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@@ -15,9 +15,11 @@ This version was exported using the old torch to ONNX converter (`torch.onnx.exp
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  **Notes:**
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  1. **Custom FourierUnitJIT**: A custom [FourierUnitJIT](https://github.com/Carve-Photos/lama/blob/main/saicinpainting/training/modules/ffc.py) implementation is used since the original cannot be directly ported to ONNX without overhead. The result is identical to the original model.
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- 2. **Fixed Input Shape**: The input shape is fixed at 800x800 pixels. Although dynamic input shapes are possible, they would require resolving issues with dynamic padding in the `irfft` and `rfftn` functions in `ffc.py`.
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  3. **Opset Version 17**: This model uses opset version 17.
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  ### 2. `lama.onnx` (NOT RECOMMENDED)
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  This version was exported using the new torch to ONNX converter (`torch.onnx.dynamo_export`).
 
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  **Notes:**
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  1. **Custom FourierUnitJIT**: A custom [FourierUnitJIT](https://github.com/Carve-Photos/lama/blob/main/saicinpainting/training/modules/ffc.py) implementation is used since the original cannot be directly ported to ONNX without overhead. The result is identical to the original model.
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+ 2. **Fixed Input Shape**: The input shape is fixed at 512x512 pixels. Although dynamic input shapes are possible, they would require resolving issues with dynamic padding in the `irfft` and `rfftn` functions in `ffc.py`.
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  3. **Opset Version 17**: This model uses opset version 17.
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+ > if you need other resolution - export it using our jupyter notebook.
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+
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  ### 2. `lama.onnx` (NOT RECOMMENDED)
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  This version was exported using the new torch to ONNX converter (`torch.onnx.dynamo_export`).