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Retrieval-based-Voice-Conve…/rvc/norms.py
2024-06-07 20:28:05 +09:00

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Python

import torch
from torch import nn
from torch.nn import functional as F
class LayerNorm(nn.Module):
def __init__(self, channels: int, eps: float = 1e-5):
super(LayerNorm, self).__init__()
self.channels = channels
self.eps = eps
self.gamma = nn.Parameter(torch.ones(channels))
self.beta = nn.Parameter(torch.zeros(channels))
def forward(self, x: torch.Tensor):
x = x.transpose(1, -1)
x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
return x.transpose(1, -1)