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@ -50,7 +50,7 @@ class LayerNorm(nn.LayerNorm):
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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if self._fast_norm:
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if self._fast_norm:
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x = fast_layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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x = fast_layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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else:
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else:
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x = F.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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x = F.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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return x
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return x
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@ -65,7 +65,7 @@ class LayerNorm2d(nn.LayerNorm):
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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x = x.permute(0, 2, 3, 1)
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x = x.permute(0, 2, 3, 1)
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if self._fast_norm:
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if self._fast_norm:
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x = fast_layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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x = fast_layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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else:
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else:
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x = F.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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x = F.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
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x = x.permute(0, 3, 1, 2)
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x = x.permute(0, 3, 1, 2)
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