TextAttack Documentation

Get Started

• Basic-Introduction
  • What is TextAttack?
  • Where should I start?
  • NLP Attacks
  • Data Augmentation
  • Features
• Installation
  • Install with pip
  • Install from Source
  • Optional Dependencies
  • FAQ on installation
• Command-Line Usage
  • Data Augmentation with textattack augment
  • Adversarial Attacks with textattack attack
  • Training Models with textattack train
    • Available Models
      • TextAttack Models
      • transformers Models
  • Evaluating Models with textattack eval-model
  • Other Commands
    • Checkpoints and textattack attack-resume
    • Listing features with textattack list
    • Examining datasets with textattack peek-dataset
• Quick API Usage
  • Attacking a BERT model
• FAQ
  • Via Slack: Where to Ask Questions:
  • Via CLI: --help
  • Via our papers: More details on results
  • Via readthedocs: More details on APIs
  • More Concrete Questions:
    • 0. For many of the dependent library issues, the following command is the first you could try:
    • 1. How to Train
    • 2. Use Custom Models
      • Model from a file
    • 3. Use Custom Datasets
      • From a file
      • Dataset loading via other mechanism, see: more details at here
      • Custom Dataset via AttackedText class
    • 4. Benchmarking Attacks
    • 5. Create Custom or New Attacks
    • 6. The attacking is too slow

Recipes

• Attack Recipes CommandLine Use
  • Help: textattack --help
  • Running Attacks: textattack attack --help
  • Attacks and Papers Implemented (”Attack Recipes”): textattack attack --recipe [recipe_name]
  • Recipe Usage Examples
• Attack Recipes API
  • Attacks on classification models
    • A2T (A2T: Attack for Adversarial Training Recipe)
    • Alzantot Genetic Algorithm
    • Faster Alzantot Genetic Algorithm
    • BAE (BAE: BERT-Based Adversarial Examples)
    • BERT-Attack:
    • CheckList:
    • DeepWordBug
    • HotFlip
    • Improved Genetic Algorithm
    • Input Reduction
    • Kuleshov2017
    • Particle Swarm Optimization
    • PWWS
    • TextFooler (Is BERT Really Robust?)
    • TextBugger
    • CLARE Recipe
    • Pruthi2019: Combating with Robust Word Recognition
  • Attacks on sequence-to-sequence models
    • MORPHEUS2020
    • Seq2Sick
• Augmenter Recipes CommandLine Use
  • Augmenting Text: textattack augment
  • Augmentation Command-Line Interface
• Augmenter Recipes API
  • Augmenter Recipes:
• TextAttack Model Zoo
  • Available Models
    • TextAttack Models
    • transformers Models
  • Evaluation Results of Available Models
    • LSTM
    • wordCNN
    • albert-base-v2
    • bert-base-uncased
    • distilbert-base-cased
    • distilbert-base-uncased
    • roberta-base
    • xlnet-base-cased
  • How we have trained the TextAttack Models
  • Training details for each TextAttack Model
  • More details on TextAttack fine-tuned NLP models (details on target NLP task, input type, output type, SOTA results on paperswithcode; model card on huggingface):

Using TextAttack

• What is an adversarial attack in NLP?
  • Terminology
  • Adversarial Examples in NLP
  • Generating adversarial examples with TextAttack
  • The future of adversarial attacks in NLP
• How to Cite TextAttack
  • Main Paper: TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
    • Our Github on TextAttack: https://github.com/QData/TextAttack
  • Our Analysis paper: Reevaluating Adversarial Examples in Natural Language
    • Our Github on Reevaluation: Reevaluating-NLP-Adversarial-Examples Github
  • Our Analysis paper: Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples
    • Our Github on benchmarking: TextAttack-Search-Benchmark Github
  • Our defense paper: Title: “Towards Improving Adversarial Training of NLP Models”
    • Code is available
    • Citations:
  • Our extended use case paper: “Expanding Scope: Adapting English Adversarial Attacks to Chinese”
    • Abstract:
    • Venue:
    • Tutorial code:
    • Citations:
• Four Components of TextAttack Attacks
  • Goal Functions
  • Constraints
  • Transformations
  • Search Methods
  • On Benchmarking Attack Recipes
  • Four components in Attack Recipes we have implemented
• Benchmarking Search Algorithms for Generating NLP Adversarial Examples
  • Title: Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples
  • Our search benchmarking result Github
  • Our benchmarking results on comparing search methods used in the past attacks.
  • Benchmarking Attack Recipes
• On Quality of Generated Adversarial Examples and How to Set Attack Contraints
  • Title: Reevaluating Adversarial Examples in Natural Language
  • Our Github on Reevaluation: Reevaluating-NLP-Adversarial-Examples Github
  • Some of our evaluation results on quality of two SOTA attack recipes
  • Some of our evaluation results on how to set constraints to evaluate NLP model’s adversarial robustness
• Making Vanilla Adversarial Training of NLP Models Feasible!
  • Title: Towards Improving Adversarial Training of NLP Models
    • Video recording of this talk: https://underline.io/events/192/sessions/7928/lecture/38377-towards-improving-adversarial-training-of-nlp-models
  • Code is available
  • Citations:
  • A2T Attack Recipe
• Lessons learned in designing TextAttack
  • Presentations on TextAttack
    • 2020: Jack Morris’ summary tutorial talk on TextAttack
    • 2021: Dr. Qi’s summary tutorial talk on TextAttack
  • Challenges in Design
  • Our design tips
  • TextAttack flowchart
  • More Details in Reference
• TextAttack Extended Functions (Multilingual)
  • Textattack Supports Multiple Model Types besides huggingface models and our textattack models:
  • Multilingual Supports
  • User defined custom inputs and models
    • Custom Datasets: Dataset from a file
      • Custom Model: from a file
  • User defined Custom attack components
  • Visulizing TextAttack generated Examples;
• How can I contribute to TextAttack?
  • Slack Channel
  • Ways to contribute
  • Submitting a new issue or feature request
    • Found a bug?
    • Do you want to add your model?
    • Do you want a new feature: a component, a recipe, or something else?
  • Start contributing! (Pull Requests)
    • Checklist
    • Tests
      • This guide was heavily inspired by the awesome transformers guide to contributing

Notebook Tutorials

• Tutorial 0: TextAttack End-To-End (Train, Eval, Attack)
  • Training
  • Evaluation
  • Attack
  • Conclusion
  • Bonus
• Tutorial 1: Transformations
  • Goal function
  • Search method
  • Transformation
  • Constraints
  • A custom transformation
  • Banana word swap
  • Using our transformation
  • Creating the goal function, model, and dataset
  • Creating the attack
  • Using the attack
  • Visualizing attack results
  • Conclusion
  • Bonus: Attacking Custom Samples
• Tutorial 2: Constraints
  • Classes of constraints
  • A new constraint
  • A custom constraint
  • NLTK and Named Entity Recognition
  • NLTK NER Example
  • Caching with @functools.lru_cache
  • Putting it all together: getting a list of Named Entity Labels from a sentence
  • Creating our NamedEntityConstraint
  • Testing our constraint
  • Conclusion
• Tutorial 3: Augmentation
  • Creating an Augmenter
  • Pre-built Augmentation Recipes
  • Conclusion
• Tutorial 4: Custom Word Embeddings
  • Importing the Model
  • Creating A Custom Dataset
  • Creating An Attack
  • Attack Results With Custom Dataset
  • Creating A Custom Word Embedding
  • Attack Results With Custom Dataset and Word Embedding
• Tutorial 5: Attacking TensorFlow models
  • Run textattack on a trained tensorflow model:
    • First: Training
    • Attacking
  • Conclusion
• Tutorial 6: Attacking scikit-learn models
  • Training
  • Attacking
  • Conclusion
• Tutorial 7: Attacking AllenNLP models
• Tutorial 8: Attacking Keras models
  • This notebook runs textattack on a trained keras model:
  • Training
  • Attacking
  • Conclusion
• Tutorial 9: Attacking multilingual models
• Tutorial10: Explaining Attacking BERT model using Captum
• Tutorial11: Attacking multilingual - Chinese NLP model using Textattack

API User Guide

• Attack
  • Attack
    • Attack
      • Attack.attack()
      • Attack.cpu_()
      • Attack.cuda_()
      • Attack.filter_transformations()
      • Attack.get_indices_to_order()
      • Attack.get_transformations()
  • AttackRecipe
    • AttackRecipe
      • AttackRecipe.build()
• Attacker
  • Attacker
    • Attacker
      • Attacker.attack_dataset()
      • Attacker.from_checkpoint()
      • Attacker.update_attack_args()
  • AttackArgs
    • AttackArgs
      • AttackArgs.create_loggers_from_args()
• AttackResult
  • AttackResult
    • AttackResult
      • AttackResult.diff_color()
      • AttackResult.goal_function_result_str()
      • AttackResult.original_text()
      • AttackResult.perturbed_text()
      • AttackResult.str_lines()
  • SuccessfulAttackResult
    • SuccessfulAttackResult
  • FailedAttackResult
    • FailedAttackResult
      • FailedAttackResult.goal_function_result_str()
      • FailedAttackResult.str_lines()
  • SkippedAttackResult
    • SkippedAttackResult
      • SkippedAttackResult.goal_function_result_str()
      • SkippedAttackResult.str_lines()
  • MaximizedAttackResult
    • MaximizedAttackResult
• Trainer
  • Trainer
    • Trainer
      • Trainer.evaluate()
      • Trainer.evaluate_step()
      • Trainer.get_eval_dataloader()
      • Trainer.get_optimizer_and_scheduler()
      • Trainer.get_train_dataloader()
      • Trainer.train()
      • Trainer.training_step()
  • TrainingArgs
    • TrainingArgs
• Datasets
  • Dataset
    • Dataset
      • Dataset.__getitem__()
      • Dataset.__len__()
  • HuggingFaceDataset
    • HuggingFaceDataset
      • HuggingFaceDataset.__getitem__()
      • HuggingFaceDataset.__len__()
• GoalFunction
  • GoalFunction
    • GoalFunction
      • GoalFunction.extra_repr_keys()
      • GoalFunction.get_output()
      • GoalFunction.get_result()
      • GoalFunction.get_results()
      • GoalFunction.init_attack_example()
  • ClassificationGoalFunction
    • ClassificationGoalFunction
      • ClassificationGoalFunction.extra_repr_keys()
  • TargetedClassification
    • TargetedClassification
      • TargetedClassification.extra_repr_keys()
  • UntargetedClassification
    • UntargetedClassification
  • InputReduction
    • InputReduction
      • InputReduction.extra_repr_keys()
  • TextToTextGoalFunction
    • TextToTextGoalFunction
  • MinimizeBleu
    • MinimizeBleu
      • MinimizeBleu.extra_repr_keys()
  • NonOverlappingOutput
    • NonOverlappingOutput
• Constraints
  • Constraint
    • Constraint
      • Constraint.call_many()
      • Constraint.check_compatibility()
      • Constraint.extra_repr_keys()
  • PreTransformationConstraint
    • PreTransformationConstraint
      • PreTransformationConstraint.check_compatibility()
      • PreTransformationConstraint.extra_repr_keys()
• Transformations
  • Transformation
    • Transformation
  • Composite Transformation
    • CompositeTransformation
• SearchMethod
  • SearchMethod
    • SearchMethod
      • SearchMethod.check_transformation_compatibility()
      • SearchMethod.perform_search()
      • SearchMethod.is_black_box
  • BeamSearch
    • BeamSearch
      • BeamSearch.extra_repr_keys()
      • BeamSearch.perform_search()
      • BeamSearch.is_black_box
  • GreedySearch
    • GreedySearch
      • GreedySearch.extra_repr_keys()
  • GreedyWordSwapWIR
    • GreedyWordSwapWIR
      • GreedyWordSwapWIR.check_transformation_compatibility()
      • GreedyWordSwapWIR.extra_repr_keys()
      • GreedyWordSwapWIR.perform_search()
      • GreedyWordSwapWIR.is_black_box
  • AlzantotGeneticAlgorithm
    • AlzantotGeneticAlgorithm
  • ImprovedGeneticAlgorithm
    • ImprovedGeneticAlgorithm
      • ImprovedGeneticAlgorithm.extra_repr_keys()
  • ParticleSwarmOptimization
    • ParticleSwarmOptimization
      • ParticleSwarmOptimization.check_transformation_compatibility()
      • ParticleSwarmOptimization.extra_repr_keys()
      • ParticleSwarmOptimization.perform_search()
      • ParticleSwarmOptimization.is_black_box

Full Reference

• textattack package
  • textattack.attack_recipes package
    • Attack Recipes Package:
    • A2T (A2T: Attack for Adversarial Training Recipe)
    • A2TYoo2021
      • A2TYoo2021.build()
    • Attack Recipe Class
    • AttackRecipe
      • AttackRecipe.build()
    • BAE (BAE: BERT-Based Adversarial Examples)
    • BAEGarg2019
      • BAEGarg2019.build()
    • BERT-Attack:
    • BERTAttackLi2020
      • BERTAttackLi2020.build()
    • CheckList:
    • CheckList2020
      • CheckList2020.build()
    • CLARE Recipe
    • CLARE2020
      • CLARE2020.build()
    • DeepWordBug
    • DeepWordBugGao2018
      • DeepWordBugGao2018.build()
    • Faster Alzantot Genetic Algorithm
    • FasterGeneticAlgorithmJia2019
      • FasterGeneticAlgorithmJia2019.build()
    • Alzantot Genetic Algorithm
    • GeneticAlgorithmAlzantot2018
      • GeneticAlgorithmAlzantot2018.build()
    • HotFlip
    • HotFlipEbrahimi2017
      • HotFlipEbrahimi2017.build()
    • Improved Genetic Algorithm
    • IGAWang2019
      • IGAWang2019.build()
    • Input Reduction
    • InputReductionFeng2018
      • InputReductionFeng2018.build()
    • Kuleshov2017
    • Kuleshov2017
      • Kuleshov2017.build()
    • MORPHEUS2020
    • MorpheusTan2020
      • MorpheusTan2020.build()
    • Pruthi2019: Combating with Robust Word Recognition
    • Pruthi2019
      • Pruthi2019.build()
    • Particle Swarm Optimization
    • PSOZang2020
      • PSOZang2020.build()
    • PWWS
    • PWWSRen2019
      • PWWSRen2019.build()
    • Seq2Sick
    • Seq2SickCheng2018BlackBox
      • Seq2SickCheng2018BlackBox.build()
    • TextBugger
    • TextBuggerLi2018
      • TextBuggerLi2018.build()
    • TextFooler (Is BERT Really Robust?)
    • TextFoolerJin2019
      • TextFoolerJin2019.build()
  • textattack.attack_results package
    • TextAttack attack_results Package
    • AttackResult Class
    • AttackResult
      • AttackResult.diff_color()
      • AttackResult.goal_function_result_str()
      • AttackResult.original_text()
      • AttackResult.perturbed_text()
      • AttackResult.str_lines()
    • FailedAttackResult Class
    • FailedAttackResult
      • FailedAttackResult.goal_function_result_str()
      • FailedAttackResult.str_lines()
    • MaximizedAttackResult Class
    • MaximizedAttackResult
    • SkippedAttackResult Class
    • SkippedAttackResult
      • SkippedAttackResult.goal_function_result_str()
      • SkippedAttackResult.str_lines()
    • SuccessfulAttackResult Class
    • SuccessfulAttackResult
  • textattack.augmentation package
    • TextAttack augmentation package:
    • Augmenter Class
    • AugmentationResult
      • AugmentationResult.tempResult
    • Augmenter
      • Augmenter.augment()
      • Augmenter.augment_many()
      • Augmenter.augment_text_with_ids()
    • Augmenter Recipes:
    • BackTranscriptionAugmenter
    • BackTranslationAugmenter
    • CLAREAugmenter
    • CharSwapAugmenter
    • CheckListAugmenter
    • DeletionAugmenter
    • EasyDataAugmenter
      • EasyDataAugmenter.augment()
    • EmbeddingAugmenter
    • SwapAugmenter
    • SynonymInsertionAugmenter
    • WordNetAugmenter
  • textattack.commands package
    • TextAttack commands Package
    • AttackCommand class
    • AttackCommand
      • AttackCommand.register_subcommand()
      • AttackCommand.run()
    • AttackResumeCommand class
    • AttackResumeCommand
      • AttackResumeCommand.register_subcommand()
      • AttackResumeCommand.run()
    • AugmentCommand class
    • AugmentCommand
      • AugmentCommand.register_subcommand()
      • AugmentCommand.run()
    • BenchmarkRecipeCommand class
    • BenchmarkRecipeCommand
      • BenchmarkRecipeCommand.register_subcommand()
      • BenchmarkRecipeCommand.run()
    • EvalModelCommand class
    • EvalModelCommand
      • EvalModelCommand.get_preds()
      • EvalModelCommand.register_subcommand()
      • EvalModelCommand.run()
      • EvalModelCommand.test_model_on_dataset()
    • ModelEvalArgs
      • ModelEvalArgs.batch_size
      • ModelEvalArgs.num_examples
      • ModelEvalArgs.num_examples_offset
      • ModelEvalArgs.random_seed
    • ListThingsCommand class
    • ListThingsCommand
      • ListThingsCommand.register_subcommand()
      • ListThingsCommand.run()
      • ListThingsCommand.things()
    • PeekDatasetCommand class
    • PeekDatasetCommand
      • PeekDatasetCommand.register_subcommand()
      • PeekDatasetCommand.run()
    • TextAttack CLI main class
    • main()
    • TextAttackCommand
      • TextAttackCommand.register_subcommand()
      • TextAttackCommand.run()
    • TrainModelCommand class
    • TrainModelCommand
      • TrainModelCommand.register_subcommand()
      • TrainModelCommand.run()
  • textattack.constraints package
    • Constraints
    • textattack.constraints.grammaticality package
      • Grammaticality:
      • textattack.constraints.grammaticality.language_models package
        • non-pre Language Models:
        • textattack.constraints.grammaticality.language_models.google_language_model package
          • Google Language Models:
          • Google Language Models from Alzantot
          • GoogLMHelper
            • GoogLMHelper.clear_cache()
            • GoogLMHelper.get_words_probs()
            • GoogLMHelper.get_words_probs_uncached()
            • GoogLMHelper.CACHE_PATH
          • Google 1-Billion Words Language Model
          • GoogleLanguageModel
            • GoogleLanguageModel.check_compatibility()
            • GoogleLanguageModel.extra_repr_keys()
          • A library for loading 1B word benchmark dataset.
          • CharsVocabulary
            • CharsVocabulary.encode_chars()
            • CharsVocabulary.word_to_char_ids()
            • CharsVocabulary.max_word_length
            • CharsVocabulary.word_char_ids
          • LM1BDataset
            • LM1BDataset.get_batch()
            • LM1BDataset.vocab
          • Vocabulary
            • Vocabulary.decode()
            • Vocabulary.encode()
            • Vocabulary.id_to_word()
            • Vocabulary.word_to_id()
            • Vocabulary.bos
            • Vocabulary.eos
            • Vocabulary.size
            • Vocabulary.unk
          • get_batch()
          • Utils for loading 1B word benchmark dataset.
          • LoadModel()
        • textattack.constraints.grammaticality.language_models.learning_to_write package
          • “Learning To Write”
          • AdaptiveSoftmax
          • AdaptiveLoss
            • AdaptiveLoss.forward()
            • AdaptiveLoss.remap_target()
            • AdaptiveLoss.reset()
            • AdaptiveLoss.training
          • AdaptiveSoftmax
            • AdaptiveSoftmax.forward()
            • AdaptiveSoftmax.log_prob()
            • AdaptiveSoftmax.reset()
            • AdaptiveSoftmax.set_target()
            • AdaptiveSoftmax.training
          • Language model helpers
          • QueryHandler
            • QueryHandler.load_model()
            • QueryHandler.query()
            • QueryHandler.try_query()
          • util_reverse()
          • “Learning To Write” Language Model
          • LearningToWriteLanguageModel
            • LearningToWriteLanguageModel.get_log_probs_at_index()
            • LearningToWriteLanguageModel.CACHE_PATH
          • RNN Language Model
          • RNNModel
            • RNNModel.forward()
            • RNNModel.init_hidden()
            • RNNModel.init_weights()
            • RNNModel.training
        • GPT2 Language Models:
        • GPT2
          • GPT2.get_log_probs_at_index()
        • Language Models Constraint
        • LanguageModelConstraint
          • LanguageModelConstraint.extra_repr_keys()
          • LanguageModelConstraint.get_log_probs_at_index()
      • CoLA for Grammaticality
      • COLA
        • COLA.clear_cache()
        • COLA.extra_repr_keys()
      • LanguageTool Grammar Checker
      • LanguageTool
        • LanguageTool.extra_repr_keys()
        • LanguageTool.get_errors()
      • Part of Speech Constraint
      • PartOfSpeech
        • PartOfSpeech.check_compatibility()
        • PartOfSpeech.clear_cache()
        • PartOfSpeech.extra_repr_keys()
    • textattack.constraints.overlap package
      • Overlap Constraints
      • BLEU Constraints
      • BLEU
        • BLEU.extra_repr_keys()
      • chrF Constraints
      • chrF
        • chrF.extra_repr_keys()
      • Edit Distance Constraints
      • LevenshteinEditDistance
        • LevenshteinEditDistance.extra_repr_keys()
      • Max Perturb Words Constraints
      • MaxWordsPerturbed
        • MaxWordsPerturbed.extra_repr_keys()
      • METEOR Constraints
      • METEOR
        • METEOR.extra_repr_keys()
    • textattack.constraints.pre_transformation package
      • Pre-Transformation:
      • Input Column Modification
      • InputColumnModification
        • InputColumnModification.extra_repr_keys()
      • Max Modification Rate
      • MaxModificationRate
        • MaxModificationRate.extra_repr_keys()
      • Max Word Index Modification
      • MaxWordIndexModification
        • MaxWordIndexModification.extra_repr_keys()
      • Min Word Lenth
      • MinWordLength
      • Repeat Modification
      • RepeatModification
      • Stopword Modification
      • StopwordModification
        • StopwordModification.check_compatibility()
      • UnmodifiableIndices
        • UnmodifiableIndices.extra_repr_keys()
      • UnmodifablePhrases
        • UnmodifablePhrases.extra_repr_keys()
    • textattack.constraints.semantics package
      • Semantic Constraints
      • textattack.constraints.semantics.sentence_encoders package
        • Sentence Encoder Constraint
        • textattack.constraints.semantics.sentence_encoders.bert package
          • sBERT
          • sBERT for Sentence Similarity
          • SBERT
            • SBERT.encode()
        • textattack.constraints.semantics.sentence_encoders.infer_sent package
          • infer sent
          • infer sent for sentence similarity
          • InferSent
            • InferSent.encode()
            • InferSent.get_infersent_model()
            • InferSent.MODEL_PATH
            • InferSent.WORD_EMBEDDING_PATH
          • Infer sent model
          • InferSentModel
            • InferSentModel.build_vocab()
            • InferSentModel.build_vocab_k_words()
            • InferSentModel.encode()
            • InferSentModel.forward()
            • InferSentModel.get_batch()
            • InferSentModel.get_w2v()
            • InferSentModel.get_w2v_k()
            • InferSentModel.get_word_dict()
            • InferSentModel.is_cuda()
            • InferSentModel.prepare_samples()
            • InferSentModel.set_w2v_path()
            • InferSentModel.tokenize()
            • InferSentModel.update_vocab()
            • InferSentModel.training
        • textattack.constraints.semantics.sentence_encoders.universal_sentence_encoder package
          • Universal sentence encoder
          • multilingual universal sentence encoder
          • MultilingualUniversalSentenceEncoder
            • MultilingualUniversalSentenceEncoder.encode()
          • universal sentence encoder class
          • UniversalSentenceEncoder
            • UniversalSentenceEncoder.encode()
        • Sentence Encoder Class
        • SentenceEncoder
          • SentenceEncoder.encode()
          • SentenceEncoder.extra_repr_keys()
        • get_angular_sim()
        • get_neg_euclidean_dist()
        • Thought Vector Class
        • ThoughtVector
          • ThoughtVector.clear_cache()
          • ThoughtVector.encode()
          • ThoughtVector.extra_repr_keys()
      • BERT Score
      • BERTScore
        • BERTScore.extra_repr_keys()
        • BERTScore.SCORE_TYPE2IDX
      • Word Embedding Distance
      • WordEmbeddingDistance
        • WordEmbeddingDistance.check_compatibility()
        • WordEmbeddingDistance.extra_repr_keys()
        • WordEmbeddingDistance.get_cos_sim()
        • WordEmbeddingDistance.get_mse_dist()
    • TextAttack Constraint Class
    • Constraint
      • Constraint.call_many()
      • Constraint.check_compatibility()
      • Constraint.extra_repr_keys()
    • Pre-Transformation Constraint Class
    • PreTransformationConstraint
      • PreTransformationConstraint.check_compatibility()
      • PreTransformationConstraint.extra_repr_keys()
  • textattack.datasets package
    • datasets package:
    • textattack.datasets.helpers package
      • Dataset Helpers
      • Ted Multi TranslationDataset Class
      • TedMultiTranslationDataset
    • Dataset Class
    • Dataset
      • Dataset.filter_by_labels_()
      • Dataset.shuffle()
    • HuggingFaceDataset Class
    • HuggingFaceDataset
      • HuggingFaceDataset.filter_by_labels_()
      • HuggingFaceDataset.shuffle()
    • get_datasets_dataset_columns()
  • textattack.goal_function_results package
    • Goal Function Result package:
    • ClassificationGoalFunctionResult Class
    • ClassificationGoalFunctionResult
      • ClassificationGoalFunctionResult.get_colored_output()
      • ClassificationGoalFunctionResult.get_text_color_input()
      • ClassificationGoalFunctionResult.get_text_color_perturbed()
    • GoalFunctionResult class
    • GoalFunctionResult
      • GoalFunctionResult.get_colored_output()
      • GoalFunctionResult.get_text_color_input()
      • GoalFunctionResult.get_text_color_perturbed()
    • GoalFunctionResultStatus
      • GoalFunctionResultStatus.MAXIMIZING
      • GoalFunctionResultStatus.SEARCHING
      • GoalFunctionResultStatus.SKIPPED
      • GoalFunctionResultStatus.SUCCEEDED
    • TextToTextGoalFunctionResult Class
    • TextToTextGoalFunctionResult
      • TextToTextGoalFunctionResult.get_colored_output()
      • TextToTextGoalFunctionResult.get_text_color_input()
      • TextToTextGoalFunctionResult.get_text_color_perturbed()
  • textattack.goal_functions package
    • Goal Functions
    • textattack.goal_functions.classification package
      • Goal fucntion for Classification
      • Determine for if an attack has been successful in Classification
      • ClassificationGoalFunction
        • ClassificationGoalFunction.extra_repr_keys()
      • Determine if maintaining the same predicted label (input reduction)
      • InputReduction
        • InputReduction.extra_repr_keys()
      • Determine if an attack has been successful in targeted Classification
      • TargetedClassification
        • TargetedClassification.extra_repr_keys()
      • Determine successful in untargeted Classification
      • UntargetedClassification
    • textattack.goal_functions.text package
      • Goal Function for Text to Text case
      • Goal Function for Attempts to minimize the BLEU score
      • MinimizeBleu
        • MinimizeBleu.clear_cache()
        • MinimizeBleu.extra_repr_keys()
        • MinimizeBleu.EPS
      • get_bleu()
      • Goal Function for seq2sick
      • NonOverlappingOutput
        • NonOverlappingOutput.clear_cache()
      • get_words_cached()
      • word_difference_score()
      • Goal Function for TextToText
      • TextToTextGoalFunction
    • GoalFunction Class
    • GoalFunction
      • GoalFunction.clear_cache()
      • GoalFunction.extra_repr_keys()
      • GoalFunction.get_output()
      • GoalFunction.get_result()
      • GoalFunction.get_results()
      • GoalFunction.init_attack_example()
  • textattack.llms package
    • Large Language Models
    • HuggingFaceLLMWrapper
    • ChatGptWrapper
  • textattack.loggers package
    • Misc Loggers: Loggers track, visualize, and export attack results.
    • Managing Attack Logs.
    • AttackLogManager
      • AttackLogManager.add_output_csv()
      • AttackLogManager.add_output_file()
      • AttackLogManager.add_output_summary_json()
      • AttackLogManager.disable_color()
      • AttackLogManager.enable_stdout()
      • AttackLogManager.enable_visdom()
      • AttackLogManager.enable_wandb()
      • AttackLogManager.flush()
      • AttackLogManager.log_attack_details()
      • AttackLogManager.log_result()
      • AttackLogManager.log_results()
      • AttackLogManager.log_sep()
      • AttackLogManager.log_summary()
      • AttackLogManager.log_summary_rows()
      • AttackLogManager.metrics
    • Attack Logs to CSV
    • CSVLogger
      • CSVLogger.close()
      • CSVLogger.flush()
      • CSVLogger.log_attack_result()
    • Attack Logs to file
    • FileLogger
      • FileLogger.close()
      • FileLogger.flush()
      • FileLogger.log_attack_result()
      • FileLogger.log_sep()
      • FileLogger.log_summary_rows()
    • Attack Logger Wrapper
    • Logger
      • Logger.close()
      • Logger.flush()
      • Logger.log_attack_result()
      • Logger.log_hist()
      • Logger.log_sep()
      • Logger.log_summary_rows()
    • Attack Logs to Visdom
    • VisdomLogger
      • VisdomLogger.bar()
      • VisdomLogger.flush()
      • VisdomLogger.hist()
      • VisdomLogger.log_attack_result()
      • VisdomLogger.log_hist()
      • VisdomLogger.log_summary_rows()
      • VisdomLogger.table()
      • VisdomLogger.text()
    • port_is_open()
    • Attack Logs to WandB
    • WeightsAndBiasesLogger
      • WeightsAndBiasesLogger.log_attack_result()
      • WeightsAndBiasesLogger.log_sep()
      • WeightsAndBiasesLogger.log_summary_rows()
  • textattack.metrics package
    • metrics package: to calculate advanced metrics for evaluting attacks and augmented text
    • textattack.metrics.attack_metrics package
      • attack_metrics package:
      • Metrics on AttackQueries
      • AttackQueries
        • AttackQueries.avg_num_queries()
        • AttackQueries.calculate()
      • Metrics on AttackSuccessRate
      • AttackSuccessRate
        • AttackSuccessRate.attack_accuracy_perc()
        • AttackSuccessRate.attack_success_rate_perc()
        • AttackSuccessRate.calculate()
        • AttackSuccessRate.original_accuracy_perc()
      • Metrics on perturbed words
      • WordsPerturbed
        • WordsPerturbed.avg_number_word_perturbed_num()
        • WordsPerturbed.avg_perturbation_perc()
        • WordsPerturbed.calculate()
    • textattack.metrics.quality_metrics package
      • Metrics on Quality package
      • Perplexity Metric:
      • Perplexity
        • Perplexity.calc_ppl()
        • Perplexity.calculate()
      • USEMetric class:
      • USEMetric
        • USEMetric.calculate()
    • Metric Class
    • Metric
      • Metric.calculate()
  • textattack.models package
    • Models
      • Models User-specified
      • Models Pre-trained
      • Model Wrappers
    • textattack.models.helpers package
      • Moderl Helpers
      • Glove Embedding
      • EmbeddingLayer
        • EmbeddingLayer.forward()
        • EmbeddingLayer.training
      • GloveEmbeddingLayer
        • GloveEmbeddingLayer.EMBEDDING_PATH
        • GloveEmbeddingLayer.training
      • LSTM 4 Classification
      • LSTMForClassification
        • LSTMForClassification.forward()
        • LSTMForClassification.from_pretrained()
        • LSTMForClassification.get_input_embeddings()
        • LSTMForClassification.load_from_disk()
        • LSTMForClassification.save_pretrained()
        • LSTMForClassification.training
      • T5 model trained to generate text from text
      • T5ForTextToText
        • T5ForTextToText.from_pretrained()
        • T5ForTextToText.get_input_embeddings()
        • T5ForTextToText.save_pretrained()
        • T5ForTextToText.training
      • Util function for Model Wrapper
      • load_cached_state_dict()
      • Word CNN for Classification
      • CNNTextLayer
        • CNNTextLayer.forward()
        • CNNTextLayer.training
      • WordCNNForClassification
        • WordCNNForClassification.forward()
        • WordCNNForClassification.from_pretrained()
        • WordCNNForClassification.get_input_embeddings()
        • WordCNNForClassification.load_from_disk()
        • WordCNNForClassification.save_pretrained()
        • WordCNNForClassification.training
    • textattack.models.tokenizers package
      • Tokenizers for Model Wrapper
      • Glove Tokenizer
      • GloveTokenizer
        • GloveTokenizer.batch_encode()
        • GloveTokenizer.convert_ids_to_tokens()
        • GloveTokenizer.encode()
      • WordLevelTokenizer
      • T5 Tokenizer
      • T5Tokenizer
        • T5Tokenizer.decode()
    • textattack.models.wrappers package
      • Model Wrappers Package
      • HuggingFace Model Wrapper
      • HuggingFaceModelWrapper
        • HuggingFaceModelWrapper.get_grad()
      • ModelWrapper class
      • ModelWrapper
        • ModelWrapper.get_grad()
        • ModelWrapper.tokenize()
      • PyTorch Model Wrapper
      • PyTorchModelWrapper
        • PyTorchModelWrapper.get_grad()
        • PyTorchModelWrapper.to()
      • scikit-learn Model Wrapper
      • SklearnModelWrapper
        • SklearnModelWrapper.get_grad()
      • TensorFlow Model Wrapper
      • TensorFlowModelWrapper
        • TensorFlowModelWrapper.get_grad()
  • textattack.prompt_augmentation package
    • Prompt Augmentation
    • PromptAugmentationPipeline
  • textattack.search_methods package
    • Search Methods
    • Reimplementation of search method from Generating Natural Language Adversarial Examples
    • AlzantotGeneticAlgorithm
    • Beam Search
    • BeamSearch
      • BeamSearch.extra_repr_keys()
      • BeamSearch.perform_search()
      • BeamSearch.is_black_box
    • Genetic Algorithm Word Swap
    • GeneticAlgorithm
      • GeneticAlgorithm.check_transformation_compatibility()
      • GeneticAlgorithm.extra_repr_keys()
      • GeneticAlgorithm.perform_search()
      • GeneticAlgorithm.is_black_box
    • Greedy Search
    • GreedySearch
      • GreedySearch.extra_repr_keys()
    • Greedy Word Swap with Word Importance Ranking
    • GreedyWordSwapWIR
      • GreedyWordSwapWIR.check_transformation_compatibility()
      • GreedyWordSwapWIR.extra_repr_keys()
      • GreedyWordSwapWIR.perform_search()
      • GreedyWordSwapWIR.is_black_box
    • Reimplementation of search method from Xiaosen Wang, Hao Jin, Kun He (2019).
    • ImprovedGeneticAlgorithm
      • ImprovedGeneticAlgorithm.extra_repr_keys()
    • Particle Swarm Optimization
    • ParticleSwarmOptimization
      • ParticleSwarmOptimization.check_transformation_compatibility()
      • ParticleSwarmOptimization.extra_repr_keys()
      • ParticleSwarmOptimization.perform_search()
      • ParticleSwarmOptimization.is_black_box
    • normalize()
    • Population based Search abstract class
    • PopulationBasedSearch
    • PopulationMember
      • PopulationMember.num_words
      • PopulationMember.score
      • PopulationMember.words
    • Search Method Abstract Class
    • SearchMethod
      • SearchMethod.check_transformation_compatibility()
      • SearchMethod.get_victim_model()
      • SearchMethod.perform_search()
      • SearchMethod.is_black_box
  • textattack.shared package
    • Shared TextAttack Functions
    • textattack.shared.utils package
      • LazyLoader
      • load_module_from_file()
      • download_from_s3()
      • download_from_url()
      • http_get()
      • path_in_cache()
      • s3_url()
      • set_cache_dir()
      • unzip_file()
      • get_textattack_model_num_labels()
      • hashable()
      • html_style_from_dict()
      • html_table_from_rows()
      • load_textattack_model_from_path()
      • set_seed()
      • sigmoid()
      • ANSI_ESCAPE_CODES
        • ANSI_ESCAPE_CODES.BOLD
        • ANSI_ESCAPE_CODES.BROWN
        • ANSI_ESCAPE_CODES.CYAN
        • ANSI_ESCAPE_CODES.FAIL
        • ANSI_ESCAPE_CODES.GRAY
        • ANSI_ESCAPE_CODES.HEADER
        • ANSI_ESCAPE_CODES.OKBLUE
        • ANSI_ESCAPE_CODES.OKGREEN
        • ANSI_ESCAPE_CODES.ORANGE
        • ANSI_ESCAPE_CODES.PINK
        • ANSI_ESCAPE_CODES.PURPLE
        • ANSI_ESCAPE_CODES.STOP
        • ANSI_ESCAPE_CODES.UNDERLINE
        • ANSI_ESCAPE_CODES.WARNING
        • ANSI_ESCAPE_CODES.YELLOW
      • ReprMixin
        • ReprMixin.extra_repr_keys()
      • TextAttackFlairTokenizer
        • TextAttackFlairTokenizer.tokenize()
      • add_indent()
      • check_if_punctuations()
      • check_if_subword()
      • color_from_label()
      • color_from_output()
      • color_text()
      • default_class_repr()
      • flair_tag()
      • has_letter()
      • is_one_word()
      • process_label_name()
      • strip_BPE_artifacts()
      • words_from_text()
      • zip_flair_result()
      • zip_stanza_result()
      • batch_model_predict()
    • Attacked Text Class
    • AttackedText
      • AttackedText.align_with_model_tokens()
      • AttackedText.all_words_diff()
      • AttackedText.convert_from_original_idxs()
      • AttackedText.delete_word_at_index()
      • AttackedText.first_word_diff()
      • AttackedText.first_word_diff_index()
      • AttackedText.free_memory()
      • AttackedText.generate_new_attacked_text()
      • AttackedText.get_deletion_indices()
      • AttackedText.insert_text_after_word_index()
      • AttackedText.insert_text_before_word_index()
      • AttackedText.ith_word_diff()
      • AttackedText.ner_of_word_index()
      • AttackedText.pos_of_word_index()
      • AttackedText.printable_text()
      • AttackedText.replace_word_at_index()
      • AttackedText.replace_words_at_indices()
      • AttackedText.text_after_word_index()
      • AttackedText.text_until_word_index()
      • AttackedText.text_window_around_index()
      • AttackedText.words_diff_num()
      • AttackedText.words_diff_ratio()
      • AttackedText.SPLIT_TOKEN
      • AttackedText.column_labels
      • AttackedText.newly_swapped_words
      • AttackedText.num_words
      • AttackedText.text
      • AttackedText.tokenizer_input
      • AttackedText.words
      • AttackedText.words_per_input
    • Misc Checkpoints
    • AttackCheckpoint
      • AttackCheckpoint.load()
      • AttackCheckpoint.save()
      • AttackCheckpoint.dataset_offset
      • AttackCheckpoint.datetime
      • AttackCheckpoint.num_failed_attacks
      • AttackCheckpoint.num_maximized_attacks
      • AttackCheckpoint.num_remaining_attacks
      • AttackCheckpoint.num_skipped_attacks
      • AttackCheckpoint.num_successful_attacks
      • AttackCheckpoint.results_count
    • Shared data fields
    • Misc Validators
    • transformation_consists_of()
    • transformation_consists_of_word_swaps()
    • transformation_consists_of_word_swaps_and_deletions()
    • validate_model_goal_function_compatibility()
    • validate_model_gradient_word_swap_compatibility()
    • Shared loads word embeddings and related distances
    • AbstractWordEmbedding
      • AbstractWordEmbedding.get_cos_sim()
      • AbstractWordEmbedding.get_mse_dist()
      • AbstractWordEmbedding.index2word()
      • AbstractWordEmbedding.nearest_neighbours()
      • AbstractWordEmbedding.word2index()
    • GensimWordEmbedding
      • GensimWordEmbedding.get_cos_sim()
      • GensimWordEmbedding.get_mse_dist()
      • GensimWordEmbedding.index2word()
      • GensimWordEmbedding.nearest_neighbours()
      • GensimWordEmbedding.word2index()
    • WordEmbedding
      • WordEmbedding.counterfitted_GLOVE_embedding()
      • WordEmbedding.get_cos_sim()
      • WordEmbedding.get_mse_dist()
      • WordEmbedding.index2word()
      • WordEmbedding.nearest_neighbours()
      • WordEmbedding.word2index()
      • WordEmbedding.PATH
  • textattack.transformations package
    • Transformations
    • textattack.transformations.sentence_transformations package
      • sentence_transformations package
      • BackTranslation class
      • BackTranslation
        • BackTranslation.translate()
      • BackTranscription class
      • BackTranscription
        • BackTranscription.back_transcribe()
      • SentenceTransformation class
      • SentenceTransformation
    • textattack.transformations.word_insertions package
      • word_insertions package
      • WordInsertion Class
      • WordInsertion
      • WordInsertionMaskedLM Class
      • WordInsertionMaskedLM
        • WordInsertionMaskedLM.extra_repr_keys()
      • WordInsertionRandomSynonym Class
      • WordInsertionRandomSynonym
        • WordInsertionRandomSynonym.deterministic
      • check_if_one_word()
    • textattack.transformations.word_merges package
      • word_merges package
      • Word Merge
      • WordMerge
      • WordMergeMaskedLM class
      • WordMergeMaskedLM
        • WordMergeMaskedLM.extra_repr_keys()
      • find_merge_index()
    • textattack.transformations.word_swaps package
      • word_swaps package
      • Word Swap
      • WordSwap
      • Word Swap by Changing Location
      • WordSwapChangeLocation
      • idx_to_words()
      • Word Swap by Changing Name
      • WordSwapChangeName
      • Word Swap by Changing Number
      • WordSwapChangeNumber
      • idx_to_words()
      • Word Swap by Contraction
      • WordSwapContract
        • WordSwapContract.reverse_contraction_map
      • Word Swap by Embedding
      • WordSwapEmbedding
        • WordSwapEmbedding.extra_repr_keys()
      • recover_word_case()
      • Word Swap by Extension
      • WordSwapExtend
      • Word Swap by Gradient
      • WordSwapGradientBased
        • WordSwapGradientBased.extra_repr_keys()
      • Word Swap by Homoglyph
      • WordSwapHomoglyphSwap
        • WordSwapHomoglyphSwap.extra_repr_keys()
        • WordSwapHomoglyphSwap.deterministic
      • Word Swap by OpenHowNet
      • WordSwapHowNet
        • WordSwapHowNet.extra_repr_keys()
        • WordSwapHowNet.PATH
      • recover_word_case()
      • Word Swap by inflections
      • WordSwapInflections
      • Word Swap by BERT-Masked LM.
      • WordSwapMaskedLM
        • WordSwapMaskedLM.extra_repr_keys()
      • recover_word_case()
      • Word Swap by Neighboring Character Swap
      • WordSwapNeighboringCharacterSwap
        • WordSwapNeighboringCharacterSwap.extra_repr_keys()
        • WordSwapNeighboringCharacterSwap.deterministic
      • Word Swap by swaps characters with QWERTY adjacent keys
      • WordSwapQWERTY
        • WordSwapQWERTY.deterministic
      • Word Swap by Random Character Deletion
      • WordSwapRandomCharacterDeletion
        • WordSwapRandomCharacterDeletion.extra_repr_keys()
        • WordSwapRandomCharacterDeletion.deterministic
      • Word Swap by Random Character Insertion
      • WordSwapRandomCharacterInsertion
        • WordSwapRandomCharacterInsertion.extra_repr_keys()
        • WordSwapRandomCharacterInsertion.deterministic
      • Word Swap by Random Character Substitution
      • WordSwapRandomCharacterSubstitution
        • WordSwapRandomCharacterSubstitution.extra_repr_keys()
        • WordSwapRandomCharacterSubstitution.deterministic
      • Word Swap by swapping synonyms in WordNet
      • WordSwapWordNet
    • Composite Transformation
    • CompositeTransformation
    • Transformation Abstract Class
    • Transformation
      • Transformation.deterministic
    • word deletion Transformation
    • WordDeletion
    • Word Swap Transformation by swapping the order of words
    • WordInnerSwapRandom
      • WordInnerSwapRandom.deterministic
  • Attack Class
  • Attack
    • Attack.attack()
    • Attack.clear_cache()
    • Attack.cpu_()
    • Attack.cuda_()
    • Attack.filter_transformations()
    • Attack.get_indices_to_order()
    • Attack.get_transformations()
  • AttackArgs Class
  • AttackArgs
    • AttackArgs.create_loggers_from_args()
    • AttackArgs.attack_n
    • AttackArgs.checkpoint_dir
    • AttackArgs.checkpoint_interval
    • AttackArgs.csv_coloring_style
    • AttackArgs.disable_stdout
    • AttackArgs.enable_advance_metrics
    • AttackArgs.log_summary_to_json
    • AttackArgs.log_to_csv
    • AttackArgs.log_to_txt
    • AttackArgs.log_to_visdom
    • AttackArgs.log_to_wandb
    • AttackArgs.metrics
    • AttackArgs.num_examples
    • AttackArgs.num_examples_offset
    • AttackArgs.num_successful_examples
    • AttackArgs.num_workers_per_device
    • AttackArgs.parallel
    • AttackArgs.query_budget
    • AttackArgs.random_seed
    • AttackArgs.shuffle
    • AttackArgs.silent
  • CommandLineAttackArgs
  • Attacker Class
  • Attacker
    • Attacker.attack_dataset()
    • Attacker.attack_interactive()
    • Attacker.from_checkpoint()
    • Attacker.update_attack_args()
  • attack_from_queue()
  • pytorch_multiprocessing_workaround()
  • set_env_variables()
  • AugmenterArgs Class
  • AugmenterArgs
    • AugmenterArgs.enable_advanced_metrics
    • AugmenterArgs.exclude_original
    • AugmenterArgs.fast_augment
    • AugmenterArgs.high_yield
    • AugmenterArgs.input_column
    • AugmenterArgs.input_csv
    • AugmenterArgs.interactive
    • AugmenterArgs.output_csv
    • AugmenterArgs.overwrite
    • AugmenterArgs.pct_words_to_swap
    • AugmenterArgs.random_seed
    • AugmenterArgs.recipe
    • AugmenterArgs.transformations_per_example
  • DatasetArgs Class
  • DatasetArgs
    • DatasetArgs.dataset_by_model
    • DatasetArgs.dataset_from_file
    • DatasetArgs.dataset_from_huggingface
    • DatasetArgs.dataset_split
    • DatasetArgs.filter_by_labels
  • ModelArgs Class
  • ModelArgs
    • ModelArgs.model
    • ModelArgs.model_from_file
    • ModelArgs.model_from_huggingface
  • Trainer Class
  • Trainer
    • Trainer.evaluate()
    • Trainer.evaluate_step()
    • Trainer.get_eval_dataloader()
    • Trainer.get_optimizer_and_scheduler()
    • Trainer.get_train_dataloader()
    • Trainer.train()
    • Trainer.training_step()
  • TrainingArgs Class
  • CommandLineTrainingArgs
    • CommandLineTrainingArgs.output_dir
  • TrainingArgs
    • TrainingArgs.alpha
    • TrainingArgs.attack_epoch_interval
    • TrainingArgs.attack_num_workers_per_device
    • TrainingArgs.checkpoint_interval_epochs
    • TrainingArgs.checkpoint_interval_steps
    • TrainingArgs.early_stopping_epochs
    • TrainingArgs.gradient_accumulation_steps
    • TrainingArgs.learning_rate
    • TrainingArgs.load_best_model_at_end
    • TrainingArgs.log_to_tb
    • TrainingArgs.log_to_wandb
    • TrainingArgs.logging_interval_step
    • TrainingArgs.num_clean_epochs
    • TrainingArgs.num_epochs
    • TrainingArgs.num_train_adv_examples
    • TrainingArgs.num_warmup_steps
    • TrainingArgs.output_dir
    • TrainingArgs.parallel
    • TrainingArgs.per_device_eval_batch_size
    • TrainingArgs.per_device_train_batch_size
    • TrainingArgs.query_budget_train
    • TrainingArgs.random_seed
    • TrainingArgs.save_last
    • TrainingArgs.tb_log_dir
    • TrainingArgs.wandb_project
    • TrainingArgs.weight_decay
  • default_output_dir()