code: def test_relu_layer_deeplift_multiple_output(self) -> None:
      model = BasicModel_MultiLayer(multi_input_module=True)
      (
          inputs,
          baselines,
      ) = _create_inps_and_base_for_deeplift_neuron_layer_testing()
  
      layer_dl = LayerDeepLift(model, model.multi_relu)
      attributions, delta = layer_dl.attribute(
          inputs[0],
          baselines[0],
          target=0,
          attribute_to_layer_input=False,
          return_convergence_delta=True,
      )
      assertTensorTuplesAlmostEqual(
          self,
          attributions,
          ([[0.0, -1.0, -1.0, -1.0]], [[0.0, -1.0, -1.0, -1.0]]),
      )
      assert_delta(self, delta)
  
imports: from __future__ import print_function
  from typing import cast, List, Tuple, Union
  import torch
  from captum.attr._core.layer.layer_deep_lift import LayerDeepLift, LayerDeepLiftShap
  from tests.helpers.basic import assert_delta, assertTensorAlmostEqual, assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet, BasicModel_ConvNet_MaxPool3d, BasicModel_MaxPool_ReLU, BasicModel_MultiLayer, LinearMaxPoolLinearModel, ReLULinearModel
  from torch import Tensor
label_desc: Use image node_id 3 for calling the TestDeepLift obj's underlying member method code with example usage: obj.test_relu_layer_deeplift_multiple_output() without return types