code: def _create_pretraining_config(with_fsdp: bool, num_gpu: int = 2):
      cfg = compose_hydra_configuration(
          [
              "config=test/integration_test/quick_swav",
              "+config/pretrain/swav/models=regnet16Gf",
              "config.DATA.TRAIN.DATA_SOURCES=[synthetic]",
              "config.DATA.TRAIN.DATA_LIMIT=40",
              "config.SEED_VALUE=0",
              "config.MODEL.AMP_PARAMS.USE_AMP=False",
              "config.MODEL.SYNC_BN_CONFIG.CONVERT_BN_TO_SYNC_BN=True",
              "config.MODEL.SYNC_BN_CONFIG.SYNC_BN_TYPE=pytorch",
              "config.MODEL.AMP_PARAMS.AMP_TYPE=pytorch",
              "config.LOSS.swav_loss.epsilon=0.03",
              "config.MODEL.FSDP_CONFIG.flatten_parameters=True",
              "config.MODEL.FSDP_CONFIG.mixed_precision=False",
              "config.MODEL.FSDP_CONFIG.fp32_reduce_scatter=False",
              "config.MODEL.FSDP_CONFIG.compute_dtype=float32",
              f"config.DISTRIBUTED.NUM_PROC_PER_NODE={num_gpu}",
              "config.LOG_FREQUENCY=1",
              "config.OPTIMIZER.construct_single_param_group_only=True",
              "config.DATA.TRAIN.BATCHSIZE_PER_REPLICA=4",
              "config.OPTIMIZER.use_larc=False",
          ]
      )
      args, config = convert_to_attrdict(cfg)
      if with_fsdp:
          config["MODEL"]["TRUNK"]["NAME"] = "regnet_fsdp"
          config["MODEL"]["HEAD"]["PARAMS"][0][0] = "swav_head_fsdp"
          config.TRAINER.TASK_NAME = "self_supervision_fsdp_task"
      else:
          config["MODEL"]["TRUNK"]["NAME"] = "regnet_v2"
          config["MODEL"]["HEAD"]["PARAMS"][0][0] = "swav_head"
      return config
  
file_path: vissl/tests/test_extract_cluster.py
imports: import os
  import shutil
  import unittest
  import numpy
  from vissl.utils.cluster_utils import ClusterAssignmentLoader
  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
label_desc: Use image node_id 1 for calling the TestExtractClusterWorkflow obj's underlying member method code with example usage: obj._create_pretraining_config(with_fsdp, num_gpu) and returns: config