docstr: Args:
      x: Tensor, shape [seq_len, batch_size, embedding_dim]
docstr_tok: ["Args",":","x",":","Tensor",",","shape","[","seq_len",",","batch_size",",","embedding_dim","]"]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      """
      Args:
          x: Tensor, shape [seq_len, batch_size, embedding_dim]
      """
      x = x + self.pe[: x.size(0)]
      return x
  
imports: import math
  import torch
  import torch.nn.functional
  from open_alpha_tensor.core.modules.attention import AlphaMultiHeadAttention
label_desc: Use image node_id 2 for calling the PositionEncoding obj's underlying member method code with example usage: obj.forward(x) and returns: x