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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