code: def get_dummy_components(self):
      torch.manual_seed(0)
      transformer = Transformer2DModel(
          sample_size=8,
          num_layers=2,
          patch_size=2,
          attention_head_dim=8,
          num_attention_heads=3,
          caption_channels=32,
          in_channels=4,
          cross_attention_dim=24,
          out_channels=8,
          attention_bias=True,
          activation_fn="gelu-approximate",
          num_embeds_ada_norm=1000,
          norm_type="ada_norm_single",
          norm_elementwise_affine=False,
          norm_eps=1e-6,
      )
      torch.manual_seed(0)
      vae = AutoencoderKL()
  
      scheduler = DDIMScheduler()
      text_encoder = T5EncoderModel.from_pretrained(
          "hf-internal-testing/tiny-random-t5"
      )
  
      tokenizer = AutoTokenizer.from_pretrained(
          "hf-internal-testing/tiny-random-t5"
      )
  
      components = {
          "transformer": transformer.eval(),
          "vae": vae.eval(),
          "scheduler": scheduler,
          "text_encoder": text_encoder,
          "tokenizer": tokenizer,
      }
      return components
  
imports: import gc
  import tempfile
  import unittest
  import numpy
  import torch
  from transformers import AutoTokenizer, T5EncoderModel
  from diffusers import AutoencoderKL, DDIMScheduler, PixArtAlphaPipeline, Transformer2DModel
  from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin, to_np
label_desc: Use image node_id 1 for calling the PixArtAlphaPipelineFastTests obj's underlying member method code with example usage: obj.get_dummy_components() and returns: components