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# Forward measurement model (Ax + n) y = forward(ref_img, task, mask_type) y_n = noiser(y) # Sampling x_start = torch.randn(ref_img.shape, device=device).requires_grad_() sample = sdedit(model, x_start, measurement=y_n, record=True, save_root=out_path)
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