code: def test_entity_ruler_remove_all_patterns(nlp, entity_ruler_factory):
      ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
      patterns = [
          {"label": "PERSON", "pattern": "Dina", "id": "dina"},
          {"label": "ORG", "pattern": "ACME", "id": "acme"},
          {"label": "DATE", "pattern": "her birthday", "id": "bday"},
      ]
      ruler.add_patterns(patterns)
      assert len(ruler.patterns) == 3
      if isinstance(ruler, EntityRuler):
          ruler.remove("dina")
      else:
          ruler.remove_by_id("dina")
      assert len(ruler.patterns) == 2
      if isinstance(ruler, EntityRuler):
          ruler.remove("acme")
      else:
          ruler.remove_by_id("acme")
      assert len(ruler.patterns) == 1
      if isinstance(ruler, EntityRuler):
          ruler.remove("bday")
      else:
          ruler.remove_by_id("bday")
      assert len(ruler.patterns) == 0
      with pytest.warns(UserWarning):
          doc = nlp("Dina founded her company ACME on her birthday")
          assert len(doc.ents) == 0
  
imports: import pytest
  from thinc.api import NumpyOps, get_current_ops
  from spacy import registry
  from spacy.errors import MatchPatternError
  from spacy.lang.en import English
  from spacy.language import Language
  from spacy.pipeline import EntityRecognizer, EntityRuler, SpanRuler, merge_entities
  from spacy.pipeline.ner import DEFAULT_NER_MODEL
  from spacy.tests.util import make_tempdir
  from spacy.tokens import Doc, Span
label_desc: Use image node_id 35 for calling a global function with example usage: test_entity_ruler_remove_all_patterns(nlp, entity_ruler_factory) without return types