code: def test_ApplyTransforms_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          default_value=dict(
              argstr="--default-value %g",
              usedefault=True,
          ),
          dimension=dict(
              argstr="--dimensionality %d",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          float=dict(
              argstr="--float %d",
              usedefault=True,
          ),
          input_image=dict(
              argstr="--input %s",
              extensions=None,
              mandatory=True,
          ),
          input_image_type=dict(
              argstr="--input-image-type %d",
          ),
          interpolation=dict(
              argstr="%s",
              usedefault=True,
          ),
          interpolation_parameters=dict(),
          invert_transform_flags=dict(),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_postfix=dict(
              usedefault=True,
          ),
          output_image=dict(
              argstr="--output %s",
              genfile=True,
              hash_files=False,
          ),
          print_out_composite_warp_file=dict(
              requires=["output_image"],
          ),
          reference_image=dict(
              argstr="--reference-image %s",
              extensions=None,
              mandatory=True,
          ),
          transforms=dict(
              argstr="%s",
              mandatory=True,
          ),
      )
      inputs = ApplyTransforms.input_spec()
  
      for key, metadata in list(input_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(inputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_ApplyTransforms_inputs() without return types