code: def __new__(cls, name: str, bases: Tuple, attrs: Dict):
      for test_config in config:
          (
              algorithms,
              model,
              args,
              layer,
              noise_tunnel,
              baseline_distr,
          ) = parse_test_config(test_config)
          dp_delta = (
              test_config["dp_delta"]
              if "dp_delta" in test_config
              else 0.0001
          )
  
          for algorithm in algorithms:
              if not should_create_generated_test(algorithm):
                  continue
              for mode in DataParallelCompareMode:
                  # Creates test case corresponding to each algorithm and
                  # DataParallelCompareMode
                  test_method = cls.make_single_dp_test(
                      algorithm,
                      model,
                      layer,
                      args,
                      dp_delta,
                      noise_tunnel,
                      baseline_distr,
                      mode,
                  )
                  test_name = gen_test_name(
                      "test_dp_" + mode.name,
                      cast(str, test_config["name"]),
                      algorithm,
                      noise_tunnel,
                  )
                  if test_name in attrs:
                      raise AssertionError(
                          "Trying to overwrite existing test with name: %r"
                          % test_name
                      )
                  attrs[test_name] = test_method
  
      return super(DataParallelMeta, cls).__new__(
          cls, name, bases, attrs
      )
  
imports: import copy
  import os
  from enum import Enum
  from typing import Any, Callable, cast, Dict, Optional, Tuple, Type
  import torch
  import torch.distributed
  from captum.attr._core.guided_grad_cam import GuidedGradCam
  from captum.attr._core.layer.layer_deep_lift import LayerDeepLift, LayerDeepLiftShap
  from captum.attr._core.layer.layer_lrp import LayerLRP
  from captum.attr._core.neuron.neuron_deep_lift import NeuronDeepLift, NeuronDeepLiftShap
  from captum.attr._core.neuron.neuron_guided_backprop_deconvnet import NeuronDeconvolution, NeuronGuidedBackprop
  from captum.attr._core.noise_tunnel import NoiseTunnel
  from captum.attr._utils.attribution import Attribution, InternalAttribution
  from tests.attr.helpers.gen_test_utils import gen_test_name, get_target_layer, parse_test_config, should_create_generated_test
  from tests.attr.helpers.test_config import config
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest, deep_copy_args
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 1 for calling the DataParallelMeta obj's underlying member method code with example usage: obj.__new__(cls, name, bases, attrs) and returns: super