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pip install -r requirements.txt python eval_onnx.py --onnx_model mnasnet_b1_int.onnx --ipu --provider_config Path\To\vaip_config.json --data_dir /Path/To/Your/Dataset| Metric | Accuracy on IPU |
|---|---|
| Top1/Top5 | 73.51% / 91.56% |
1@misc{rw2019timm,
2 author = {Ross Wightman},
3 title = {PyTorch Image Models},
4 year = {2019},
5 publisher = {GitHub},
6 journal = {GitHub repository},
7 doi = {10.5281/zenodo.4414861},
8 howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
9}1@inproceedings{tan2019mnasnet,
2 title={Mnasnet: Platform-aware neural architecture search for mobile},
3 author={Tan, Mingxing and Chen, Bo and Pang, Ruoming and Vasudevan, Vijay and Sandler, Mark and Howard, Andrew and Le, Quoc V},
4 booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
5 pages={2820--2828},
6 year={2019}
7}