def METHOD_NAME(self, cmd):
    itn_result = ''
    if self.framework == Frameworks.torch:
        from fun_text_processing.inverse_text_normalization.inverse_normalize import InverseNormalizer
        if cmd['lang'] == 'ja':
            itn_normalizer = InverseNormalizer(
                lang=cmd['lang'],
                cache_dir=cmd['cache_dir'],
                overwrite_cache=cmd['overwrite_cache'],
                enable_standalone_number=cmd['enable_standalone_number'],
                enable_0_to_9=cmd['enable_0_to_9'])
        else:
            itn_normalizer = InverseNormalizer(
                lang=cmd['lang'],
                cache_dir=cmd['cache_dir'],
                overwrite_cache=cmd['overwrite_cache'])
        itn_result = itn_normalizer.inverse_normalize(
            cmd['text_in'], verbose=cmd['verbose'])
    else:
        raise ValueError('model type is mismatching')
    return itn_result