(window_size, sigma)
| 30 | |
| 31 | |
| 32 | def gaussian(window_size, sigma): |
| 33 | gauss = torch.Tensor([exp(-(x - window_size // 2) ** 2 / float(2 * sigma ** 2)) for x in range(window_size)]) |
| 34 | return gauss / gauss.sum() |
| 35 | |
| 36 | |
| 37 | def create_window(window_size, channel): |