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| images = np.zeros((1, 3, 360, 640), dtype=np.float32) | |
| masks = np.ones((1, 1, 360, 640), dtype=np.float32) | |
| torch.onnx.export(nnet.model, | |
| (images, masks), | |
| "model_float32.onnx", | |
| export_params=True, | |
| opset_version=11, | |
| do_constant_folding=True, | |
| input_names = ['input_rgb','input_mask'], | |
| output_names = ['pred_logits', 'pred_curves','foo_out_1', 'foo_out_2','weights']) |
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