code: def test_hff_dynamic_size():
      feature_maps = [
          torch.randn((4, 3, 512, 512)),
          torch.randn((4, 3, 256, 256)),
          torch.randn((4, 3, 128, 128)),
          torch.randn((4, 3, 64, 64)),
      ]
  
      hff = HFF(upsample_scale=2)
      output = hff(feature_maps)
      assert output.size(2) == 512
      assert output.size(3) == 512
  
imports: import pytest
  import torch
  from pytorch_toolbelt.modules import HFF, ResidualDeconvolutionUpsample2d, GlobalKMaxPool2d
label_desc: Use image node_id 1 for calling a global function with example usage: test_hff_dynamic_size() without return types