def test_imagenet__BaselineGradient(): def method(model): return BaselineGradient(model) dryrun.test_analyzer(method, "imagenet.*")
def test_fast__BaselineLRPZ(): def method(model): return BaselineLRPZ(model) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__LRPZIgnoreBias(): def method(model): return LRPZIgnoreBias(model) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__BoundedDeepTaylor(): def method(model): return BoundedDeepTaylor(model, low=-1, high=1) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_imagenet__BoundedDeepTaylor(): def method(model): return BoundedDeepTaylor(model, low=-1, high=1) dryrun.test_analyzer(method, "imagenet.*")
def test_precommit__AnalyzerNetworkBase_neuron_selection_max(): def method(model): return Gradient(model, neuron_selection_mode="max_activation") dryrun.test_analyzer(method, "mnist.*")
def test_precommit__DeepTaylor(): def method(model): return DeepTaylor(model) dryrun.test_analyzer(method, "mnist.*")
def test_fast__PathIntegrator__python_based(): def method(model): return PathIntegrator(Input(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__PathIntegrator__keras_based(): def method(model): return PathIntegrator(Gradient(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__GaussianSmoother__keras_based(): def method(model): return GaussianSmoother(Gradient(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__GaussianSmoother__keras_based(): def method(model): return GaussianSmoother(Gradient(model)) dryrun.test_analyzer(method, "mnist.*")
def test_fast__GaussianSmoother__python_based(): def method(model): return GaussianSmoother(Input(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__BaselineGradient_pp_square(): def method(model): return BaselineGradient(model, postprocess="square") dryrun.test_analyzer(method, "mnist.*")
def test_fast__BaselineGradient_pp_square(): def method(model): return BaselineGradient(model, postprocess="square") dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__BaseReverseNetwork_reverse_check_finite(): def method(model): return Gradient(model, reverse_verbose=True, reverse_check_finite=True) dryrun.test_analyzer(method, "mnist.*")
def test_precommit__PathIntegrator__keras_based(): def method(model): return PathIntegrator(Gradient(model)) dryrun.test_analyzer(method, "mnist.*")
def test_fast__AnalyzerNetworkBase_neuron_selection_max(): def method(model): return Gradient(model, neuron_selection_mode="max_activation") dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__WrapperBase(): def method(model): return WrapperBase(Gradient(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__DeepTaylor(): def method(model): return DeepTaylor(model) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__WrapperBase(): def method(model): return WrapperBase(Gradient(model)) dryrun.test_analyzer(method, "mnist.*")
def test_imagenet__DeepTaylor(): def method(model): return DeepTaylor(model) dryrun.test_analyzer(method, "imagenet.*")
def test_fast__AugmentReduceBase__python_based(): def method(model): return AugmentReduceBase(Input(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__BoundedDeepTaylor(): def method(model): return BoundedDeepTaylor(model, low=-1, high=1) dryrun.test_analyzer(method, "mnist.*")
def test_fast__AugmentReduceBase__keras_based(): def method(model): return AugmentReduceBase(Gradient(model)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__LRPAlpha1Beta0(): def method(model): return LRPAlpha1Beta0(model) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__AugmentReduceBase__keras_based(): def method(model): return AugmentReduceBase(Gradient(model)) dryrun.test_analyzer(method, "mnist.*")
def test_fast__LRPZ__with_boxed_input_layer_rule(): def method(model): return LRPZ(model, input_layer_rule=(-10, 10)) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__BaseReverseNetwork_reverse_check_finite(): def method(model): return Gradient(model, reverse_verbose=True, reverse_check_finite=True) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_fast__LRPEpsilon(): def method(model): return LRPEpsilon(model) dryrun.test_analyzer(method, "trivia.*:mnist.log_reg")
def test_precommit__BaselineGradient(): def method(model): return BaselineGradient(model) dryrun.test_analyzer(method, "mnist.*")