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NPU (HUAWEI Ascend)

Usage

Please refer to link installing mmcv on NPU Devices.

Here we use 8 NPUs on your computer to train the model with the following command:

bash tools/dist_train.sh configs/ssd/ssd300_coco.py 8

Also, you can use only one NPU to train the model with the following command:

python tools/train.py configs/ssd/ssd300_coco.py

Verified Models

Model box AP mask AP Config Download
ssd300 25.6 --- config log
ssd512 29.4 --- config log
*ssdlite-mbv2 20.2 --- config log
retinanet-r50 36.6 --- config log
*fcos-r50 36.1 --- config log
solov2-r50 --- 34.7 config log

Notes:

  • If not specially marked, the results are same between results on the NPU and results on the GPU with FP32.

  • (*) The results on the NPU of these models are aligned with the results of the mixed-precision training on the GPU, but are lower than the results of the FP32. This situation is mainly related to the phase of the model itself in mixed-precision training, users please adjust the hyperparameters to achieve the best result by self.

All above models are provided by Huawei Ascend group.

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