From 9135a1137168be8d9174aac96bbcae51482683e1 Mon Sep 17 00:00:00 2001 From: gaotingquan Date: Thu, 16 Dec 2021 08:52:07 +0000 Subject: [PATCH] docs: update benchmark curve --- docs/en/ImageNet_models_en.md | 11 +++++++---- docs/en/models/models_intro_en.md | 7 +++---- .../v100.fp32.bs1.main_fps_top1_s.jpg | Bin 165523 -> 0 bytes .../v100.fp32.bs1.main_fps_top1_s.png | Bin 0 -> 375984 bytes .../v100.fp32.bs1.visiontransformer.png | Bin 0 -> 259727 bytes docs/images/models/mobile_arm_top1.png | Bin 143928 -> 365611 bytes .../algorithm_introduction/ImageNet_models.md | 7 +++++-- docs/zh_CN/models/models_intro.md | 7 +++---- 8 files changed, 18 insertions(+), 14 deletions(-) delete mode 100644 docs/images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.jpg create mode 100644 docs/images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png create mode 100644 docs/images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png diff --git a/docs/en/ImageNet_models_en.md b/docs/en/ImageNet_models_en.md index 9a2f0b95..a3471c5f 100644 --- a/docs/en/ImageNet_models_en.md +++ b/docs/en/ImageNet_models_en.md @@ -8,14 +8,17 @@ Based on the ImageNet-1k classification dataset, the 35 classification network s Curves of accuracy to the inference time of common server-side models are shown as follows. -![](../images/models/T4_benchmark/t4.fp32.bs1.main_fps_top1.png) - +![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png) Curves of accuracy to the inference time and storage size of common mobile-side models are shown as follows. -![](../images/models/mobile_arm_storage.png) +![](../../images/models/mobile_arm_storage.png) + +![](../../images/models/mobile_arm_top1.png) + +Curves of accuracy to the inference time of some VisionTransformer models are shown as follows. -![](../images/models/mobile_arm_top1.png) +![](../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png) ### SSLD pretrained models diff --git a/docs/en/models/models_intro_en.md b/docs/en/models/models_intro_en.md index 677d742d..f932adae 100644 --- a/docs/en/models/models_intro_en.md +++ b/docs/en/models/models_intro_en.md @@ -5,7 +5,7 @@ Based on the ImageNet1k classification dataset, the 29 classification network structures supported by PaddleClas and the corresponding 134 image classification pretrained models are shown below. Training trick, a brief introduction to each series of network structures, and performance evaluation will be shown in the corresponding chapters. ## Evaluation environment -* CPU evaluation environment is based on Snapdragon 855 (SD855). +* Arm evaluation environment is based on Snapdragon 855 (SD855). * The GPU evaluation environment is based on V100 and TensorRT, and the evaluation script is as follows. ```shell @@ -23,12 +23,11 @@ python tools/infer/predict.py \ --batch_size=1 ``` -![](../../images/models/T4_benchmark/t4.fp32.bs4.main_fps_top1.png) - -![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.jpg) +![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png) ![](../../images/models/mobile_arm_top1.png) +![](../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png) > If you think this document is helpful to you, welcome to give a star to our project:[https://github.com/PaddlePaddle/PaddleClas](https://github.com/PaddlePaddle/PaddleClas) diff --git a/docs/images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.jpg b/docs/images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.jpg deleted file mode 100644 index 44a101c67b250c15b239b162cbf6311c1277d962..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 165523 zcmeFZby!yG*ENdW9T>z`2?Z4a0cn#GP>@cQlI|`W6ajevX%M7Sx&+?zUMvX7-NpPUfmTJ+_Uq1jXw%Ryeq65f>BFe}3Vjp@|mL z#LcV(GP1wOgl}GxvI-pUw6&|9TU-0JY&+CiQW99=pIZAf)Sjf~HX!Hrf%&tb5H07e z7kbp^VpRFWPkGOIi$v2fnEdu#l!`v^xq;&0A!ers7FMgPEdwh{zPq;C5Ab273X@vEOH|NVmguim}?eE#^* zTcd6Nd|tFeDC^%p=-Euu@$V}cZ9F*n@1I`Tu*34-&jTMn=l=Ke|9*L_#D6ai7U91m z2aE9kmt%F6{G!sgFRuS_96L1eEU z@uNqML<|oPD-8q(2k+dyyMcf8*S@)lc3EEA`Mj7{p3ctO?H31pNHlnR?+c1Dr2ffC zhx&(~6ATxp2S&etaH1)1Y?OZTW%y|hfBLn67goZl|tG4#bILiu}eMvo)fq{ zG9&uaNZLhWJwJYgwWaHhxiA&nP1k9p5uO>Ul@$;u+2cO&`Nb|0jjC$*Nj`Q1L#6f9 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zqj@ngwgJU3XE9Qjc`aM~W=wXZ&j$WRjKkK55iv6{{{Q9w@-#e;zv30WJ?_bwDGB3k Mg({}~jm*#g1vlfN%>V!Z diff --git a/docs/zh_CN/algorithm_introduction/ImageNet_models.md b/docs/zh_CN/algorithm_introduction/ImageNet_models.md index f747e81e..8fb8aaca 100644 --- a/docs/zh_CN/algorithm_introduction/ImageNet_models.md +++ b/docs/zh_CN/algorithm_introduction/ImageNet_models.md @@ -44,8 +44,7 @@ 常见服务器端模型的精度指标与其预测耗时的变化曲线如下图所示。 -![](../../images/models/T4_benchmark/t4.fp32.bs1.main_fps_top1.png) - +![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png) 常见移动端模型的精度指标与其预测耗时、模型存储大小的变化曲线如下图所示。 @@ -53,6 +52,10 @@ ![](../../images/models/mobile_arm_top1.png) +部分VisionTransformer模型的精度指标与其预测耗时的变化曲线如下图所示。 + +![](../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png) + ## 2. SSLD 知识蒸馏预训练模型 diff --git a/docs/zh_CN/models/models_intro.md b/docs/zh_CN/models/models_intro.md index 0c30be7e..b141a8af 100644 --- a/docs/zh_CN/models/models_intro.md +++ b/docs/zh_CN/models/models_intro.md @@ -16,17 +16,16 @@ ## 2. 评估环境 -* CPU 的评估环境基于骁龙 855(SD855)。 +* Arm 的评估环境基于骁龙 855(SD855)。 * Intel CPU 的评估环境基于 Intel(R) Xeon(R) Gold 6148。 * GPU 评估环境基于 V100 和 TensorRT。 -![](../../images/models/T4_benchmark/t4.fp32.bs4.main_fps_top1.png) - -![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.jpg) +![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png) ![](../../images/models/mobile_arm_top1.png) +![](../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png) > 如果您觉得此文档对您有帮助,欢迎 star 我们的项目:[https://github.com/PaddlePaddle/PaddleClas](https://github.com/PaddlePaddle/PaddleClas) -- GitLab