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import torch.nn as nn
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from .resample import UpSample1d, DownSample1d
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class Activation1d(nn.Module):
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def __init__(
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self,
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activation,
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up_ratio: int = 2,
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down_ratio: int = 2,
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up_kernel_size: int = 12,
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down_kernel_size: int = 12,
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):
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super().__init__()
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self.up_ratio = up_ratio
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self.down_ratio = down_ratio
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self.act = activation
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self.upsample = UpSample1d(up_ratio, up_kernel_size)
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self.downsample = DownSample1d(down_ratio, down_kernel_size)
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def forward(self, x):
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x = self.upsample(x)
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x = self.act(x)
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x = self.downsample(x)
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return x
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