# 1. 推理Benchmark ## 1.1 软硬件环境 - PLSC-ViT模型推理采用GPU的型号为A100,不同的尺度的模型采用了单机8卡或是4机32卡。 ## 1.2 数据集 - 测试使用的数据集为ImageNet. ## 1.3 指标 | Model | Phase | Dataset | gpu | img/sec | Top1 Acc | Official | | --- | --- | --- | --- | --- | --- | --- | | ViT-B_16_224 |pretrain |ImageNet2012 |A100*N1C8 | 3583| 0.75196 | 0.7479 | | ViT-B_16_384 |finetune | ImageNet2012 | A100*N1C8 | 719 | 0.77972 | 0.7791 | | ViT-L_16_224 | pretrain | ImageNet21K | A100*N4C32 | 5256 | - | - | | |ViT-L_16_384 |finetune | ImageNet2012 | A100*N4C32 | 934 | 0.85030 | 0.8505 | # 2. 相关使用说明 https://github.com/PaddlePaddle/PLSC/blob/master/task/classification/vit/README.md
