class_docstr: Basic prediction head that applies a dropout and convolution (without normalization and activation) to the
  feature map with the smallest stride and resize the predicted feature map to the input image size.
code: def get_output_spec(self) -> FeatureMapsSpecification:
      return self.output_spec
  
file_path: pytorch-toolbelt/pytorch_toolbelt/modules/heads/resize.py
imports: from typing import Optional, List, Union, Mapping, Tuple
  import torch.jit
  from torch import nn, Tensor
  from pytorch_toolbelt.modules.interfaces import AbstractHead, FeatureMapsSpecification
label_desc: Use image node_id 3 for calling the ResizeHead obj's underlying member method code with example usage: obj.get_output_spec() and returns: self