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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def from_yaml(cls, yaml_str=None, str_or_buffer=None):
 """ Create a SegmentedMNLDiscreteChoiceModel instance from a saved YAML configuration. Arguments are mutally exclusive. Parameters yaml_str : str, optional A YAML string from which to load model. str_or_buffer : str or file like, optional File name or buffer from which to load YAML. Returns ------- SegmentedMNLDiscreteChoiceModel """

        cfg = yamlio.yaml_to_dict(yaml_str, str_or_buffer)

        default_model_expr = cfg['default_config']['model_expression']

        seg = cls(
            cfg['segmentation_col'],
            cfg['sample_size'],
            cfg['probability_mode'],
            cfg['choice_mode'],
            cfg['choosers_fit_filters'],
            cfg['choosers_predict_filters'],
            cfg['alts_fit_filters'],
            cfg['alts_predict_filters'],
            cfg['interaction_predict_filters'],
            cfg['estimation_sample_size'],
            cfg['prediction_sample_size'],
            cfg['choice_column'],
            default_model_expr,
            cfg['remove_alts'],
            cfg['name'])

        if "models" not in cfg:
            cfg["models"] = {}

        for name, m in cfg['models'].items():
            m['model_expression'] = m.get(
                'model_expression', default_model_expr)
            m['sample_size'] = cfg['sample_size']
            m['probability_mode'] = cfg['probability_mode']
            m['choice_mode'] = cfg['choice_mode']
            m['choosers_fit_filters'] = None
            m['choosers_predict_filters'] = None
            m['alts_fit_filters'] = None
            m['alts_predict_filters'] = None
            m['interaction_predict_filters'] = \
                cfg['interaction_predict_filters']
            m['estimation_sample_size'] = cfg['estimation_sample_size']
            m['prediction_sample_size'] = cfg['prediction_sample_size']
            m['choice_column'] = cfg['choice_column']

            model = MNLDiscreteChoiceModel.from_yaml(
                yamlio.convert_to_yaml(m, None))
            seg._group.add_model(model)

        logger.debug(
            'loaded segmented LCM model {} from YAML'.format(seg.name))
        return seg