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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}
}
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Dataset used to train amd/resnet50