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feat: add instructions to export to onnx
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.vscode/launch.json
vendored
2
.vscode/launch.json
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@ -17,7 +17,7 @@
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// "--ckpt_path",
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// "--ckpt_path",
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// "${workspaceFolder}/lightning_logs/version_264/checkpoints/epoch=9-st&ep=1000.ckpt",
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// "${workspaceFolder}/lightning_logs/version_264/checkpoints/epoch=9-st&ep=1000.ckpt",
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"--data.num_workers",
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"--data.num_workers",
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"0",
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"1",
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"--trainer.benchmark",
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"--trainer.benchmark",
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"false",
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"false",
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"--trainer.num_sanity_val_steps",
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"--trainer.num_sanity_val_steps",
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11
README.md
11
README.md
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@ -28,6 +28,17 @@ Start inference on images:
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python src/main.py predict --ckpt_path <path_to_checkpoint>
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python src/main.py predict --ckpt_path <path_to_checkpoint>
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```
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```
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Quick and dirty way to export to `.onnx`:
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```python
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>>> from src.module import DETR
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>>> checkpoint = "<path_to_checkpoint>"
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>>> model = DETR.load_from_checkpoint(checkpoint)
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>>> model.net.save_pretrained("hugginface_checkpoint")
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```
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```bash
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python -m transformers.onnx --model=hugginface_checkpoint onnx_export/
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```
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## License
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## License
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Distributed under the [MIT](https://choosealicense.com/licenses/mit/) license. \
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Distributed under the [MIT](https://choosealicense.com/licenses/mit/) license. \
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