code: def forward(
      self,
      phones: paddle.Tensor,
      tones: paddle.Tensor,
      speaker_embeddings: paddle.Tensor,
  ):
      outputs = self.synthesizer.infer(
          phones, tones=tones, global_condition=speaker_embeddings
      )
      mel_input = paddle.transpose(
          outputs["mel_outputs_postnet"], [0, 2, 1]
      )
      waveforms = self.vocoder.infer(mel_input)
      return waveforms
  
imports: import importlib
  import os
  from typing import List
  import numpy
  import paddle
  import paddle.nn
  from paddlehub.env import MODULE_HOME
  from paddlehub.module.module import moduleinfo
  from paddlehub.utils.log import logger
  from paddlenlp.data import Pad
  from parakeet.models import ConditionalWaveFlow, Tacotron2
  from parakeet.models.lstm_speaker_encoder import LSTMSpeakerEncoder
  import soundfile
  from .audio_processor import SpeakerVerificationPreprocessor
  from .chinese_g2p import convert_sentence
  from .preprocess_transcription import voc_phones, voc_tones, phone_pad_token, tone_pad_token
label_desc: Use image node_id 4 for calling the VoiceCloner obj's underlying member method code with example usage: obj.forward(phones, tones, speaker_embeddings) and returns: waveforms