ixrt

GoogLeNet (ixRT)

Model Description

GoogLeNet is a type of convolutional neural network based on the Inception architecture. It utilises Inception modules, which allow the network to choose between multiple convolutional filter sizes in each block. An Inception network stacks these modules on top of each other, with occasional max-pooling layers with stride 2 to halve the resolution of the grid.

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/googlenet-1378be20.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 googlenet --weight googlenet-1378be20.pth --output checkpoints/googlenet.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/GOOGLENET_CONFIG

FP16

# Accuracy
bash scripts/infer_googlenet_fp16_accuracy.sh
# Performance
bash scripts/infer_googlenet_fp16_performance.sh

INT8

# Accuracy
bash scripts/infer_googlenet_int8_accuracy.sh
# Performance
bash scripts/infer_googlenet_int8_performance.sh

Model Results

Model	BatchSize	Precision	FPS	Top-1(%)	Top-5(%)
GoogLeNet	32	FP16	6470.34	62.456	84.33
GoogLeNet	32	INT8	9358.11	62.106	84.30