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	| # Copyright (c) 2023 Amphion. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import torch.nn as nn | |
| from .resample import * | |
| # This code is adopted from BigVGAN under the MIT License | |
| # https://github.com/NVIDIA/BigVGAN | |
| class Activation1d(nn.Module): | |
| def __init__( | |
| self, | |
| activation, | |
| up_ratio: int = 2, | |
| down_ratio: int = 2, | |
| up_kernel_size: int = 12, | |
| down_kernel_size: int = 12, | |
| ): | |
| super().__init__() | |
| self.up_ratio = up_ratio | |
| self.down_ratio = down_ratio | |
| self.act = activation | |
| self.upsample = UpSample1d(up_ratio, up_kernel_size) | |
| self.downsample = DownSample1d(down_ratio, down_kernel_size) | |
| # x: [B,C,T] | |
| def forward(self, x): | |
| x = self.upsample(x) | |
| x = self.act(x) | |
| x = self.downsample(x) | |
| return x | |
