docstr: Generate audio array from input text.
  
  Args:
      text: text to be turned into audio
      history_prompt: history choice for audio cloning
      text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
      waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
  
  Returns:
      numpy audio array at sample frequency 24khz
docstr_tok: ["Generate","audio","array","from","input","text",".","Args",":","text",":","text","to","be","turned","into","audio","history_prompt",":","history","choice","for","audio","cloning","text_temp",":","generation","temperature","(","1.0","more","diverse",",","0.0","more","conservative",")","waveform_temp",":","generation","temperature","(","1.0","more","diverse",",","0.0","more","conservative",")","Returns",":","numpy","audio","array","at","sample","frequency","24khz"]
code: def generate_audio(
      self,
      text: str,
      history_prompt: Optional[str] = None,
      text_temp: float = 0.7,
      waveform_temp: float = 0.7,
      base=None,
      allow_early_stop=True,
      **kwargs,
  ):
      """Generate audio array from input text.
  
      Args:
          text: text to be turned into audio
          history_prompt: history choice for audio cloning
          text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
          waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)
  
      Returns:
          numpy audio array at sample frequency 24khz
      """
      x_semantic = self.text_to_semantic(
          text,
          history_prompt=history_prompt,
          temp=text_temp,
          base=base,
          allow_early_stop=allow_early_stop,
          **kwargs,
      )
      audio_arr, c, f = self.semantic_to_waveform(
          x_semantic,
          history_prompt=history_prompt,
          temp=waveform_temp,
          base=base,
      )
      return audio_arr, [x_semantic, c, f]
  
imports: import os
  from dataclasses import dataclass
  from typing import Optional
  import numpy
  from coqpit import Coqpit
  from encodec import EncodecModel
  from transformers import BertTokenizer
  from TTS.tts.layers.bark.inference_funcs import codec_decode, generate_coarse, generate_fine, generate_text_semantic, generate_voice, load_voice
  from TTS.tts.layers.bark.load_model import load_model
  from TTS.tts.layers.bark.model import GPT
  from TTS.tts.layers.bark.model_fine import FineGPT
  from TTS.tts.models.base_tts import BaseTTS
label_desc: Use image node_id 7 for calling the Bark obj's underlying member method code with example usage: obj.generate_audio(text, history_prompt, text_temp, waveform_temp, base, allow_early_stop) and returns: audio_arr,  list