def test_relu_deepliftshap_with_custom_attr_func(self) -> None:
model = ReLULinearModel()
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
neuron_dl = NeuronDeepLiftShap(model, model.l3)
expected = (torch.zeros(3, 3), torch.zeros(3, 3))
self._relu_custom_attr_func_assert(neuron_dl, inputs, baselines,
expected)
def test_relu_neuron_deeplift_shap(self):
model = ReLULinearDeepLiftModel()
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
neuron_dl = NeuronDeepLiftShap(model, model.relu)
attributions = neuron_dl.attribute(
inputs, 0, baselines, attribute_to_neuron_input=True
)
assertTensorAlmostEqual(self, attributions[0], [[-30.0, 1.0, -0.0]])
assertTensorAlmostEqual(self, attributions[1], [[0.0, 0.0, 0.0]])
attributions = neuron_dl.attribute(
inputs, 0, baselines, attribute_to_neuron_input=False
)
assertTensorAlmostEqual(self, attributions[0], [[0.0, 0.0, 0.0]])
assertTensorAlmostEqual(self, attributions[1], [[0.0, 0.0, 0.0]])
def test_linear_neuron_deeplift_shap(self) -> None:
model = ReLULinearModel()
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
neuron_dl = NeuronDeepLiftShap(model, model.l3)
attributions = neuron_dl.attribute(inputs,
0,
baselines,
attribute_to_neuron_input=True)
assertTensorAlmostEqual(self, attributions[0], [[-0.0, 0.0, -0.0]])
assertTensorAlmostEqual(self, attributions[1], [[0.0, 0.0, 0.0]])
attributions = neuron_dl.attribute(inputs,
0,
baselines,
attribute_to_neuron_input=False)
self.assertTrue(neuron_dl.multiplies_by_inputs)
assertTensorAlmostEqual(self, attributions[0], [[-0.0, 0.0, -0.0]])
assertTensorAlmostEqual(self, attributions[1], [[6.0, 9.0, 0.0]])
