code: def __init__(
      self,
      text_encoder: FlaxCLIPTextModel,
      text_encoder_2: FlaxCLIPTextModel,
      vae: FlaxAutoencoderKL,
      tokenizer: CLIPTokenizer,
      tokenizer_2: CLIPTokenizer,
      unet: FlaxUNet2DConditionModel,
      scheduler: Union[
          FlaxDDIMScheduler,
          FlaxPNDMScheduler,
          FlaxLMSDiscreteScheduler,
          FlaxDPMSolverMultistepScheduler,
      ],
      dtype: jnp.dtype = jnp.float32,
  ):
      super().__init__()
      self.dtype = dtype
  
      self.register_modules(
          vae=vae,
          text_encoder=text_encoder,
          text_encoder_2=text_encoder_2,
          tokenizer=tokenizer,
          tokenizer_2=tokenizer_2,
          unet=unet,
          scheduler=scheduler,
      )
      self.vae_scale_factor = 2 ** (
          len(self.vae.config.block_out_channels) - 1
      )
  
file_path: llmga/llmga/diffusers/src/diffusers/pipelines/stable_diffusion_xl/pipeline_flax_stable_diffusion_xl.py
imports: from functools import partial
  from typing import Dict, List, Optional, Union
  import jax
  import jax.numpy
  from flax.core.frozen_dict import FrozenDict
  from transformers import CLIPTokenizer, FlaxCLIPTextModel
  from diffusers.utils import logging
  from ...models import FlaxAutoencoderKL, FlaxUNet2DConditionModel
  from ...schedulers import FlaxDDIMScheduler, FlaxDPMSolverMultistepScheduler, FlaxLMSDiscreteScheduler, FlaxPNDMScheduler
  from ..pipeline_flax_utils import FlaxDiffusionPipeline
  from .pipeline_output import FlaxStableDiffusionXLPipelineOutput
label_desc: Use image node_id 1 to create a new FlaxStableDiffusionXLPipeline object from inherited base classes: FlaxDiffusionPipeline with example: obj = FlaxStableDiffusionXLPipeline(text_encoder, text_encoder_2, vae, tokenizer, tokenizer_2, unet, scheduler, dtype)