code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      # residual connection
      x = self.dense(x) + self.skip(x)
  
      # layer normalization
      if self.layer_norm is not None:
          x = self.layer_norm(x)
  
      return x
  
file_path: darts/darts/models/forecasting/tide_model.py
imports: from typing import Optional, Tuple
  import torch
  import torch.nn
  from darts.logging import get_logger, raise_log
  from darts.models.forecasting.pl_forecasting_module import PLMixedCovariatesModule, io_processor
  from darts.models.forecasting.torch_forecasting_model import MixedCovariatesTorchModel
label_desc: Use image node_id 2 for calling the _ResidualBlock obj's underlying member method code with example usage: obj.forward(x) and returns: x