fixtures.py 文件源码

def add_file(prediction, create, value, *args, **kwargs):
        train_featureset = prediction.model.featureset
        fset_data, data = featurize.load_featureset(train_featureset.file_uri)
        if 'class' in prediction.dataset.name or 'regr' in prediction.dataset.name:
            labels = data['labels']
        else:
            labels = []
        model_data = joblib.load(prediction.model.file_uri)
        if hasattr(model_data, 'best_estimator_'):
            model_data = model_data.best_estimator_
        preds = model_data.predict(fset_data)
        pred_probs = (pd.DataFrame(model_data.predict_proba(fset_data),
                                   index=fset_data.index.astype(str),
                                   columns=model_data.classes_)
                      if hasattr(model_data, 'predict_proba') else [])
        all_classes = model_data.classes_ if hasattr(model_data, 'classes_') else []
        pred_path = pjoin(TMP_DIR, '{}.npz'.format(str(uuid.uuid4())))
        featurize.save_featureset(fset_data, pred_path, labels=labels,
                                  preds=preds, pred_probs=pred_probs)
        prediction.file_uri = pred_path
        DBSession().commit()