Fixing typos after rebase.

evalml/pipelines/binary_classification_pipeline.py

@@ -48,6 +48,7 @@ def predict_proba(self, X):
         """
         return super().predict_proba(X)
 
+    @staticmethod
     def _score(X, y, predictions, objective):
         """Given data, model predictions or predicted probabilities computed on the data, and an objective, evaluate and return the objective score.
         """

evalml/pipelines/classification_pipeline.py

@@ -120,8 +120,8 @@ def score(self, X, y, objectives):
             y = pd.Series(y)
 
         objectives = [get_objective(o) for o in objectives]
-        y_predicted, y_predicted_proba = self._compute_predictions(X, objectives)
         y = self._encode_targets(y)
+        y_predicted, y_predicted_proba = self._compute_predictions(X, objectives)
 
         def always_suitable(objective):
             return True

evalml/tests/automl_tests/test_automl.py

@@ -184,22 +184,13 @@ def test_objective_score_raises(mock_score, X_y_binary, caplog):
     X, y = X_y_binary
     automl = AutoMLSearch(problem_type='binary', max_pipelines=1)
 
-    with pytest.raises(PipelineScoreError) as e:
-        automl.search(X, y)
-        out = caplog.text
-
-        assert msg in out
-        assert not np.isnan(e.scored_successfully.values()).any()
-
-    caplog.clear()
-    automl = AutoMLSearch(problem_type='binary', max_pipelines=1)
     automl.search(X, y)
     out = caplog.text
 
     assert msg in out
     pipeline_results = automl.results.get('pipeline_results')
     assert len(pipeline_results) == 1
-    cv_scores_all = pipeline_results[0].get('cv_data')
+    cv_scores_all = pipeline_results[0].get('cv_data')  # {})
     scores = cv_scores_all[0]['all_objective_scores']
     auc_score = scores.pop('AUC')
     assert np.isnan(auc_score)