ludwig/features/numerical_feature.py [284:317]:
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    @staticmethod
    def calculate_overall_stats(
            test_stats,
            output_feature,
            dataset,
            train_set_metadata
    ):
        pass

    @staticmethod
    def postprocess_results(
            output_feature,
            result,
            metadata,
            experiment_dir_name,
            skip_save_unprocessed_output=False,
    ):
        postprocessed = {}
        name = output_feature['name']

        npy_filename = None
        if is_on_master():
            npy_filename = os.path.join(experiment_dir_name, '{}_{}.npy')
        else:
            skip_save_unprocessed_output = True

        if PREDICTIONS in result and len(result[PREDICTIONS]) > 0:
            postprocessed[PREDICTIONS] = result[PREDICTIONS].numpy()
            if not skip_save_unprocessed_output:
                np.save(
                    npy_filename.format(name, PREDICTIONS),
                    result[PREDICTIONS]
                )
            del result[PREDICTIONS]
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ludwig/features/vector_feature.py [277:310]:
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    @staticmethod
    def calculate_overall_stats(
            test_stats,
            output_feature,
            dataset,
            train_set_metadata
    ):
        pass

    @staticmethod
    def postprocess_results(
            output_feature,
            result,
            metadata,
            experiment_dir_name,
            skip_save_unprocessed_output=False,
    ):
        postprocessed = {}
        name = output_feature['name']

        npy_filename = None
        if is_on_master():
            npy_filename = os.path.join(experiment_dir_name, '{}_{}.npy')
        else:
            skip_save_unprocessed_output = True

        if PREDICTIONS in result and len(result[PREDICTIONS]) > 0:
            postprocessed[PREDICTIONS] = result[PREDICTIONS].numpy()
            if not skip_save_unprocessed_output:
                np.save(
                    npy_filename.format(name, PREDICTIONS),
                    result[PREDICTIONS]
                )
            del result[PREDICTIONS]
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