code: def test_ner():
      nlp = stanza.Pipeline(
          **{
              "processors": "tokenize,ner",
              "dir": TEST_MODELS_DIR,
              "lang": "en",
              "logging_level": "error",
          }
      )
      doc = nlp(EN_DOC)
      assert EN_DOC_GOLD == "\n".join(
          [ent.pretty_print() for ent in doc.ents]
      )
  
file_path: stanza/stanza/tests/ner/test_ner_tagger.py
imports: import os
  import pytest
  import stanza
  from stanza.tests import *
  from stanza.models import ner_tagger
  from stanza.utils.confusion import confusion_to_macro_f1
  import stanza.utils.datasets.ner.prepare_ner_file
  from stanza.utils.training.run_ner import build_pretrain_args
label_desc: Use image node_id 1 for calling a global function with example usage: test_ner() without return types