class_docstr: ### Scale up the feature map by $2  imes$
class_docstr_tok: ["#","#","#","Scale","up","the","feature","map","by","$","2","imes","$"]
code: def forward(self, x: torch.Tensor, t: torch.Tensor):
      # `t` is not used, but it's kept in the arguments because for the attention layer function signature
      # to match with `ResidualBlock`.
      _ = t
      return self.conv(x)
  
imports: import math
  from typing import Optional, Tuple, Union, List
  import torch
  from torch import nn
  from labml_helpers.module import Module
label_desc: Use image node_id 2 for calling the Upsample obj's underlying member method code with example usage: obj.forward(x, t) and returns: self