Introduction to Image Classification Model Kunlun (Continuously updated)¶

Catalogue¶

1. Foreword
2. Training of Kunlun

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

2. Training of Kunlun¶

See quick_startfor 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/kunlun/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/kunlun/VGG19_finetune_kunlun.yaml \
    -o use_gpu=False \
    -o use_xpu=True \
    -o is_distributed=False