Closes ("model labels")
@@ -313,7 +313,7 @@ class FastGradientMethod(Attack):
:param eps: (optional float) attack step size (input variation)
:param ord: (optional) Order of the norm (mimics NumPy).
Possible values: np.inf, 1 or 2.
- :param y: (optional) A tensor with the model labels. Only provide
+ :param y: (optional) A tensor with the true labels. Only provide
this parameter if you'd like to use true labels when crafting
adversarial samples. Otherwise, model predictions are used as
labels to avoid the "label leaking" effect (explained in this
@@ -359,7 +359,7 @@ class FastGradientMethod(Attack):
:param eps: (optional float) attack step size (input variation)
:param ord: (optional) Order of the norm (mimics NumPy).
Possible values: np.inf, 1 or 2.
- :param y: (optional) A tensor with the model labels. Only provide
+ :param y: (optional) A tensor with the true labels. Only provide
this parameter if you'd like to use true labels when crafting
adversarial samples. Otherwise, model predictions are used as
labels to avoid the "label leaking" effect (explained in this
@@ -405,7 +405,7 @@ def fgm(x,
TensorFlow implementation of the Fast Gradient Method.
:param x: the input placeholder
:param logits: output of model.get_logits
- :param y: (optional) A placeholder for the model labels. If targeted
+ :param y: (optional) A placeholder for the true labels. If targeted
is true, then provide the target label. Otherwise, only provide
this parameter if you'd like to use true labels when crafting
adversarial samples. Otherwise, model predictions are used as
@@ -636,7 +636,7 @@ class ProjectedGradientDescent(Attack):
compared to original input
:param eps_iter: (optional float) step size for each attack iteration
:param nb_iter: (optional int) Number of attack iterations.
- :param y: (optional) A tensor with the model labels.
+ :param y: (optional) A tensor with the true labels.
:param y_target: (optional) A tensor with the labels to target. Leave
y_target=None if y is also set. Labels should be
one-hot-encoded.
@@ -820,7 +820,7 @@ class MomentumIterativeMethod(Attack):
compared to original input
:param eps_iter: (optional float) step size for each attack iteration
:param nb_iter: (optional int) Number of attack iterations.
- :param y: (optional) A tensor with the model labels.
+ :param y: (optional) A tensor with the true labels.
:param y_target: (optional) A tensor with the labels to target. Leave
y_target=None if y is also set. Labels should be
one-hot-encoded.
