Esempio n. 1
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    def test_linear_layer_deeplift_batch(self) -> None:
        model = ReLULinearModel(inplace=True)
        _, baselines = _create_inps_and_base_for_deeplift_neuron_layer_testing(
        )
        x1 = torch.tensor(
            [[-10.0, 1.0, -5.0], [-10.0, 1.0, -5.0], [-10.0, 1.0, -5.0]],
            requires_grad=True,
        )
        x2 = torch.tensor([[3.0, 3.0, 1.0], [3.0, 3.0, 1.0], [3.0, 3.0, 1.0]],
                          requires_grad=True)
        inputs = (x1, x2)

        layer_dl = LayerDeepLift(model, model.l3)
        attributions, delta = layer_dl.attribute(
            inputs,
            baselines,
            attribute_to_layer_input=True,
            return_convergence_delta=True,
        )
        assertTensorAlmostEqual(self, attributions[0], [[0.0, 15.0]])
        assert_delta(self, delta)

        attributions, delta = layer_dl.attribute(
            inputs,
            baselines,
            attribute_to_layer_input=False,
            return_convergence_delta=True,
        )
        assertTensorAlmostEqual(self, attributions, [[15.0]])
        assert_delta(self, delta)
Esempio n. 2
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    def test_linear_layer_deeplift(self) -> None:
        model = ReLULinearModel(inplace=True)
        inputs, baselines = _create_inps_and_base_for_deeplift_neuron_layer_testing(
        )

        layer_dl = LayerDeepLift(model, model.l3)
        attributions, delta = layer_dl.attribute(
            inputs,
            baselines,
            attribute_to_layer_input=True,
            return_convergence_delta=True,
        )
        assertTensorAlmostEqual(self, attributions[0], [[0.0, 15.0]])
        assert_delta(self, delta)
Esempio n. 3
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    def test_relu_layer_deeplift_add_args(self) -> None:
        model = ReLULinearModel()
        inputs, baselines = _create_inps_and_base_for_deeplift_neuron_layer_testing(
        )

        layer_dl = LayerDeepLift(model, model.relu)
        attributions, delta = layer_dl.attribute(
            inputs,
            baselines,
            additional_forward_args=3.0,
            attribute_to_layer_input=True,
            return_convergence_delta=True,
        )
        assertTensorAlmostEqual(self, attributions[0], [[0.0, 45.0]])
        assert_delta(self, delta)
Esempio n. 4
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 def test_relu_layer_deepliftshap(self) -> None:
     model = ReLULinearModel()
     (
         inputs,
         baselines,
     ) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
     layer_dl_shap = LayerDeepLiftShap(model, model.relu)
     attributions, delta = layer_dl_shap.attribute(
         inputs,
         baselines,
         attribute_to_layer_input=True,
         return_convergence_delta=True,
     )
     assertTensorAlmostEqual(self, attributions[0], [[0.0, 15.0]])
     assert_delta(self, delta)
Esempio n. 5
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    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)