code: def test_parallel_training_equivalent_to_single_prefix_tuning(self):
      self.run_parallel_training_equivalent_to_single(
          PrefixTuningConfig()
      )
  
imports: import copy
  import random
  import torch
  from adapters import ADAPTER_MODEL_MAPPING, AutoAdapterModel, PrefixTuningConfig, SeqBnConfig, T5AdapterModel
  from adapters.composition import BatchSplit, Parallel
  from adapters.models.bert_generation.adapter_model import BertGenerationAdapterModel
  from transformers import MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, Trainer, TrainingArguments
  from transformers.testing_utils import require_torch, torch_device
label_desc: Use image node_id 8 for calling the ParallelTrainingMixin obj's underlying member method code with example usage: obj.test_parallel_training_equivalent_to_single_prefix_tuning() without return types