def test_relu_layer_deepliftshap_wo_mutliplying_by_inputs(self) -> None:
model = ReLULinearModel()
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
layer_dl_shap = LayerDeepLiftShap(model, model.relu, multiply_by_inputs=False)
attributions = layer_dl_shap.attribute(
inputs, baselines, attribute_to_layer_input=True,
)
assertTensorAlmostEqual(self, attributions[0], [[0.0, 1.0]])
def test_linear_layer_deepliftshap(self):
model = ReLULinearDeepLiftModel(inplace=True)
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
layer_dl_shap = LayerDeepLiftShap(model, model.l3)
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)
attributions, delta = layer_dl_shap.attribute(
inputs,
baselines,
attribute_to_layer_input=False,
return_convergence_delta=True,
)
assertTensorAlmostEqual(self, attributions, [[15.0]])
assert_delta(self, delta)
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)
def test_relu_layer_deepliftshap_multiple_output(self):
model = BasicModel_MultiLayer(multi_input_module=True)
(
inputs,
baselines,
) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
layer_dl = LayerDeepLiftShap(model, model.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)