ixrt

EfficientNet_v2_s (ixRT)

Model Description

EfficientNetV2 S is an optimized model in the EfficientNetV2 series, which was developed by Google researchers. It continues the legacy of the EfficientNet family, focusing on advancing the state-of-the-art in accuracy and efficiency through advanced scaling techniques and architectural innovations.

Supported Environments

GPU	IXUCA SDK	Release	Branch
MR-V100	4.4.0	26.03	release/26.03
MR-V100	4.3.0	25.12	release/25.12

Note: 请切换到与您的 SDK 版本对应的 Release 分支进行测试。请勿直接在 master 分支上运行测试，因为 master 分支可能包含与您的本地 SDK 版本不兼容的最新更改。

切换分支命令示例：git checkout release/26.03

Model Preparation

Prepare Resources

Pretrained model: https://download.pytorch.org/models/efficientnet_v2_s-dd5fe13b.pth

Dataset: https://www.image-net.org/download.php to download the validation dataset.

Install Dependencies

pip3 install -r ../../ixrt_common/requirements.txt

Model Conversion

mkdir checkpoints
python3 ../../ixrt_common/export.py --model-name efficientnet_v2_s --weight efficientnet_v2_s-dd5fe13b.pth --output checkpoints/efficientnet_v2_s.onnx

Model Inference

export PROJ_DIR=./
export DATASETS_DIR=/path/to/imagenet_val/
export CHECKPOINTS_DIR=./checkpoints
export RUN_DIR=../../ixrt_common/
export CONFIG_DIR=../../ixrt_common/config/EFFICIENTNET_V2_S_CONFIG

FP16

# Accuracy
bash scripts/infer_efficientnet_v2_s_fp16_accuracy.sh
# Performance
bash scripts/infer_efficientnet_v2_s_fp16_performance.sh

Model Results

Model	BatchSize	Precision	FPS	Top-1(%)	Top-5(%)
Efficientnet_v2_s	32	FP16	2020.388	81.312	95.288