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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| # author: adefossez | |
| import math | |
| import torch as th | |
| from torch.nn import functional as F | |
| def sinc(t): | |
| """sinc. | |
| :param t: the input tensor | |
| """ | |
| return th.where(t == 0, th.tensor(1., device=t.device, dtype=t.dtype), | |
| th.sin(t) / t) | |
| def kernel_upsample2(zeros=56): | |
| """kernel_upsample2. | |
| """ | |
| win = th.hann_window(4 * zeros + 1, periodic=False) | |
| winodd = win[1::2] | |
| t = th.linspace(-zeros + 0.5, zeros - 0.5, 2 * zeros) | |
| t *= math.pi | |
| kernel = (sinc(t) * winodd).view(1, 1, -1) | |
| return kernel | |
| def upsample2(x, zeros=56): | |
| """ | |
| Upsampling the input by 2 using sinc interpolation. | |
| Smith, Julius, and Phil Gossett. "A flexible sampling-rate conversion method." | |
| ICASSP'84. IEEE International Conference on Acoustics, Speech, and Signal Processing. | |
| Vol. 9. IEEE, 1984. | |
| """ | |
| *other, time = x.shape | |
| kernel = kernel_upsample2(zeros).to(x) | |
| out = F.conv1d(x.view(-1, 1, time), kernel, padding=zeros)[..., 1:].view( | |
| *other, time | |
| ) | |
| y = th.stack([x, out], dim=-1) | |
| return y.view(*other, -1) | |
| def kernel_downsample2(zeros=56): | |
| """kernel_downsample2. | |
| """ | |
| win = th.hann_window(4 * zeros + 1, periodic=False) | |
| winodd = win[1::2] | |
| t = th.linspace(-zeros + 0.5, zeros - 0.5, 2 * zeros) | |
| t.mul_(math.pi) | |
| kernel = (sinc(t) * winodd).view(1, 1, -1) | |
| return kernel | |
| def downsample2(x, zeros=56): | |
| """ | |
| Downsampling the input by 2 using sinc interpolation. | |
| Smith, Julius, and Phil Gossett. "A flexible sampling-rate conversion method." | |
| ICASSP'84. IEEE International Conference on Acoustics, Speech, and Signal Processing. | |
| Vol. 9. IEEE, 1984. | |
| """ | |
| if x.shape[-1] % 2 != 0: | |
| x = F.pad(x, (0, 1)) | |
| xeven = x[..., ::2] | |
| xodd = x[..., 1::2] | |
| *other, time = xodd.shape | |
| kernel = kernel_downsample2(zeros).to(x) | |
| out = xeven + F.conv1d( | |
| xodd.view(-1, 1, time), kernel, padding=zeros | |
| )[..., :-1].view(*other, time) | |
| return out.view(*other, -1).mul(0.5) | |