code: def forward(self, x: torch.Tensor, skip: torch.Tensor):
      if self.input_size != self.skip_size:
          skip = self.resample(skip)
  
      if self.trainable_add:
          skip = skip * self.gate(self.mask) * 2.0
  
      output = self.norm(x + skip)
      return output
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from darts.logging import get_logger
  from darts.utils.torch import MonteCarloDropout
label_desc: Use image node_id 2 for calling the _AddNorm obj's underlying member method code with example usage: obj.forward(x, skip) and returns: output