cceae1fee29ec0269616e7c2364f1714a518b2c3,python/src/vmaf/core/quality_runner_extra.py,VmafQualityRunnerWithLocalExplainer,_run_on_asset,#VmafQualityRunnerWithLocalExplainer#Any#,22

Before Change

        feature_result = vmaf_fassembler.results[0]
        model = self._load_model(asset)
        xs = model.get_per_unit_xs_from_a_result(feature_result)
        ys_pred = self.predict_with_model(model, xs)

        if self.optional_dict2 is not None and \
           "explainer" in self.optional_dict2:
            explainer = self.optional_dict2["explainer"]
        else:
            explainer = LocalExplainer()

        exps = explainer.explain(model, xs)
        result_dict = {}
        result_dict.update(feature_result.result_dict) // add feature result
        result_dict[self.get_scores_key()] = ys_pred // add quality score
        result_dict[self.get_explanations_key()] = exps // add local explanations
        return Result(asset, self.executor_id, result_dict)

After Change

        feature_result = vmaf_fassembler.results[0]
        model = self._load_model(asset)
        xs = model.get_per_unit_xs_from_a_result(feature_result)
        ys_pred = self.predict_with_model(model, xs)["ys_pred"]

        if self.optional_dict2 is not None and \
           "explainer" in self.optional_dict2:
            explainer = self.optional_dict2["explainer"]
        else:
            explainer = LocalExplainer()

        exps = explainer.explain(model, xs)
        result_dict = {}
        result_dict.update(feature_result.result_dict) // add feature result
        result_dict[self.get_scores_key()] = ys_pred // add quality score
        result_dict[self.get_explanations_key()] = exps // add local explanations
        return Result(asset, self.executor_id, result_dict)

Instances