code: def _create_swav_pretraining_config(num_gpu: int = 2):
      cfg = compose_hydra_configuration(
          [
              "config=test/integration_test/quick_swav",
              "config.DATA.TRAIN.DATA_SOURCES=[synthetic]",
              "config.DATA.TRAIN.DATA_LIMIT=40",
              "config.DATA.TRAIN.BATCHSIZE_PER_REPLICA=4",
              "config.SEED_VALUE=0",
              "config.LOSS.swav_loss.epsilon=0.03",
              f"config.DISTRIBUTED.NUM_PROC_PER_NODE={num_gpu}",
              "config.LOG_FREQUENCY=1",
          ]
      )
      args, config = convert_to_attrdict(cfg)
      return config
  
imports: import os
  import unittest
  import torch
  import torch.nn.functional
  from vissl.losses.swav_distillation_loss import SwAVDistillationCriterion
  from vissl.losses.swav_loss import SwAVCriterion
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict
  from vissl.utils.test_utils import gpu_test, in_temporary_directory, run_integration_test, spawn_distributed_test
label_desc: Use image node_id 1 for calling the TestDistillationSwAV obj's underlying member method code with example usage: obj._create_swav_pretraining_config(num_gpu) and returns: config