def recognize(self, inputs: schemas.PredictInput, max_tokens_per_frame: int = 3, **kwargs):
        """
        Recognize greedy from input signals

        Parameters
        ----------
        inputs : schemas.PredictInput

        Returns
        -------
        named tuple of
            (
                tokens, will be feed to text_featurizer.detokenize or text_featurizer.detokenize_unicode_points,
                next_encoder_states, if encoder does not have states, returns None, will be used to predict next chunk of audio,
                next_tokens, will be used to predict next chunk of audio,
                next_decoder_states, next states of predict_net, will be used to predict next chunk of audio,
            )
        """
        if self._batch_size == 1:
            return self.recognize_single(inputs, max_tokens_per_frame=max_tokens_per_frame, **kwargs)
        return self.recognize_batch(inputs, **kwargs)

        Recognize greedy from input signals

        Parameters
        ----------
        inputs : schemas.PredictInput

        Returns
        -------
        named tuple of
            (
                tokens, will be feed to text_featurizer.detokenize or text_featurizer.detokenize_unicode_points,
                next_encoder_states, if encoder does not have states, returns None, will be used to predict next chunk of audio,
                next_tokens, will be used to predict next chunk of audio,
                next_decoder_states, next states of predict_net, will be used to predict next chunk of audio,
            )
        
tensorflow_asr/models/transducer/base_transducer.py