class_docstr: Select a single Tensor from the dict or list of output tensors.
  
  Usage example:
      >>> model = MyAwesomeSegmentationModel() # Returns dict {"OUTPUT_MASK": Tensor, ...}
      >>> net  = nn.Sequential(model, SelectByIndex("OUTPUT_MASK"), nn.Sigmoid())
code: def forward(self, outputs: Dict[str, Tensor]) -> Tensor:
      return outputs[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 SelectByIndex obj's underlying member method code with example usage: obj.forward(outputs) and returns: outputs