class_docstr: Learns a position embedding
class_docstr_tok: ["Learns","a","position","embedding"]
code: def forward(self, x):
      timing = self.timing_table[: x.shape[1], :]
      timing = timing.expand(x.shape[0], -1, -1)
      out = torch.cat([x, timing], dim=-1)
      return out
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from stanza.models.constituency.positional_encoding import ConcatSinusoidalEncoding
label_desc: Use image node_id 2 for calling the ConcatPositionalEncoding obj's underlying member method code with example usage: obj.forward(x) and returns: out