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.*")
