class_docstr: General class to jointly train text2mel and vocoder parts.
docstr: Run inference.
  
  Args:
      text (Tensor): Input text index tensor (T_text,).
  
  Returns:
      Dict[str, Tensor]:
          * wav (Tensor): Generated waveform tensor (T_wav,).
          * feat_gan (Tensor): Generated feature tensor (T_text, C).
docstr_tok: ["Run","inference",".","Args",":","text","(","Tensor",")",":","Input","text","index","tensor","(","T_text",",",")",".","Returns",":","Dict","[","str",",","Tensor","]",":","*","wav","(","Tensor",")",":","Generated","waveform","tensor","(","T_wav",",",")",".","*","feat_gan","(","Tensor",")",":","Generated","feature","tensor","(","T_text",",","C",")","."]
code: def inference(
      self,
      text: torch.Tensor,
      **kwargs,
  ) -> Dict[str, torch.Tensor]:
      """Run inference.
  
      Args:
          text (Tensor): Input text index tensor (T_text,).
  
      Returns:
          Dict[str, Tensor]:
              * wav (Tensor): Generated waveform tensor (T_wav,).
              * feat_gan (Tensor): Generated feature tensor (T_text, C).
  
      """
      output_dict = self.generator["text2mel"].inference(
          text=text,
          **kwargs,
      )
      wav = self.generator["vocoder"].inference(output_dict["feat_gen"])
      if self.use_pqmf:
          wav = self.pqmf.synthesis(wav.unsqueeze(0).transpose(1, 2))
          wav = wav.squeeze(0).transpose(0, 1)
      output_dict.update(wav=wav)
  
      return output_dict
  
imports: from typing import Any, Dict
  import torch
  from typeguard import check_argument_types
  from espnet2.gan_tts.abs_gan_tts import AbsGANTTS
  from espnet2.gan_tts.hifigan import HiFiGANGenerator, HiFiGANMultiPeriodDiscriminator, HiFiGANMultiScaleDiscriminator, HiFiGANMultiScaleMultiPeriodDiscriminator, HiFiGANPeriodDiscriminator, HiFiGANScaleDiscriminator
  from espnet2.gan_tts.hifigan.loss import DiscriminatorAdversarialLoss, FeatureMatchLoss, GeneratorAdversarialLoss, MelSpectrogramLoss
  from espnet2.gan_tts.melgan import MelGANGenerator, MelGANMultiScaleDiscriminator
  from espnet2.gan_tts.melgan.pqmf import PQMF
  from espnet2.gan_tts.parallel_wavegan import ParallelWaveGANDiscriminator, ParallelWaveGANGenerator
  from espnet2.gan_tts.style_melgan import StyleMelGANDiscriminator, StyleMelGANGenerator
  from espnet2.gan_tts.utils import get_random_segments, get_segments
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet2.tts.fastspeech import FastSpeech
  from espnet2.tts.fastspeech2 import FastSpeech2
  from espnet2.tts.tacotron2 import Tacotron2
  from espnet2.tts.transformer import Transformer
label_desc: Use image node_id 7 for calling the JointText2Wav obj's underlying member method code with example usage: obj.inference(text) and returns: output_dict