class_docstr: Configuration class for the DelightfulTTS model.
  
  Attributes:
      model (str): Name of the model ("delightful_tts").
      audio (DelightfulTtsAudioConfig): Configuration for audio settings.
      model_args (DelightfulTtsArgs): Configuration for model arguments.
      use_attn_priors (bool): Whether to use attention priors.
      vocoder (VocoderConfig): Configuration for the vocoder.
      init_discriminator (bool): Whether to initialize the discriminator.
      steps_to_start_discriminator (int): Number of steps to start the discriminator.
      grad_clip (List[float]): Gradient clipping values.
      lr_gen (float): Learning rate for the  gan generator.
      lr_disc (float): Learning rate for the gan discriminator.
      lr_scheduler_gen (str): Name of the learning rate scheduler for the generator.
      lr_scheduler_gen_params (dict): Parameters for the learning rate scheduler for the generator.
      lr_scheduler_disc (str): Name of the learning rate scheduler for the discriminator.
      lr_scheduler_disc_params (dict): Parameters for the learning rate scheduler for the discriminator.
      scheduler_after_epoch (bool): Whether to schedule after each epoch.
      optimizer (str): Name of the optimizer.
      optimizer_params (dict): Parameters for the optimizer.
      ssim_loss_alpha (float): Alpha value for the SSIM loss.
      mel_loss_alpha (float): Alpha value for the mel loss.
      aligner_loss_alpha (float): Alpha value for the aligner loss.
      pitch_loss_alpha (float): Alpha value for the pitch loss.
      energy_loss_alpha (float): Alpha value for the energy loss.
      u_prosody_loss_alpha (float): Alpha value for the utterance prosody loss.
      p_prosody_loss_alpha (float): Alpha value for the phoneme prosody loss.
      dur_loss_alpha (float): Alpha value for the duration loss.
      char_dur_loss_alpha (float): Alpha value for the character duration loss.
      binary_align_loss_alpha (float): Alpha value for the binary alignment loss.
      binary_loss_warmup_epochs (int): Number of warm-up epochs for the binary loss.
      disc_loss_alpha (float): Alpha value for the discriminator loss.
      gen_loss_alpha (float): Alpha value for the generator loss.
      feat_loss_alpha (float): Alpha value for the feature loss.
      vocoder_mel_loss_alpha (float): Alpha value for the vocoder mel loss.
      multi_scale_stft_loss_alpha (float): Alpha value for the multi-scale STFT loss.
      multi_scale_stft_loss_params (dict): Parameters for the multi-scale STFT loss.
      return_wav (bool): Whether to return audio waveforms.
      use_weighted_sampler (bool): Whether to use a weighted sampler.
      weighted_sampler_attrs (dict): Attributes for the weighted sampler.
      weighted_sampler_multipliers (dict): Multipliers for the weighted sampler.
      r (int): Value for the `r` override.
      compute_f0 (bool): Whether to compute F0 values.
      f0_cache_path (str): Path to the F0 cache.
      attn_prior_cache_path (str): Path to the attention prior cache.
      num_speakers (int): Number of speakers.
      use_speaker_embedding (bool): Whether to use speaker embedding.
      speakers_file (str): Path to the speaker file.
      speaker_embedding_channels (int): Number of channels for the speaker embedding.
      language_ids_file (str): Path to the language IDs file.
class_docstr_tok: ["Configuration","class","for","the","DelightfulTTS","model",".","Attributes",":","model","(","str",")",":","Name","of","the","model","(","``","delightful_tts","''",")",".","audio","(","DelightfulTtsAudioConfig",")",":","Configuration","for","audio","settings",".","model_args","(","DelightfulTtsArgs",")",":","Configuration","for","model","arguments",".","use_attn_priors","(","bool",")",":","Whether","to","use","attention","priors",".","vocoder","(","VocoderConfig",")",":","Configuration","for","the","vocoder",".","init_discriminator","(","bool",")",":","Whether","to","initialize","the","discriminator",".","steps_to_start_discriminator","(","int",")",":","Number","of","steps","to","start","the","discriminator",".","grad_clip","(","List","[","float","]",")",":","Gradient","clipping","values",".","lr_gen","(","float",")",":","Learning","rate","for","the","gan","generator",".","lr_disc","(","float",")",":","Learning","rate","for","the","gan","discriminator",".","lr_scheduler_gen","(","str",")",":","Name","of","the","learning","rate","scheduler","for","the","generator",".","lr_scheduler_gen_params","(","dict",")",":","Parameters","for","the","learning","rate","scheduler","for","the","generator",".","lr_scheduler_disc","(","str",")",":","Name","of","the","learning","rate","scheduler","for","the","discriminator",".","lr_scheduler_disc_params","(","dict",")",":","Parameters","for","the","learning","rate","scheduler","for","the","discriminator",".","scheduler_after_epoch","(","bool",")",":","Whether","to","schedule","after","each","epoch",".","optimizer","(","str",")",":","Name","of","the","optimizer",".","optimizer_params","(","dict",")",":","Parameters","for","the","optimizer",".","ssim_loss_alpha","(","float",")",":","Alpha","value","for","the","SSIM","loss",".","mel_loss_alpha","(","float",")",":","Alpha","value","for","the","mel","loss",".","aligner_loss_alpha","(","float",")",":","Alpha","value","for","the","aligner","loss",".","pitch_loss_alpha","(","float",")",":","Alpha","value","for","the","pitch","loss",".","energy_loss_alpha","(","float",")",":","Alpha","value","for","the","energy","loss",".","u_prosody_loss_alpha","(","float",")",":","Alpha","value","for","the","utterance","prosody","loss",".","p_prosody_loss_alpha","(","float",")",":","Alpha","value","for","the","phoneme","prosody","loss",".","dur_loss_alpha","(","float",")",":","Alpha","value","for","the","duration","loss",".","char_dur_loss_alpha","(","float",")",":","Alpha","value","for","the","character","duration","loss",".","binary_align_loss_alpha","(","float",")",":","Alpha","value","for","the","binary","alignment","loss",".","binary_loss_warmup_epochs","(","int",")",":","Number","of","warm-up","epochs","for","the","binary","loss",".","disc_loss_alpha","(","float",")",":","Alpha","value","for","the","discriminator","loss",".","gen_loss_alpha","(","float",")",":","Alpha","value","for","the","generator","loss",".","feat_loss_alpha","(","float",")",":","Alpha","value","for","the","feature","loss",".","vocoder_mel_loss_alpha","(","float",")",":","Alpha","value","for","the","vocoder","mel","loss",".","multi_scale_stft_loss_alpha","(","float",")",":","Alpha","value","for","the","multi-scale","STFT","loss",".","multi_scale_stft_loss_params","(","dict",")",":","Parameters","for","the","multi-scale","STFT","loss",".","return_wav","(","bool",")",":","Whether","to","return","audio","waveforms",".","use_weighted_sampler","(","bool",")",":","Whether","to","use","a","weighted","sampler",".","weighted_sampler_attrs","(","dict",")",":","Attributes","for","the","weighted","sampler",".","weighted_sampler_multipliers","(","dict",")",":","Multipliers","for","the","weighted","sampler",".","r","(","int",")",":","Value","for","the","`","r","`","override",".","compute_f0","(","bool",")",":","Whether","to","compute","F0","values",".","f0_cache_path","(","str",")",":","Path","to","the","F0","cache",".","attn_prior_cache_path","(","str",")",":","Path","to","the","attention","prior","cache",".","num_speakers","(","int",")",":","Number","of","speakers",".","use_speaker_embedding","(","bool",")",":","Whether","to","use","speaker","embedding",".","speakers_file","(","str",")",":","Path","to","the","speaker","file",".","speaker_embedding_channels","(","int",")",":","Number","of","channels","for","the","speaker","embedding",".","language_ids_file","(","str",")",":","Path","to","the","language","IDs","file","."]
code: def __post_init__(self):
      # Pass multi-speaker parameters to the model args as `model.init_multispeaker()` looks for it there.
      if self.num_speakers > 0:
          self.model_args.num_speakers = self.num_speakers
  
      # speaker embedding settings
      if self.use_speaker_embedding:
          self.model_args.use_speaker_embedding = True
      if self.speakers_file:
          self.model_args.speakers_file = self.speakers_file
  
      # d-vector settings
      if self.use_d_vector_file:
          self.model_args.use_d_vector_file = True
      if self.d_vector_dim is not None and self.d_vector_dim > 0:
          self.model_args.d_vector_dim = self.d_vector_dim
      if self.d_vector_file:
          self.model_args.d_vector_file = self.d_vector_file
  
imports: from dataclasses import dataclass, field
  from typing import List
  from TTS.tts.configs.shared_configs import BaseTTSConfig
  from TTS.tts.models.delightful_tts import DelightfulTtsArgs, DelightfulTtsAudioConfig, VocoderConfig
label_desc: Use image node_id 1 for calling the DelightfulTTSConfig obj's underlying member method code with example usage: obj.__post_init__() without return types