code: def test_custom_diffusion(self):
      with tempfile.TemporaryDirectory() as tmpdir:
          test_args = f"""
                  examples/custom_diffusion/train_custom_diffusion.py
                  --pretrained_model_name_or_path hf-internal-testing/tiny-stable-diffusion-pipe
                  --instance_data_dir docs/source/en/imgs
                  --instance_prompt <new1>
                  --resolution 64
                  --train_batch_size 1
                  --gradient_accumulation_steps 1
                  --max_train_steps 2
                  --learning_rate 1.0e-05
                  --scale_lr
                  --lr_scheduler constant
                  --lr_warmup_steps 0
                  --modifier_token <new1>
                  --no_safe_serialization
                  --output_dir {tmpdir}
                  """.split()
  
          run_command(self._launch_args + test_args)
          # save_pretrained smoke test
          self.assertTrue(
              os.path.isfile(
                  os.path.join(
                      tmpdir, "pytorch_custom_diffusion_weights.bin"
                  )
              )
          )
          self.assertTrue(
              os.path.isfile(os.path.join(tmpdir, "<new1>.bin"))
          )
  
imports: import logging
  import os
  import shutil
  import subprocess
  import sys
  import tempfile
  import unittest
  from typing import List
  import safetensors
  from accelerate.utils import write_basic_config
  from diffusers import DiffusionPipeline, UNet2DConditionModel
label_desc: Use image node_id 15 for calling the ExamplesTestsAccelerate obj's underlying member method code with example usage: obj.test_custom_diffusion() without return types