class_docstr: Wraps a model that returns dict or list and returns only a specific element.
  
  Usage example:
      >>> model = MyAwesomeSegmentationModel() # Returns dict {"OUTPUT_MASK": Tensor, ...}
      >>> net  = nn.Sequential(PickModelOutput(model, "OUTPUT_MASK")), nn.Sigmoid())
code: def forward(self, *input, **kwargs) -> Tensor:
      output = self.model(*input, **kwargs)
      return output[self.target_key]
  
imports: import torch
  from torch import nn, Tensor
  from typing import List, Union, Iterable, Optional, Dict, Tuple
  from pytorch_toolbelt.inference.tta import _deaugment_averaging
label_desc: Use image node_id 2 for calling the PickModelOutput obj's underlying member method code with example usage: obj.forward() and returns: output