code: def _get_basic_config() -> Tuple[Module, Tensor, Tensor, Any]:
      input = torch.tensor(
          [1.0, 2.0, 3.0, 0.0, -1.0, 7.0], requires_grad=True
      ).T
      # manually percomputed gradients
      grads = torch.tensor([-0.0, -0.0, -0.0, 1.0, 1.0, -0.0])
      return BasicModel(), input, grads, None
  
imports: from typing import Any, cast, Tuple, Union
  import torch
  from captum._utils.gradient import compute_gradients
  from captum._utils.typing import TensorOrTupleOfTensorsGeneric
  from captum.attr._core.noise_tunnel import NoiseTunnel
  from captum.attr._core.saliency import Saliency
  from tests.helpers.basic import assertTensorAlmostEqual, assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel, BasicModel5_MultiArgs
  from tests.helpers.classification_models import SoftmaxModel
  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,  input,  grads,  None