def _internal_influence_test_assert(
self,
model: Module,
target_layer: Module,
test_input: Union[Tensor, Tuple[Tensor, ...]],
expected_activation: Union[float, List[List[float]],
Tuple[List[List[float]], ...]],
baseline: BaselineType = None,
additional_args: Any = None,
attribute_to_layer_input: bool = False,
):
for internal_batch_size in [None, 5, 20]:
int_inf = InternalInfluence(model, target_layer)
attributions = int_inf.attribute(
test_input,
baselines=baseline,
target=0,
n_steps=500,
method="riemann_trapezoid",
additional_forward_args=additional_args,
internal_batch_size=internal_batch_size,
attribute_to_layer_input=attribute_to_layer_input,
)
assertTensorTuplesAlmostEqual(self,
attributions,
expected_activation,
delta=0.01,
mode="max")
def _internal_influence_test_assert(
self,
model,
target_layer,
test_input,
expected_activation,
baseline=None,
additional_args=None,
attribute_to_layer_input=False,
):
for internal_batch_size in [None, 1, 20]:
int_inf = InternalInfluence(model, target_layer)
attributions = int_inf.attribute(
test_input,
baselines=baseline,
target=0,
n_steps=500,
method="riemann_trapezoid",
additional_forward_args=additional_args,
internal_batch_size=internal_batch_size,
attribute_to_layer_input=attribute_to_layer_input,
)
assertTensorTuplesAlmostEqual(
self,
attributions,
expected_activation,
delta=0.01,
mode="max",
)
def _internal_influence_test_assert(
self,
model,
target_layer,
test_input,
expected_activation,
baseline=None,
additional_args=None,
attribute_to_layer_input=False,
):
for internal_batch_size in [None, 1, 20]:
int_inf = InternalInfluence(model, target_layer)
attributions = int_inf.attribute(
test_input,
baselines=baseline,
target=0,
n_steps=500,
method="riemann_trapezoid",
additional_forward_args=additional_args,
internal_batch_size=internal_batch_size,
attribute_to_layer_input=attribute_to_layer_input,
)
for i in range(len(expected_activation)):
assertArraysAlmostEqual(
attributions[i:i + 1].squeeze(0).tolist(),
expected_activation[i],
delta=0.01,
)