docstr: x: (b, 80, s)
docstr_tok: ["x",":","(","b",",","80",",","s",")"]
code: def forward(self, x):
      """
      x: (b, 80, s)
      """
      h = self.init(x)
      h = self.attn(h)
      return h
  
imports: import math
  import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the ConditioningEncoder obj's underlying member method code with example usage: obj.forward(x) and returns: h