code: def txt2img(
      id_task: str,
      prompt: str,
      negative_prompt: str,
      prompt_styles,
      steps: int,
      sampler_name: str,
      n_iter: int,
      batch_size: int,
      cfg_scale: float,
      height: int,
      width: int,
      enable_hr: bool,
      denoising_strength: float,
      hr_scale: float,
      hr_upscaler: str,
      hr_second_pass_steps: int,
      hr_resize_x: int,
      hr_resize_y: int,
      hr_checkpoint_name: str,
      hr_sampler_name: str,
      hr_prompt: str,
      hr_negative_prompt,
      override_settings_texts,
      request: gr.Request,
      *args,
  ):
      override_settings = create_override_settings_dict(
          override_settings_texts
      )
  
      p = processing.StableDiffusionProcessingTxt2Img(
          sd_model=shared.sd_model,
          outpath_samples=opts.outdir_samples
          or opts.outdir_txt2img_samples,
          outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
          prompt=prompt,
          styles=prompt_styles,
          negative_prompt=negative_prompt,
          sampler_name=sampler_name,
          batch_size=batch_size,
          n_iter=n_iter,
          steps=steps,
          cfg_scale=cfg_scale,
          width=width,
          height=height,
          enable_hr=enable_hr,
          denoising_strength=denoising_strength if enable_hr else None,
          hr_scale=hr_scale,
          hr_upscaler=hr_upscaler,
          hr_second_pass_steps=hr_second_pass_steps,
          hr_resize_x=hr_resize_x,
          hr_resize_y=hr_resize_y,
          hr_checkpoint_name=None
          if hr_checkpoint_name == "Use same checkpoint"
          else hr_checkpoint_name,
          hr_sampler_name=None
          if hr_sampler_name == "Use same sampler"
          else hr_sampler_name,
          hr_prompt=hr_prompt,
          hr_negative_prompt=hr_negative_prompt,
          override_settings=override_settings,
      )
  
      p.scripts = modules.scripts.scripts_txt2img
      p.script_args = args
  
      p.user = request.username
  
      if shared.opts.enable_console_prompts:
          print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
  
      with closing(p):
          processed = modules.scripts.scripts_txt2img.run(p, *args)
  
          if processed is None:
              processed = processing.process_images(p)
  
      shared.total_tqdm.clear()
  
      generation_info_js = processed.js()
      if opts.samples_log_stdout:
          print(generation_info_js)
  
      if opts.do_not_show_images:
          processed.images = []
  
      return (
          processed.images,
          generation_info_js,
          plaintext_to_html(processed.info),
          plaintext_to_html(processed.comments, classname="comments"),
      )
  
file_path: stable-diffusion-webui/modules/txt2img.py
imports: from contextlib import closing
  import modules.scripts
  from modules import processing
  from modules.generation_parameters_copypaste import create_override_settings_dict
  from modules.shared import opts
  import modules.shared
  from modules.ui import plaintext_to_html
  import gradio
label_desc: Use image node_id 1 for calling a global function with example usage: txt2img(id_task, prompt, negative_prompt, prompt_styles, steps, sampler_name, n_iter, batch_size, cfg_scale, height, width, enable_hr, denoising_strength, hr_scale, hr_upscaler, hr_second_pass_steps, hr_resize_x, hr_resize_y, hr_checkpoint_name, hr_sampler_name, hr_prompt, hr_negative_prompt, override_settings_texts, request) and returns: processed,  generation_info_js,  plaintext_to_html,  plaintext_to_html