# QAT.axera

**Repository Path**: axera-opensource/QAT.axera

## Basic Information

- **Project Name**: QAT.axera
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-09-14
- **Last Updated**: 2025-09-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# QAT.axera

axera QAT demo
包含一个最小导出 demo 和一个 resnet50 训练 demo

## minimum export demo

```bash
python -m minimum.minimum_demo
```

## resnet50 train

```bash
# download imagenet dataset
cd QAT.axera
mkdir -p dataset/imagenet && cd dataset/imagenet
wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_train.tar --no-check-certificate
wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar --no-check-certificate
wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_devkit_t12.tar.gz --no-check-certificate

# download resnet50 pretrained model
cd QAT.axera
wget -O resnet50/resnet50_pretrained_float.pth https://download.pytorch.org/models/resnet50-0676ba61.pth

# train
cd QAT.axera
mkdir -p resnet50/checkpoint
python -m resnet50.train
# 4bit 量化位宽时参考 resnet50/config_4w4f 配置，并用 simplify_and_fix_4bit_dtype 替代 onnx_simplify

# test
cd QAT.axera
python -m resnet50.test
```

## Validate on board

[请点击查看上板测试文档。](pulsar2/README.md)