code: def test_zero_suggestions(name):
      # Test with a suggester that can return 0 suggestions
      @registry.misc("test_mixed_zero_suggester")
      def make_mixed_zero_suggester():
          def mixed_zero_suggester(docs, *, ops=None):
              if ops is None:
                  ops = get_current_ops()
              spans = []
              lengths = []
              for doc in docs:
                  if len(doc) > 0 and len(doc) % 2 == 0:
                      spans.append((0, 1))
                      lengths.append(1)
                  else:
                      lengths.append(0)
              spans = ops.asarray2i(spans)
              lengths_array = ops.asarray1i(lengths)
              if len(spans) > 0:
                  output = Ragged(ops.xp.vstack(spans), lengths_array)
              else:
                  output = Ragged(
                      ops.xp.zeros((0, 0), dtype="i"), lengths_array
                  )
              return output
  
          return mixed_zero_suggester
  
      fix_random_seed(0)
      nlp = English()
      spancat = nlp.add_pipe(
          name,
          config={
              "suggester": {"@misc": "test_mixed_zero_suggester"},
              "spans_key": SPAN_KEY,
          },
      )
      train_examples = make_examples(nlp)
      optimizer = nlp.initialize(get_examples=lambda: train_examples)
      assert spancat.model.get_dim("nO") == spancat._n_labels
      assert set(spancat.labels) == {"LOC", "PERSON"}
  
      nlp.update(train_examples, sgd=optimizer)
      # empty doc
      nlp("")
      # single doc with zero suggestions
      nlp("one")
      # single doc with one suggestion
      nlp("two two")
      # batch with mixed zero/one suggestions
      list(
          nlp.pipe(
              [
                  "one",
                  "two two",
                  "three three three",
                  "",
                  "four four four four",
              ]
          )
      )
      # batch with no suggestions
      list(nlp.pipe(["", "one", "three three three"]))
  
imports: import numpy
  import pytest
  from numpy.testing import assert_almost_equal, assert_array_equal
  from thinc.api import NumpyOps, Ragged, get_current_ops
  from spacy import util
  from spacy.lang.en import English
  from spacy.language import Language
  from spacy.tokens import SpanGroup
  from spacy.tokens._dict_proxies import SpanGroups
  from spacy.training import Example
  from spacy.util import fix_random_seed, make_tempdir, registry
label_desc: Use image node_id 15 for calling a global function with example usage: test_zero_suggestions(name) and returns: mixed_zero_suggester, output