class_docstr: Combined Pipeline for text-to-image generation using Wuerstchen
  
  This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
  library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
  
  Args:
      tokenizer (`CLIPTokenizer`):
          The decoder tokenizer to be used for text inputs.
      text_encoder (`CLIPTextModel`):
          The decoder text encoder to be used for text inputs.
      decoder (`WuerstchenDiffNeXt`):
          The decoder model to be used for decoder image generation pipeline.
      scheduler (`DDPMWuerstchenScheduler`):
          The scheduler to be used for decoder image generation pipeline.
      vqgan (`PaellaVQModel`):
          The VQGAN model to be used for decoder image generation pipeline.
      prior_tokenizer (`CLIPTokenizer`):
          The prior tokenizer to be used for text inputs.
      prior_text_encoder (`CLIPTextModel`):
          The prior text encoder to be used for text inputs.
      prior_prior (`WuerstchenPrior`):
          The prior model to be used for prior pipeline.
      prior_scheduler (`DDPMWuerstchenScheduler`):
          The scheduler to be used for prior pipeline.
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code: def progress_bar(self, iterable=None, total=None):
      self.prior_pipe.progress_bar(iterable=iterable, total=total)
      self.decoder_pipe.progress_bar(iterable=iterable, total=total)
  
file_path: llmga/llmga/diffusers/src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
imports: from typing import Callable, List, Optional, Union
  import torch
  from transformers import CLIPTextModel, CLIPTokenizer
  from ...schedulers import DDPMWuerstchenScheduler
  from ...utils import replace_example_docstring
  from ..pipeline_utils import DiffusionPipeline
  from .modeling_paella_vq_model import PaellaVQModel
  from .modeling_wuerstchen_diffnext import WuerstchenDiffNeXt
  from .modeling_wuerstchen_prior import WuerstchenPrior
  from .pipeline_wuerstchen import WuerstchenDecoderPipeline
  from .pipeline_wuerstchen_prior import WuerstchenPriorPipeline
label_desc: Use image node_id 5 for calling the WuerstchenCombinedPipeline obj's underlying member method code with example usage: obj.progress_bar(iterable, total) without return types