docstr: Returns dummy input for this feature map specification
  :return: Dummy input tensor
docstr_tok: ["Returns","dummy","input","for","this","feature","map","specification",":","return",":","Dummy","input","tensor"]
code: def get_dummy_input(
      self, device=None, image_size=(640, 512)
  ) -> List[Tensor]:
      """
      Returns dummy input for this feature map specification
      :return: Dummy input tensor
      """
      feature_maps = []
      rows, cols = image_size
      for c, s in zip(self.channels, self.strides):
          feature_maps.append(
              torch.randn((1, c, rows // s, cols // s), device=device)
          )
      return feature_maps
  
imports: import dataclasses
  from abc import abstractmethod
  from typing import Protocol, Tuple, List, Union, Mapping, Callable
  import numpy
  import torch.jit
  from torch import nn, Tensor
  from pytorch_toolbelt.utils import pytorch_toolbelt_deprecated
label_desc: Use image node_id 3 for calling the FeatureMapsSpecification obj's underlying member method code with example usage: obj.get_dummy_input(device, image_size) and returns: feature_maps