code: def forward(self, x):
      x = x + self.pe[: x.size(0), :]
      return self.dropout(x)
  
imports: import math
  from typing import Optional, Tuple, Union
  import torch
  import torch.nn
  from darts.logging import get_logger, raise_if, raise_if_not, raise_log
  from darts.models.components import glu_variants, layer_norm_variants
  from darts.models.components.glu_variants import GLU_FFN
  from darts.models.components.transformer import CustomFeedForwardDecoderLayer, CustomFeedForwardEncoderLayer
  from darts.models.forecasting.pl_forecasting_module import PLPastCovariatesModule, io_processor
  from darts.models.forecasting.torch_forecasting_model import PastCovariatesTorchModel
label_desc: Use image node_id 2 for calling the _PositionalEncoding obj's underlying member method code with example usage: obj.forward(x) and returns: self