code: def _get_basic_config() -> Tuple[Module, Tensor]:
      input = torch.arange(16).view(1, 1, 4, 4).float()
      return BasicModel_ConvNet_One_Conv(), input
  
imports: from typing import cast, Tuple
  import torch
  import torch.nn
  from captum.attr import InputXGradient, LRP
  from captum.attr._utils.lrp_rules import Alpha1_Beta0_Rule, EpsilonRule, GammaRule, IdentityRule
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModelWithReusedLinear, SimpleLRPModel
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 1 for calling a global function with example usage: _get_basic_config() and returns: BasicModel_ConvNet_One_Conv,  input