textattack.search_methods package
Search Methods
Search methods explore the transformation space in an attempt to find a successful attack as determined by a Goal Functions and list of Constraints
Reimplementation of search method from Generating Natural Language Adversarial Examples
by Alzantot et. al arxiv.org/abs/1804.07998 from github.com/nesl/nlp_adversarial_examples
- class textattack.search_methods.alzantot_genetic_algorithm.AlzantotGeneticAlgorithm(pop_size=60, max_iters=20, temp=0.3, give_up_if_no_improvement=False, post_crossover_check=True, max_crossover_retries=20)[source]
Bases:
GeneticAlgorithm
Attacks a model with word substiutitions using a genetic algorithm.
- Parameters
pop_size (int) – The population size. Defaults to 60.
max_iters (int) – The maximum number of iterations to use. Defaults to 20.
temp (float) – Temperature for softmax function used to normalize probability dist when sampling parents. Higher temperature increases the sensitivity to lower probability candidates.
give_up_if_no_improvement (bool) – If True, stop the search early if no candidate that improves the score is found.
post_crossover_check (bool) – If True, check if child produced from crossover step passes the constraints.
max_crossover_retries (int) – Maximum number of crossover retries if resulting child fails to pass the constraints. Applied only when post_crossover_check is set to True. Setting it to 0 means we immediately take one of the parents at random as the child upon failure.
Beam Search
- class textattack.search_methods.beam_search.BeamSearch(beam_width=8)[source]
Bases:
SearchMethod
An attack that maintains a beam of the beam_width highest scoring AttackedTexts, greedily updating the beam with the highest scoring transformations from the current beam.
- Parameters
goal_function – A function for determining how well a perturbation is doing at achieving the attack’s goal.
transformation – The type of transformation.
beam_width (int) – the number of candidates to retain at each step
- perform_search(initial_result)[source]
Perturbs attacked_text from
initial_result
until goal is reached or search is exhausted.Must be overridden by specific search methods.
- property is_black_box
Returns True if search method does not require access to victim model’s internal states.
Genetic Algorithm Word Swap
- class textattack.search_methods.genetic_algorithm.GeneticAlgorithm(pop_size=60, max_iters=20, temp=0.3, give_up_if_no_improvement=False, post_crossover_check=True, max_crossover_retries=20)[source]
Bases:
PopulationBasedSearch
,ABC
Base class for attacking a model with word substiutitions using a genetic algorithm.
- Parameters
pop_size (int) – The population size. Defaults to 20.
max_iters (int) – The maximum number of iterations to use. Defaults to 50.
temp (float) – Temperature for softmax function used to normalize probability dist when sampling parents. Higher temperature increases the sensitivity to lower probability candidates.
give_up_if_no_improvement (bool) – If True, stop the search early if no candidate that improves the score is found.
post_crossover_check (bool) – If True, check if child produced from crossover step passes the constraints.
max_crossover_retries (int) – Maximum number of crossover retries if resulting child fails to pass the constraints. Applied only when post_crossover_check is set to True. Setting it to 0 means we immediately take one of the parents at random as the child upon failure.
- check_transformation_compatibility(transformation)[source]
The genetic algorithm is specifically designed for word substitutions.
- perform_search(initial_result)[source]
Perturbs attacked_text from
initial_result
until goal is reached or search is exhausted.Must be overridden by specific search methods.
- property is_black_box
Returns True if search method does not require access to victim model’s internal states.
Greedy Search
- class textattack.search_methods.greedy_search.GreedySearch[source]
Bases:
BeamSearch
A search method that greedily chooses from a list of possible perturbations.
Implemented by calling
BeamSearch
with beam_width set to 1.
Greedy Word Swap with Word Importance Ranking
When WIR method is set to unk
, this is a reimplementation of the search
method from the paper: Is BERT Really Robust?
A Strong Baseline for Natural Language Attack on Text Classification and Entailment by Jin et. al, 2019. See https://arxiv.org/abs/1907.11932 and https://github.com/jind11/TextFooler.
- class textattack.search_methods.greedy_word_swap_wir.GreedyWordSwapWIR(wir_method='unk', unk_token='[UNK]')[source]
Bases:
SearchMethod
An attack that greedily chooses from a list of possible perturbations in order of index, after ranking indices by importance.
- Parameters
wir_method – method for ranking most important words
model_wrapper – model wrapper used for gradient-based ranking
- check_transformation_compatibility(transformation)[source]
Since it ranks words by their importance, GreedyWordSwapWIR is limited to word swap and deletion transformations.
- perform_search(initial_result)[source]
Perturbs attacked_text from
initial_result
until goal is reached or search is exhausted.Must be overridden by specific search methods.
- property is_black_box
Returns True if search method does not require access to victim model’s internal states.
Reimplementation of search method from Xiaosen Wang, Hao Jin, Kun He (2019).
Natural Language Adversarial Attack and Defense in Word Level. http://arxiv.org/abs/1909.06723
- class textattack.search_methods.improved_genetic_algorithm.ImprovedGeneticAlgorithm(pop_size=60, max_iters=20, temp=0.3, give_up_if_no_improvement=False, post_crossover_check=True, max_crossover_retries=20, max_replace_times_per_index=5)[source]
Bases:
GeneticAlgorithm
Attacks a model with word substiutitions using a genetic algorithm.
- Parameters
pop_size (int) – The population size. Defaults to 20.
max_iters (int) – The maximum number of iterations to use. Defaults to 50.
temp (float) – Temperature for softmax function used to normalize probability dist when sampling parents. Higher temperature increases the sensitivity to lower probability candidates.
give_up_if_no_improvement (bool) – If True, stop the search early if no candidate that improves the score is found.
post_crossover_check (bool) – If True, check if child produced from crossover step passes the constraints.
max_crossover_retries (int) – Maximum number of crossover retries if resulting child fails to pass the constraints. Applied only when post_crossover_check is set to True. Setting it to 0 means we immediately take one of the parents at random as the child upon failure.
max_replace_times_per_index (int) – The maximum times words at the same index can be replaced in improved genetic algorithm.
Particle Swarm Optimization
Reimplementation of search method from Word-level Textual Adversarial Attacking as Combinatorial Optimization by Zang et.
al https://www.aclweb.org/anthology/2020.acl-main.540.pdf https://github.com/thunlp/SememePSO-Attack
- class textattack.search_methods.particle_swarm_optimization.ParticleSwarmOptimization(pop_size=60, max_iters=20, post_turn_check=True, max_turn_retries=20)[source]
Bases:
PopulationBasedSearch
Attacks a model with word substiutitions using a Particle Swarm Optimization (PSO) algorithm. Some key hyper-parameters are setup according to the original paper:
“We adjust PSO on the validation set of SST and set ω_1 as 0.8 and ω_2 as 0.2. We set the max velocity of the particles V_{max} to 3, which means the changing probability of the particles ranges from 0.047 (sigmoid(-3)) to 0.953 (sigmoid(3)).”
- Parameters
pop_size (
int
, optional) – The population size. Defaults to 60.max_iters (
int
, optional) – The maximum number of iterations to use. Defaults to 20.post_turn_check (
bool
, optional) – If True, check if new position reached by moving passes the constraints. Defaults to Truemax_turn_retries (
bool
, optional) – Maximum number of movement retries if new position after turning fails to pass the constraints. Applied only when post_movement_check is set to True. Setting it to 0 means we immediately take the old position as the new position upon failure.
- check_transformation_compatibility(transformation)[source]
The genetic algorithm is specifically designed for word substitutions.
- perform_search(initial_result)[source]
Perturbs attacked_text from
initial_result
until goal is reached or search is exhausted.Must be overridden by specific search methods.
- property is_black_box
Returns True if search method does not require access to victim model’s internal states.
Population based Search
- class textattack.search_methods.population_based_search.PopulationBasedSearch[source]
Bases:
SearchMethod
,ABC
Abstract base class for population-based search methods.
Examples include: genetic algorithm, particle swarm optimization
Search Method Abstract Class
- class textattack.search_methods.search_method.SearchMethod[source]
Bases:
ReprMixin
,ABC
This is an abstract class that contains main helper functionality for search methods.
A search method is a strategy for applying transformations until the goal is met or the search is exhausted.
- check_transformation_compatibility(transformation)[source]
Determines whether this search method is compatible with
transformation
.
- abstract perform_search(initial_result)[source]
Perturbs attacked_text from
initial_result
until goal is reached or search is exhausted.Must be overridden by specific search methods.
- property is_black_box
Returns True if search method does not require access to victim model’s internal states.