code: def get_aux_input(self, aux_input: Dict):
      sid, g, lid, _ = self._set_cond_input(aux_input)
      return {
          "speaker_ids": sid,
          "style_wav": None,
          "d_vectors": g,
          "language_ids": lid,
      }
  
imports: from typing import Callable, Dict, Tuple
  import torch
  import torch.nn.functional
  from coqpit import Coqpit
  from torch import nn
  from TTS.tts.layers.delightful_tts.conformer import Conformer
  from TTS.tts.layers.delightful_tts.encoders import PhonemeLevelProsodyEncoder, UtteranceLevelProsodyEncoder, get_mask_from_lengths
  from TTS.tts.layers.delightful_tts.energy_adaptor import EnergyAdaptor
  from TTS.tts.layers.delightful_tts.networks import EmbeddingPadded, positional_encoding
  from TTS.tts.layers.delightful_tts.phoneme_prosody_predictor import PhonemeProsodyPredictor
  from TTS.tts.layers.delightful_tts.pitch_adaptor import PitchAdaptor
  from TTS.tts.layers.delightful_tts.variance_predictor import VariancePredictor
  from TTS.tts.layers.generic.aligner import AlignmentNetwork
  from TTS.tts.utils.helpers import generate_path, maximum_path, sequence_mask
label_desc: Use image node_id 4 for calling the AcousticModel obj's underlying member method code with example usage: obj.get_aux_input(aux_input) and returns: dict