reformatting with python3.9 black

textattack/__init__.py

@@ -9,6 +9,7 @@
 
 TextAttack provides components for common NLP tasks like sentence encoding, grammar-checking, and word replacement that can be used on their own.
 """
+
 from .attack_args import AttackArgs, CommandLineAttackArgs
 from .augment_args import AugmenterArgs
 from .dataset_args import DatasetArgs

textattack/attack.py

@@ -83,8 +83,8 @@ def __init__(
         constraints: List[Union[Constraint, PreTransformationConstraint]],
         transformation: Transformation,
         search_method: SearchMethod,
-        transformation_cache_size=2 ** 15,
-        constraint_cache_size=2 ** 15,
+        transformation_cache_size=2**15,
+        constraint_cache_size=2**15,
     ):
         """Initialize an attack object.
 
@@ -372,9 +372,9 @@ def filter_transformations(
                 uncached_texts.append(transformed_text)
             else:
                 # promote transformed_text to the top of the LRU cache
-                self.constraints_cache[
-                    (current_text, transformed_text)
-                ] = self.constraints_cache[(current_text, transformed_text)]
+                self.constraints_cache[(current_text, transformed_text)] = (
+                    self.constraints_cache[(current_text, transformed_text)]
+                )
                 if self.constraints_cache[(current_text, transformed_text)]:
                     filtered_texts.append(transformed_text)
         filtered_texts += self._filter_transformations_uncached(

textattack/attack_args.py

@@ -507,8 +507,8 @@ class _CommandLineAttackArgs:
     interactive: bool = False
     parallel: bool = False
     model_batch_size: int = 32
-    model_cache_size: int = 2 ** 18
-    constraint_cache_size: int = 2 ** 18
+    model_cache_size: int = 2**18
+    constraint_cache_size: int = 2**18
 
     @classmethod
     def _add_parser_args(cls, parser):

textattack/attack_recipes/bae_garg_2019.py

@@ -3,6 +3,7 @@
 ============================================
 
 """
+
 from textattack.constraints.grammaticality import PartOfSpeech
 from textattack.constraints.pre_transformation import (
     RepeatModification,

textattack/attack_recipes/bert_attack_li_2020.py

@@ -10,6 +10,7 @@
     Consider using smaller values for "max_candidates".
 
 """
+
 from textattack import Attack
 from textattack.constraints.overlap import MaxWordsPerturbed
 from textattack.constraints.pre_transformation import (

textattack/attack_recipes/checklist_ribeiro_2020.py

@@ -5,6 +5,7 @@
 (Beyond Accuracy: Behavioral Testing of NLP models with CheckList)
 
 """
+
 from textattack import Attack
 from textattack.constraints.pre_transformation import RepeatModification
 from textattack.goal_functions import UntargetedClassification

textattack/attack_recipes/hotflip_ebrahimi_2017.py

@@ -5,6 +5,7 @@
 (HotFlip: White-Box Adversarial Examples for Text Classification)
 
 """
+
 from textattack import Attack
 from textattack.constraints.grammaticality import PartOfSpeech
 from textattack.constraints.overlap import MaxWordsPerturbed

textattack/attack_recipes/iga_wang_2019.py

@@ -6,6 +6,7 @@
 (Natural Language Adversarial Attacks and Defenses in Word Level)
 
 """
+
 from textattack import Attack
 from textattack.constraints.overlap import MaxWordsPerturbed
 from textattack.constraints.pre_transformation import StopwordModification

textattack/attack_recipes/input_reduction_feng_2018.py

@@ -5,6 +5,7 @@
 (Pathologies of Neural Models Make Interpretations Difficult)
 
 """
+
 from textattack import Attack
 from textattack.constraints.pre_transformation import (
     RepeatModification,

textattack/attack_recipes/kuleshov_2017.py

@@ -4,6 +4,7 @@
 (Adversarial Examples for Natural Language Classification Problems)
 
 """
+
 from textattack import Attack
 from textattack.constraints.grammaticality.language_models import GPT2
 from textattack.constraints.overlap import MaxWordsPerturbed

textattack/attack_recipes/morpheus_tan_2020.py

@@ -5,6 +5,7 @@
 
 
 """
+
 from textattack import Attack
 from textattack.constraints.pre_transformation import (
     RepeatModification,

textattack/attack_recipes/pruthi_2019.py

@@ -3,6 +3,7 @@
 =================================================================
 
 """
+
 from textattack import Attack
 from textattack.constraints.overlap import MaxWordsPerturbed
 from textattack.constraints.pre_transformation import (

textattack/attack_recipes/pso_zang_2020.py

@@ -6,6 +6,7 @@
 (Word-level Textual Adversarial Attacking as Combinatorial Optimization)
 
 """
+
 from textattack import Attack
 from textattack.constraints.pre_transformation import (
     InputColumnModification,

textattack/attack_recipes/pwws_ren_2019.py

@@ -6,6 +6,7 @@
 (Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency)
 
 """
+
 from textattack import Attack
 from textattack.constraints.pre_transformation import (
     RepeatModification,

textattack/attack_recipes/seq2sick_cheng_2018_blackbox.py

@@ -4,6 +4,7 @@
 ================================================
 (Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples)
 """
+
 from textattack import Attack
 from textattack.constraints.overlap import LevenshteinEditDistance
 from textattack.constraints.pre_transformation import (

textattack/attack_results/successful_attack_result.py

@@ -4,7 +4,6 @@
 
 """
 
-
 from .attack_result import AttackResult
 
 

textattack/augment_args.py

@@ -3,7 +3,6 @@
 ===================
 """
 
-
 from dataclasses import dataclass
 
 AUGMENTATION_RECIPE_NAMES = {

textattack/augmentation/__init__.py

@@ -6,7 +6,6 @@
 Transformations and constraints can be used outside of an attack for simple NLP data augmentation with the ``Augmenter`` class that returns all possible transformations for a given string.
 """
 
-
 from .augmenter import Augmenter
 from .recipes import (
     WordNetAugmenter,

textattack/augmentation/augmenter.py

@@ -2,6 +2,7 @@
 Augmenter Class
 ===================
 """
+
 import random
 
 import tqdm

textattack/augmentation/recipes.py

@@ -5,6 +5,7 @@
 Transformations and constraints can be used for simple NLP data augmentations. Here is a list of recipes for NLP data augmentations
 
 """
+
 import random
 
 from textattack.constraints.pre_transformation import (

textattack/commands/__init__.py

@@ -5,7 +5,6 @@
 
 """
 
-
 from abc import ABC, abstractmethod
 from .textattack_command import TextAttackCommand
 from . import textattack_cli

textattack/commands/eval_model_command.py

@@ -5,7 +5,6 @@
 
 """
 
-
 from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
 from dataclasses import dataclass
 

textattack/commands/textattack_cli.py

@@ -5,7 +5,6 @@
 
 """
 
-
 # !/usr/bin/env python
 import argparse
 

textattack/commands/train_model_command.py

@@ -5,7 +5,6 @@
 
 """
 
-
 from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
 
 from textattack import CommandLineTrainingArgs, Trainer

textattack/constraints/grammaticality/cola.py

@@ -3,6 +3,7 @@
 --------------------------
 
 """
+
 import lru
 import nltk
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
@@ -43,7 +44,7 @@ def __init__(
 
         self.max_diff = max_diff
         self.model_name = model_name
-        self._reference_score_cache = lru.LRU(2 ** 10)
+        self._reference_score_cache = lru.LRU(2**10)
         model = AutoModelForSequenceClassification.from_pretrained(model_name)
         tokenizer = AutoTokenizer.from_pretrained(model_name)
         self.model = HuggingFaceModelWrapper(model, tokenizer)

textattack/constraints/grammaticality/language_models/__init__.py

@@ -4,7 +4,6 @@
 
 """
 
-
 from .language_model_constraint import LanguageModelConstraint
 
 from .google_language_model import Google1BillionWordsLanguageModel

textattack/constraints/grammaticality/language_models/google_language_model/__init__.py

@@ -4,7 +4,6 @@
 
 """
 
-
 from .google_language_model import (
     GoogleLanguageModel as Google1BillionWordsLanguageModel,
 )

textattack/constraints/grammaticality/language_models/google_language_model/alzantot_goog_lm.py

@@ -7,7 +7,6 @@
     All rights reserved.
 """
 
-
 import os
 
 import lru
@@ -49,7 +48,7 @@ def __init__(self):
                 self.sess, self.graph, self.PBTXT_PATH, self.CKPT_PATH
             )
 
-        self.lm_cache = lru.LRU(2 ** 18)
+        self.lm_cache = lru.LRU(2**18)
 
     def clear_cache(self):
         self.lm_cache.clear()

textattack/constraints/grammaticality/language_models/google_language_model/google_language_model.py

@@ -3,6 +3,7 @@
 --------------------------------------
 
 """
+
 from collections import defaultdict
 
 import numpy as np

textattack/constraints/grammaticality/language_models/google_language_model/lm_utils.py

@@ -5,6 +5,7 @@
     Author: Moustafa Alzantot ([email protected])
     All rights reserved.
 """
+
 import sys
 
 from textattack.shared.utils import LazyLoader

textattack/constraints/grammaticality/language_models/gpt2.py

@@ -4,7 +4,6 @@
 
 """
 
-
 import os
 
 import torch

textattack/constraints/grammaticality/language_models/learning_to_write/__init__.py

@@ -3,4 +3,5 @@
 --------------------------
 
 """
+
 from .learning_to_write import LearningToWriteLanguageModel

textattack/constraints/grammaticality/language_models/learning_to_write/adaptive_softmax.py

@@ -3,7 +3,6 @@
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 """
 
-
 import torch
 from torch import nn
 from torch.autograd import Variable

textattack/constraints/grammaticality/language_models/learning_to_write/rnn_model.py

@@ -4,7 +4,6 @@
 
 """
 
-
 from torch import nn as nn
 from torch.autograd import Variable
 

textattack/constraints/grammaticality/language_tool.py

@@ -2,6 +2,7 @@
 LanguageTool Grammar Checker
 ------------------------------
 """
+
 import language_tool_python
 
 from textattack.constraints import Constraint

textattack/constraints/grammaticality/part_of_speech.py

@@ -2,6 +2,7 @@
 Part of Speech Constraint
 --------------------------
 """
+
 import flair
 from flair.data import Sentence
 from flair.models import SequenceTagger
@@ -56,7 +57,7 @@ def __init__(
         self.language_nltk = language_nltk
         self.language_stanza = language_stanza
 
-        self._pos_tag_cache = lru.LRU(2 ** 14)
+        self._pos_tag_cache = lru.LRU(2**14)
         if tagger_type == "flair":
             if tagset == "universal":
                 self._flair_pos_tagger = SequenceTagger.load("upos-fast")

textattack/constraints/overlap/meteor_score.py

@@ -6,7 +6,6 @@
 
 """
 
-
 import nltk
 
 from textattack.constraints import Constraint

textattack/constraints/pre_transformation/__init__.py

@@ -5,6 +5,7 @@
 
 Pre-transformation constraints determine if a transformation is valid based on only the original input and the position of the replacement. These constraints are applied before the transformation is even called. For example, these constraints can prevent search methods from swapping words at the same index twice, or from replacing stopwords.
 """
+
 from .stopword_modification import StopwordModification
 from .repeat_modification import RepeatModification
 from .input_column_modification import InputColumnModification

textattack/constraints/pre_transformation/max_modification_rate.py

@@ -4,6 +4,7 @@
 -----------------------------
 
 """
+
 import math
 
 from textattack.constraints import PreTransformationConstraint

textattack/constraints/pre_transformation/max_word_index_modification.py

@@ -4,6 +4,7 @@
 -----------------------------
 
 """
+
 from textattack.constraints import PreTransformationConstraint
 
 

textattack/constraints/semantics/__init__.py

@@ -4,6 +4,7 @@
 ---------------------
 Semantic constraints determine if a transformation is valid based on similarity of the semantics of the orignal input and the transformed input.
 """
+
 from . import sentence_encoders
 
 from .word_embedding_distance import WordEmbeddingDistance

textattack/constraints/semantics/sentence_encoders/__init__.py

@@ -3,7 +3,6 @@
 ----------------------------
 """
 
-
 from .sentence_encoder import SentenceEncoder
 
 from .sentence_bert import SBERT

textattack/constraints/semantics/sentence_encoders/infer_sent/__init__.py

@@ -3,5 +3,4 @@
 ^^^^^^^^^^^^
 """
 
-
 from .infer_sent import InferSent