class_docstr: Expand the `target` to match the `output` size before applying `crit`.
class_docstr_tok: ["Expand","the","`","target","`","to","match","the","`","output","`","size","before","applying","`","crit","`","."]
code: def forward(self, output: Tensor, target: Tensor):
      return self.crit(
          output, target[:, None].expand_as(output).float()
      )
  
imports: from __future__ import annotations
  from ..basics import *
  from .all import *
label_desc: Use image node_id 2 for calling the AdaptiveLoss obj's underlying member method code with example usage: obj.forward(output, target) and returns: self