ixrt

EfficientNet B0 (ixRT)

Model Description

EfficientNet B0 is a convolutional neural network architecture that belongs to the EfficientNet family, which was introduced by Mingxing Tan and Quoc V. Le in their paper "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks." The EfficientNet family is known for achieving state-of-the-art performance on various computer vision tasks while being more computationally efficient than many existing models.

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_b0_rwightman-3dd342df.pth

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

Install Dependencies

# Install libGL
## CentOS
yum install -y mesa-libGL
## Ubuntu
apt install -y libgl1-mesa-glx

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

Model Conversion

mkdir checkpoints
python3 ../../ixrt_common/export.py --model-name efficientnet_b0 --weight /path/to/efficientnet_b0_rwightman-3dd342df.pth --output checkpoints/efficientnet_b0.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_B0_CONFIG

FP16

# Accuracy
bash scripts/infer_efficientnet_b0_fp16_accuracy.sh
# Performance
bash scripts/infer_efficientnet_b0_fp16_performance.sh

INT8

# Accuracy
bash scripts/infer_efficientnet_b0_int8_accuracy.sh
# Performance
bash scripts/infer_efficientnet_b0_int8_performance.sh

Model Results

Model	BatchSize	Precision	FPS	Top-1(%)	Top-5(%)
EfficientNet B0	32	FP16	2325.54	77.66	93.58
EfficientNet B0	32	INT8	2666.00	74.27	91.85