4.0 KiB
4.0 KiB
NPU (HUAWEI Ascend)
Usage
Please install MMCV with NPU device support according to {external+mmcv:doc}the tutorial <get_started/build>.
Here we use 8 NPUs on your computer to train the model with the following command:
bash tools/dist_train.sh configs/cspnet/resnet50_8xb32_in1k.py 8 --device npu
Also, you can use only one NPU to trian the model with the following command:
python tools/train.py configs/cspnet/resnet50_8xb32_in1k.py --device npu
Verified Models
| Model | Top-1 (%) | Top-5 (%) | Config | Download |
|---|---|---|---|---|
| CSPResNeXt50 | 77.10 | 93.55 | config | model | log |
| DenseNet121 | 72.62 | 91.04 | config | model | log |
| EfficientNet-B4(AA + AdvProp) | 75.55 | 92.86 | config | model | log |
| HRNet-W18 | 77.01 | 93.46 | config | model | log |
| ResNetV1D-152 | 77.11 | 94.54 | config | model | log |
| ResNet-50 | 76.40 | - | config | model | log |
| ResNetXt-32x4d-50 | 77.55 | 93.75 | config | model | log |
| SE-ResNet-50 | 77.64 | 93.76 | config | model | log |
| VGG-11 | 68.92 | 88.83 | config | model | log |
| ShuffleNetV2 1.0x | 69.53 | 88.82 | config | model | log |
All above models are provided by Huawei Ascend group.