# Model Compression

In PaddleDetection, a complete tutorial and benchmarks for model compression based on [PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim) are provided. Currently supported methods:

- [pruning](prune)
- [quantitative](quant)
- [distillation](distill)
- [The joint strategy](extensions)

It is recommended that you use a combination of pruning and distillation training, or use pruning and quantization for test model compression. The following takes YOLOv3 as an example to carry out cutting, distillation and quantization experiments.

## Experimental Environment

- Python 3.7+
- PaddlePaddle >= 2.1.0
- PaddleSlim >= 2.1.0
- CUDA 10.1+
- cuDNN >=7.6.5

**Version Dependency between PaddleDetection, Paddle and PaddleSlim Version**
| PaddleDetection Version | PaddlePaddle Version | PaddleSlim Version |                                                                                               Note                                                                                               |
| :---------------------: | :------------------: | :----------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
|       release/2.1       |       >= 2.1.0       |        2.1         | Quantitative model exports rely on the latest Paddle Develop branch, available in[PaddlePaddle Daily version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) |
|       release/2.0       |       >= 2.0.1       |        2.0         |                                                                      Quantization depends on Paddle 2.1 and PaddleSlim 2.1                                                                       |


#### Install PaddleSlim
- Method 1: Install it directly：
```
pip install paddleslim -i https://pypi.tuna.tsinghua.edu.cn/simple
```
- Method 2: Compile and install：
```
git clone https://github.com/PaddlePaddle/PaddleSlim.git
cd PaddleSlim
python setup.py install
```

## Quick Start

### Train

```shell
python tools/train.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml}
```

- `-c`: Specify the model configuration file.
- `--slim_config`: Specify the compression policy profile.
- If you want to use distillation, please refer to [Distillation Doc](distill/README.md) for specific distillation methods and more distillation of detection models.


### Evaluation

```shell
python tools/eval.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} -o weights=output/{SLIM_CONFIG}/model_final
```

- `-c`: Specify the model configuration file.
- `--slim_config`: Specify the compression policy profile.
- `-o weights`: Specifies the path of the model trained by the compression algorithm.

### Test

```shell
python tools/infer.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} \
    -o weights=output/{SLIM_CONFIG}/model_final
    --infer_img={IMAGE_PATH}
```

- `-c`: Specify the model configuration file.
- `--slim_config`: Specify the compression policy profile.
- `-o weights`: Specifies the path of the model trained by the compression algorithm.
- `--infer_img`: Specifies the test image path.


## Full Chain Deployment

### the model is derived from moving to static

```shell
python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} -o weights=output/{SLIM_CONFIG}/model_final
```

- `-c`: Specify the model configuration file.
- `--slim_config`: Specify the compression policy profile.
- `-o weights`: Specifies the path of the model trained by the compression algorithm.

### prediction and deployment

- Paddle-Inference Prediction：
    - [Python Deployment](../../deploy/python/README.md)
    - [C++ Deployment](../../deploy/cpp/README.md)
    - [TensorRT Predictive Deployment Tutorial](../../deploy/TENSOR_RT.md)
- Server deployment: Used[PaddleServing](../../deploy/serving/README.md)
- Mobile deployment: Use[Paddle-Lite](../../deploy/lite/README.md) Deploy it on the mobile terminal.

## Benchmark

### Pruning

#### Pascal VOC Benchmark

|       Model        | Compression Strategy  |     GFLOPs     | Model Volume(MB) | Input Size | Predict Delay(SD855) |   Box AP   |                                              Download                                              |                                                      Model Configuration File                                                      |                                              Compression Algorithm Configuration File                                               |
| :----------------: | :-------------------: | :------------: | :--------------: | :--------: | :------------------: | :--------: | :------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------: |
| YOLOv3-MobileNetV1 |       baseline        |     24.13      |        93        |    608     |       332.0ms        |    75.1    |        [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams)        | [configuration file](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     |          -           | 78.4(+3.3) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_prune_l1_norm.yml) |

#### COCO Benchmark
|           Mode            | Compression Strategy | GFLOPs | Model Volume(MB) | Input Size | Predict Delay(SD855) | Box AP |                                         Download                                          |                                                     Model Configuration File                                                     |                                                  Compression Algorithm Configuration File                                                   |
| :-----------------------: | :------------------: | :----: | :--------------: | :--------: | :------------------: | :----: | :---------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------: |
| PP-YOLO-MobileNetV3_large |       baseline       |   --   |       18.5       |    608     |        25.1ms        |  23.2  |      [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams)       |   [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml)   |                                                                      -                                                                      |
| PP-YOLO-MobileNetV3_large |      剪裁-FPGM       |  -37%  |       12.6       |    608     |          -           |  22.3  | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) |   [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml)   | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) |
|     YOLOv3-DarkNet53      |       baseline       |   --   |      238.2       |    608     |          -           |  39.0  |      [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams)       | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) |                                                                      -                                                                      |
|     YOLOv3-DarkNet53      |      剪裁-FPGM       |  -24%  |        -         |    608     |          -           |  37.6  |  [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams)   | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) |  [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_darknet_prune_fpgm.yml)   |
|       PP-YOLO_R50vd       |       baseline       |   --   |      183.3       |    608     |          -           |  44.8  |     [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams)      |  [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)  |                                                                      -                                                                      |
|       PP-YOLO_R50vd       |      剪裁-FPGM       |  -35%  |        -         |    608     |          -           |  42.1  |   [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams)    |  [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)  |   [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml)    |

Description:
- Currently, all models except RCNN series models are supported.
- The SD855 predicts the delay for deployment using Paddle Lite, using the ARM8 architecture and using 4 Threads (4 Threads) to reason the delay.

### Quantitative

#### COCO Benchmark

| Model                     | Compression Strategy       | Input Size  | Model Volume(MB) | Prediction Delay(V100) | Prediction Delay(SD855) |        Box AP         |                                          Download                                           |                                 Download of Inference Model                                 |                                                          Model Configuration File                                                          |                                                 Compression Algorithm Configuration File                                                 |
| ------------------------- | -------------------------- | ----------- | :--------------: | :--------------------: | :---------------------: | :-------------------: | :-----------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------: |
| PP-YOLOE-l | baseline     | 640      | - |   11.2ms(trt_fp32) &#124; 7.7ms(trt_fp16)   | -- | 50.9     | [link](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams) | -  | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) |  - |
| PP-YOLOE-l | Common Online quantitative     | 640      | - |   6.7ms(trt_int8)  | -- | 48.8     | [link](https://paddledet.bj.bcebos.com/models/slim/ppyoloe_l_coco_qat.pdparams) | -  | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyoloe_l_qat.yml) |
| PP-YOLOv2_R50vd           | baseline                   | 640         |      208.6       |         19.1ms         |           --            |         49.1          |    [link](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams)     |    [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar)     |      [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)       |                                                                    -                                                                     |
| PP-YOLOv2_R50vd           | PACT Online quantitative   | 640         |        --        |         17.3ms         |           --            |         48.1          |     [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams)     |       [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar)        |      [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)       |    [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml)     |
| PP-YOLO_R50vd             | baseline                   | 608         |      183.3       |         17.4ms         |           --            |         44.8          |      [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams)       |      [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar)       |      [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)       |                                                                    -                                                                     |
| PP-YOLO_R50vd             | PACT Online quantitative   | 608         |       67.3       |         13.8ms         |           --            |         44.3          |     [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams)      |        [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar)        |      [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml)       |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_r50vd_qat_pact.yml)     |
| PP-YOLO-MobileNetV3_large | baseline                   | 320         |       18.5       |         2.7ms          |         27.9ms          |         23.2          |       [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams)        |       [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar)        |       [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml)        |                                                                    -                                                                     |
| PP-YOLO-MobileNetV3_large | Common Online quantitative | 320         |       5.6        |           --           |         25.1ms          |         24.3          |     [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams)      |        [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar)        |       [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml)        |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_mbv3_large_qat.yml)     |
| YOLOv3-MobileNetV1        | baseline                   | 608         |       94.2       |         8.9ms          |          332ms          |         29.4          |    [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams)    |    [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar)    |    [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml)    |                                                                    -                                                                     |
| YOLOv3-MobileNetV1        | Common Online quantitative | 608         |       25.4       |         6.6ms          |          248ms          |         30.5          |  [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams)  |    [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar)     |    [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml)    | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v1_qat.yml)  |
| YOLOv3-MobileNetV3        | baseline                   | 608         |       90.3       |         9.4ms          |         367.2ms         |         31.4          | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |                                                                    -                                                                     |
| YOLOv3-MobileNetV3        | PACT Online quantitative   | 608         |       24.4       |         8.0ms          |         280.0ms         |         31.1          |  [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams)  |    [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar)     | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v3_qat.yml)  |
| YOLOv3-DarkNet53          | baseline                   | 608         |      238.2       |         16.0ms         |           --            |         39.0          |     [link](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams)      |     [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar)      |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)      |                                                                    -                                                                     |
| YOLOv3-DarkNet53          | Common Online quantitative | 608         |       78.8       |         12.4ms         |           --            |         38.8          |    [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams)     |       [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar)       |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)      |    [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_darknet_qat.yml)    |
| SSD-MobileNet_v1          | baseline                   | 300         |       22.5       |         4.4ms          |         26.6ms          |         73.8          |    [link](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams)    |    [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar)    |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml)      |                                                                    -                                                                     |
| SSD-MobileNet_v1          | Common Online quantitative | 300         |       7.1        |           --           |         21.5ms          |         72.9          |  [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams)  |    [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar)     |     [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml)      |   [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ssd_mobilenet_v1_qat.yml)   |
| Mask-ResNet50-FPN         | baseline                   | (800, 1333) |      174.1       |        359.5ms         |           --            |       39.2/35.6       |      [link](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams)      |      [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar)      |    [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml)     |                                                                    -                                                                     |
| Mask-ResNet50-FPN         | Common Online quantitative | (800, 1333) |        --        |           --           |           --            | 39.7(+0.5)/35.9(+0.3) |    [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams)    |      [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar)       |    [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml)     | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) |

Description:
- The above V100 prediction delay non-quantified model is tested by TensorRT FP32, and the quantified model is tested by TensorRT INT8, and both of them include NMS time.
- The SD855 predicts the delay for deployment using PaddleLite, using the ARM8 architecture and using 4 Threads (4 Threads) to reason the delay.

### Distillation

#### COCO Benchmark

| Model              | Compression Strategy | Input Size |   Box AP   |                                           Download                                            |                                                       Model Configuration File                                                       |                                                      Compression Strategy Configuration File                                                      |
| ------------------ | -------------------- | ---------- | :--------: | :-------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------: |
| YOLOv3-MobileNetV1 | baseline             | 608        |    29.4    |     [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams)     | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |                                                                         -                                                                         |
| YOLOv3-MobileNetV1 | Distillation         | 608        | 31.0(+1.6) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) |

- For the specific distillation method and more distillation detection models, please refer to [distill](distill/README.md).

### Distillation Pruning Combined Strategy

#### COCO Benchmark

| Model              | Compression Strategy     | Input Size |    GFLOPs    | Model Volume(MB) | Prediction Delay(SD855) |   Box AP   |                                              Download                                               |                                                       Model Configuration File                                                       |                                                          Compression Algorithm Configuration File                                                          |
| ------------------ | ------------------------ | ---------- | :----------: | :--------------: | :---------------------: | :--------: | :-------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------: |
| YOLOv3-MobileNetV1 | baseline                 | 608        |    24.65     |       94.2       |         332.0ms         |    29.4    |        [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams)        | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |                                                                             -                                                                              |
| YOLOv3-MobileNetV1 | Distillation + Tailoring | 608        | 7.54(-69.4%) |   30.9(-67.2%)   |         166.1ms         | 28.4(-1.0) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) |
