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37 lines
3.8 KiB
Markdown
37 lines
3.8 KiB
Markdown
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# NPU (HUAWEI Ascend)
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## Usage
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Please refer to the [building documentation of MMCV](https://mmcv.readthedocs.io/en/latest/get_started/build.html#build-mmcv-full-on-ascend-npu-machine) to install MMCV and [MMEngine](https://mmengine.readthedocs.io/en/latest/get_started/installation.html#build-from-source) on NPU devices.
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Here we use 4 NPUs on your computer to train the model with the following command:
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```shell
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bash tools/dist_train.sh configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py 4
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```
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Also, you can use only one NPU to train the model with the following command:
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```shell
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python tools/train.py configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py
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```
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## Models Results
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| Model | mIoU | Config | Download |
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| :-----------------: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------- |
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| [deeplabv3](<>) | 78.92 | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/deeplabv3_r50-d8_512x1024_40k_cityscapes.log.json) |
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| [deeplabv3plus](<>) | 79.68 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.log.json) |
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| [hrnet](<>) | 77.09 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18_512x1024_40k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/fcn_hr18_512x1024_40k_cityscapes.log.json) |
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| [fcn](<>) | 72.69 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/fcn_r50-d8_512x1024_40k_cityscapes.log.json) |
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| [pspnet](<>) | 78.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/pspnet_r50-d8_512x1024_80k_cityscapes.log.json) |
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| [unet](<>) | 69.00 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.log.json) |
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| [apcnet](<>) | 78.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/apcnet/apcnet_r50-d8_512x1024_40k_cityscapes.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/apcnet_r50-d8_512x1024_40k_cityscapes.log.json) |
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| [upernet](<>) | 78.22 | [config](https://github.com/open-mmlab/mmsegmentation/tree/1.x/configs/upernet/upernet_r50_4xb2-40k_cityscapes-512x1024.py) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/device/npu/upernet_r50_512x1024_40k_cityscapes.log.json) |
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**Notes:**
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- If not specially marked, the results on NPU with amp are the basically same as those on the GPU with FP32.
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**All above models are provided by Huawei Ascend group.**
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