code: def test_Normalize12_inputs():
      input_map = dict(
          affine_regularization_type=dict(
              field="eoptions.affreg",
          ),
          apply_to_files=dict(
              copyfile=True,
              field="subj.resample",
          ),
          bias_fwhm=dict(
              field="eoptions.biasfwhm",
          ),
          bias_regularization=dict(
              field="eoptions.biasreg",
          ),
          deformation_file=dict(
              copyfile=False,
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
              field="subj.def",
              mandatory=True,
              xor=["image_to_align", "tpm"],
          ),
          image_to_align=dict(
              copyfile=True,
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
              field="subj.vol",
              mandatory=True,
              xor=["deformation_file"],
          ),
          jobtype=dict(
              usedefault=True,
          ),
          matlab_cmd=dict(),
          mfile=dict(
              usedefault=True,
          ),
          out_prefix=dict(
              field="woptions.prefix",
              usedefault=True,
          ),
          paths=dict(),
          sampling_distance=dict(
              field="eoptions.samp",
          ),
          smoothness=dict(
              field="eoptions.fwhm",
          ),
          tpm=dict(
              copyfile=False,
              extensions=None,
              field="eoptions.tpm",
              xor=["deformation_file"],
          ),
          use_mcr=dict(),
          use_v8struct=dict(
              min_ver="8",
              usedefault=True,
          ),
          warping_regularization=dict(
              field="eoptions.reg",
          ),
          write_bounding_box=dict(
              field="woptions.bb",
          ),
          write_interp=dict(
              field="woptions.interp",
          ),
          write_voxel_sizes=dict(
              field="woptions.vox",
          ),
      )
      inputs = Normalize12.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_Normalize12_inputs() without return types