def METHOD_NAME(self, x):
    module_device = x.device
    downcast_x = _cast_if_autocast_enabled(x)
    downcast_weight = _cast_if_autocast_enabled(self.weight) if self.weight is not None else self.weight
    downcast_bias = _cast_if_autocast_enabled(self.bias) if self.bias is not None else self.bias
    with torch.autocast(enabled=False, device_type=module_device.type):
        return F.layer_norm(downcast_x, self.normalized_shape, downcast_weight, downcast_bias, self.eps)