class_docstr: Deep supervision head takes all feature maps and applies 1x1 convolution to each of them.
code: def get_output_spec(self) -> FeatureMapsSpecification:
      return self.output_spec
  
file_path: pytorch-toolbelt/pytorch_toolbelt/modules/heads/deep_supervision.py
imports: from typing import List, Dict, Optional, Callable
  import torch
  import torch.nn
  from pytorch_toolbelt.datasets import name_for_stride
  from pytorch_toolbelt.modules.simple import conv1x1
  from pytorch_toolbelt.modules.interfaces import AbstractHead, FeatureMapsSpecification
label_desc: Use image node_id 3 for calling the DeepSupervisionHead obj's underlying member method code with example usage: obj.get_output_spec() and returns: self