pdparams')): + raise ValueError("Model pretrain path `{}` does not exists. " + "If you don't want to load pretrain model, " + "please delete `pretrain_weights` field in " + "config file.".format(path)) + + model_dict = model.state_dict() + + pre_state_dict = paddle.static.load_program_state(path) + param_state_dict = {} + for key in model_dict.keys(): + weight_name = model_dict[key].name + if weight_name in pre_state_dict.keys(): + logger.info('Load weight: {}, shape: {}'.format( + weight_name, pre_state_dict[weight_name].shape)) + param_state_dict[key] = pre_state_dict[weight_name] + else: + if 'backbone' in key: + logger.info('Lack weight: {}, structure name: {}'.format( + weight_name, key)) + param_state_dict[key] = model_dict[key] + model.set_dict(param_state_dict) + return + + def save_model(model, optimizer, save_dir, save_name, last_epoch): """ save model into disk. diff --git a/tools/eval.py b/tools/eval.py index 21ee29d160cfb1331489dcc09a597e302f6a09c8..3025dd822d021811440ceb11964d9bd357eb3a15 100755 --- a/tools/eval.py +++ b/tools/eval.py @@ -33,6 +33,7 @@ from ppdet.utils.check import check_gpu, check_version, check_config from ppdet.utils.cli import ArgsParser from ppdet.engine import Trainer, init_parallel_env from ppdet.metrics.coco_utils import json_eval_results +from ppdet.slim import build_slim_model from ppdet.utils.logger import setup_logger logger = setup_logger('eval') @@ -100,22 +101,22 @@ def run(FLAGS, cfg): def main(): FLAGS = parse_args() - cfg = load_config(FLAGS.config) # TODO: bias should be unified cfg['bias'] = 1 if FLAGS.bias else 0 cfg['classwise'] = True if FLAGS.classwise else False cfg['output_eval'] = FLAGS.output_eval merge_config(FLAGS.opt) + + place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') + if FLAGS.slim_config: - slim_cfg = load_config(FLAGS.slim_config) - merge_config(slim_cfg) + cfg = build_slim_model(cfg, FLAGS.slim_config, mode='eval') + check_config(cfg) check_gpu(cfg.use_gpu) check_version() - place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') - run(FLAGS, cfg) diff --git a/tools/export_model.py b/tools/export_model.py index d04422873d06e49e2de596d09496c91778251532..8cf3885c88552ca9b48f8b8d6796377d96912a2e 100644 --- a/tools/export_model.py +++ b/tools/export_model.py @@ -31,6 +31,7 @@ from ppdet.core.workspace import load_config, merge_config from ppdet.utils.check import check_gpu, check_version, check_config from ppdet.utils.cli import ArgsParser from ppdet.engine import Trainer +from ppdet.slim import build_slim_model from ppdet.utils.logger import setup_logger logger = setup_logger('export_model') @@ -84,15 +85,15 @@ def run(FLAGS, cfg): def main(): paddle.set_device("cpu") FLAGS = parse_args() - cfg = load_config(FLAGS.config) # TODO: to be refined in the future if 'norm_type' in cfg and cfg['norm_type'] == 'sync_bn': FLAGS.opt['norm_type'] = 'bn' merge_config(FLAGS.opt) + if FLAGS.slim_config: - slim_cfg = load_config(FLAGS.slim_config) - merge_config(slim_cfg) + cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test') + check_config(cfg) check_gpu(cfg.use_gpu) check_version() diff --git a/tools/infer.py b/tools/infer.py index a2507680b812b34e04007c4bff8e366330bf4760..19d7b36f6460521b01b0f20f540984399c701991 100755 --- a/tools/infer.py +++ b/tools/infer.py @@ -31,6 +31,7 @@ from ppdet.core.workspace import load_config, merge_config from ppdet.engine import Trainer from ppdet.utils.check import check_gpu, check_version, check_config from ppdet.utils.cli import ArgsParser +from ppdet.slim import build_slim_model from ppdet.utils.logger import setup_logger logger = setup_logger('train') @@ -127,19 +128,20 @@ def run(FLAGS, cfg): def main(): FLAGS = parse_args() - cfg = load_config(FLAGS.config) cfg['use_vdl'] = FLAGS.use_vdl cfg['vdl_log_dir'] = FLAGS.vdl_log_dir merge_config(FLAGS.opt) + + place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') + if FLAGS.slim_config: - slim_cfg = load_config(FLAGS.slim_config) - merge_config(slim_cfg) + cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test') + check_config(cfg) check_gpu(cfg.use_gpu) check_version() - place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') run(FLAGS, cfg) diff --git a/tools/train.py b/tools/train.py index cdbe87ab2d1603527ddf60397a66ad53670a04f3..565ba8e906f19c95c1a75a8e1e9ce479c12d4cac 100755 --- a/tools/train.py +++ b/tools/train.py @@ -33,6 +33,7 @@ import paddle from ppdet.core.workspace import load_config, merge_config, create from ppdet.utils.checkpoint import load_weight, load_pretrain_weight from ppdet.engine import Trainer, init_parallel_env, set_random_seed, init_fleet_env +from ppdet.slim import build_slim_model import ppdet.utils.cli as cli import ppdet.utils.check as check @@ -98,7 +99,7 @@ def run(FLAGS, cfg): # load weights if FLAGS.resume is not None: trainer.resume_weights(FLAGS.resume) - elif not FLAGS.slim_config and 'pretrain_weights' in cfg and cfg.pretrain_weights: + elif 'pretrain_weights' in cfg and cfg.pretrain_weights: trainer.load_weights(cfg.pretrain_weights) # training @@ -107,22 +108,22 @@ def run(FLAGS, cfg): def main(): FLAGS = parse_args() - cfg = load_config(FLAGS.config) cfg['fp16'] = FLAGS.fp16 cfg['fleet'] = FLAGS.fleet cfg['use_vdl'] = FLAGS.use_vdl cfg['vdl_log_dir'] = FLAGS.vdl_log_dir merge_config(FLAGS.opt) + + place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') + if FLAGS.slim_config: - slim_cfg = load_config(FLAGS.slim_config) - merge_config(slim_cfg) + cfg = build_slim_model(cfg, FLAGS.slim_config) + check.check_config(cfg) check.check_gpu(cfg.use_gpu) check.check_version() - place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu') - run(FLAGS, cfg)