code: def test_issue7019():
      scores = {
          "LABEL_A": 0.39829102,
          "LABEL_B": 0.938298329382,
          "LABEL_C": None,
      }
      print_textcats_auc_per_cat(msg, scores)
      scores = {
          "LABEL_A": {
              "p": 0.3420302,
              "r": 0.3929020,
              "f": 0.49823928932,
          },
          "LABEL_B": {"p": None, "r": None, "f": None},
      }
      print_prf_per_type(msg, scores, name="foo", type="bar")
  
imports: import random
  import numpy.random
  import pytest
  from numpy.testing import assert_almost_equal
  from thinc.api import Config, compounding, fix_random_seed, get_current_ops
  from wasabi import msg
  import spacy
  from spacy import util
  from spacy.cli.evaluate import print_prf_per_type, print_textcats_auc_per_cat
  from spacy.lang.en import English
  from spacy.language import Language
  from spacy.pipeline import TextCategorizer
  from spacy.pipeline.textcat import single_label_bow_config, single_label_cnn_config, single_label_default_config
  from spacy.pipeline.textcat_multilabel import multi_label_bow_config, multi_label_cnn_config, multi_label_default_config
  from spacy.pipeline.tok2vec import DEFAULT_TOK2VEC_MODEL
  from spacy.scorer import Scorer
  from spacy.tokens import Doc, DocBin
  from spacy.training import Example
  from spacy.training.initialize import init_nlp
  from ..util import make_tempdir
label_desc: Use image node_id 7 for calling a global function with example usage: test_issue7019() without return types