# 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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