code: def test_predict_binary(self, monkeypatch, weak_labels):
      class MockPredict:
          calls_count = 0
  
          @classmethod
          def __call__(cls, L_matrix, verbose):
              cls.calls_count += 1
              return np.array([[0.6, 0.4]])
  
      monkeypatch.setattr(
          "flyingsquid.label_model.LabelModel.predict_proba",
          MockPredict(),
      )
  
      weak_labels._label2int = {None: -1, "negative": 0, "positive": 1}
  
      label_model = FlyingSquid(weak_labels=weak_labels)
      label_model.fit()
  
      records = label_model.predict()
  
      assert MockPredict.calls_count == 1
      assert len(records) == 1
      assert records[0].prediction == [
          ("negative", 0.6),
          ("positive", 0.4),
      ]
  
imports: import sys
  import numpy
  import pytest
  from argilla.client.models import TextClassificationRecord
  from argilla.labeling.text_classification import FlyingSquid, Snorkel, WeakLabels, WeakMultiLabels
  from argilla.labeling.text_classification.label_models import LabelModel, MajorityVoter, MissingAnnotationError, NotFittedError, TieBreakPolicy, TooFewRulesError
label_desc: Use image node_id 6 for calling the TestFlyingSquid obj's underlying member method code with example usage: obj.test_predict_binary(monkeypatch, weak_labels) and returns: np