PaddleClas/docs/en/Introduction to Image Classification Model Kunlun (Continuously updated) en_US.md

Introduction to Image Classification Model Kunlun (Continuously updated)

---

Contents

• 1. Foreword
• 2. Training of Kunlun
  • 2.1 ResNet50
  • 2.2 MobileNetV3
  • 2.3 HRNet
  • 2.4 VGG16/19

1. Forword

• This document describes the models currently supported by Kunlun and how to train these models on Kunlun devices. To install PaddlePaddle that supports Kunlun, please refer to install_kunlun(https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/paddle/install/install_Kunlun_zh.md)

2. Training of Kunlun

• See [quick_start](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.3/docs/zh_CN/quick_start/quick_start_ classification_new_user.md) for data sources and pre-trained models. The training effect of Kunlun is aligned with CPU/GPU.

2.1 ResNet50

• Command:

python3.7 ppcls/static/train.py \
    -c ppcls/configs/quick_start/kunlun/ResNet50_vd_finetune_kunlun.yaml \
    -o use_gpu=False \
    -o use_xpu=True \
    -o is_distributed=False

The difference with cpu/gpu training lies in the addition of -o use_xpu=True, indicating that the execution is on a Kunlun device.

2.2 MobileNetV3

• Command：

python3.7 ppcls/static/train.py \
    -c ppcls/configs/quick_start/MobileNetV3_large_x1_0.yaml \
    -o use_gpu=False \
    -o use_xpu=True \
    -o is_distributed=False

2.3 HRNet

• Command：

python3.7 ppcls/static/train.py \
    -c ppcls/configs/quick_start/kunlun/HRNet_W18_C_finetune_kunlun.yaml \
    -o is_distributed=False \
    -o use_xpu=True \
    -o use_gpu=False

2.4 VGG16/19

• Command：

python3.7 ppcls/static/train.py \
    -c ppcls/configs/quick_start/VGG16_finetune_kunlun.yaml \
    -o use_gpu=False \
    -o use_xpu=True \
    -o is_distributed=False
python3.7 ppcls/static/train.py \
    -c ppcls/configs/quick_start/VGG19_finetune_kunlun.yaml \
    -o use_gpu=False \
    -o use_xpu=True \
    -o is_distributed=False