metadata
license: apache-2.0
datasets:
- imagenet-1k
metrics:
- accuracy
tags:
- RyzenAI
- vision
- classification
- pytorch
ResNet-50 v1.5
Quantized ResNet model that could be supported by AMD Ryzen AI.
Model description
ResNet (Residual Network) was first introduced in the paper Deep Residual Learning for Image Recognition by He et al.
This model is ResNet50 v1.5 from torchvision.
How to use
Installation
Follow Ryzen AI Installation to prepare the environment for Ryzen AI. Run the following script to install pre-requisites for this model.
pip install -r requirements.txt
Data Preparation
Follow PyTorch Example to prepare dataset.
Model Evaluation
python eval_onnx.py --onnx_model ResNet_int.onnx --ipu --provider_config Path\To\vaip_config.json --data_dir /Path/To/Your/Dataset
Performance
Metric | Accuracy on IPU |
---|---|
Top1/Top5 | 76.17% / 92.86% |
@article{He2015,
author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
title={Deep Residual Learning for Image Recognition},
journal={arXiv preprint arXiv:1512.03385},
year={2015}
}