class_docstr: Test the DDPOTrainer class.
class_docstr_tok: ["Test","the","DDPOTrainer","class","."]
code: def setUp(self):
      self.ddpo_config = DDPOConfig(
          num_epochs=2,
          train_gradient_accumulation_steps=1,
          per_prompt_stat_tracking_buffer_size=32,
          sample_num_batches_per_epoch=2,
          sample_batch_size=2,
          mixed_precision=None,
          save_freq=1000000,
      )
      pretrained_model = (
          "hf-internal-testing/tiny-stable-diffusion-torch"
      )
      pretrained_revision = "main"
  
      pipeline = DefaultDDPOStableDiffusionPipeline(
          pretrained_model,
          pretrained_model_revision=pretrained_revision,
          use_lora=False,
      )
  
      self.trainer = DDPOTrainer(
          self.ddpo_config, scorer_function, prompt_function, pipeline
      )
  
      return super().setUp()
  
file_path: trl/tests/test_ddpo_trainer.py
imports: import gc
  import unittest
  import torch
  from trl import is_diffusers_available, is_peft_available
  from .testing_utils import require_diffusers
label_desc: Use image node_id 1 for calling the DDPOTrainerTester obj's underlying member method code with example usage: obj.setUp() and returns: super