code: def test_xformers_enable_works(self):
      (
          init_dict,
          inputs_dict,
      ) = self.prepare_init_args_and_inputs_for_common()
      model = self.model_class(**init_dict)
  
      model.enable_xformers_memory_efficient_attention()
  
      assert (
          model.mid_block.attentions[0]
          .transformer_blocks[0]
          .attn1.processor.__class__.__name__
          == "XFormersAttnProcessor"
      ), "xformers is not enabled"
  
imports: import copy
  import gc
  import os
  import tempfile
  import unittest
  from collections import OrderedDict
  import torch
  from parameterized import parameterized
  from pytest import mark
  from diffusers import UNet2DConditionModel
  from diffusers.models.attention_processor import CustomDiffusionAttnProcessor, IPAdapterAttnProcessor
  from diffusers.models.embeddings import ImageProjection, IPAdapterPlusImageProjection
  from diffusers.utils import logging
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import backend_empty_cache, enable_full_determinism, floats_tensor, load_hf_numpy, require_torch_accelerator, require_torch_accelerator_with_fp16, require_torch_accelerator_with_training, require_torch_gpu, skip_mps, slow, torch_all_close, torch_device
  from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
label_desc: Use image node_id 5 for calling the UNet2DConditionModelTests obj's underlying member method code with example usage: obj.test_xformers_enable_works() without return types