code: def get_lora_components(self):
      prior = self.dummy_prior
  
      prior_lora_config = LoraConfig(
          r=4,
          lora_alpha=4,
          target_modules=["to_q", "to_k", "to_v", "to_out.0"],
          init_lora_weights=False,
      )
  
      (
          prior_lora_attn_procs,
          prior_lora_layers,
      ) = create_prior_lora_layers(prior)
  
      lora_components = {
          "prior_lora_layers": prior_lora_layers,
          "prior_lora_attn_procs": prior_lora_attn_procs,
      }
  
      return prior, prior_lora_config, lora_components
  
imports: import unittest
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import DDPMWuerstchenScheduler, WuerstchenPriorPipeline
  from diffusers.loaders import AttnProcsLayers
  from diffusers.models.attention_processor import LoRAAttnProcessor, LoRAAttnProcessor2_0
  from diffusers.pipelines.wuerstchen import WuerstchenPrior
  from diffusers.utils.import_utils import is_peft_available
  from diffusers.utils.testing_utils import enable_full_determinism, require_peft_backend, skip_mps, torch_device
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 16 for calling the WuerstchenPriorPipelineFastTests obj's underlying member method code with example usage: obj.get_lora_components() and returns: prior,  prior_lora_config,  lora_components