code: def test_decoders(decoder_cls, decoder_params):
      input_spec = FeatureMapsSpecification(
          channels=(64, 128, 256, 512, 1024), strides=(4, 8, 16, 32, 64)
      )
      input = input_spec.get_dummy_input()
  
      decoder = decoder_cls(input_spec, **decoder_params).eval()
      output = decoder(input)
  
      print()
      print(decoder.__class__.__name__)
      print(count_parameters(decoder, human_friendly=True))
      pprint(describe_outputs(output))
  
      torch.jit.trace(decoder, (input,))
  
imports: from pprint import pprint
  import pytest
  import torch
  import pytorch_toolbelt.modules.decoders
  from pytorch_toolbelt.modules.interfaces import FeatureMapsSpecification
  from pytorch_toolbelt.modules.upsample import UpsampleLayerType
  from pytorch_toolbelt.utils.torch_utils import count_parameters, describe_outputs
label_desc: Use image node_id 1 for calling a global function with example usage: test_decoders(decoder_cls, decoder_params) without return types