How to use test_negation method in pyshould
Best Python code snippet using pyshould_python
prepro.py
Source:prepro.py 
1# Copyright (c) Microsoft. All rights reserved.2# Modified Copyright by Ubiquitous Knowledge Processing (UKP) Lab, Technische Universität Darmstadt3import argparse4from data_utils.log_wrapper import create_logger5from data_utils.glue_utils import *6import random7LOW_RESOURCE_DATA_RATES = [0.1, 0.3, 0.7]8bert_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')9logger = create_logger(__name__, to_disk=True, log_file='bert_data_proc_512.log')10def get_random_indices(dump_path, data, rate):11 rdm_indices = []12 if rate < 1.0:13 with open("data_splits/low_resource_splits/"+dump_path.rsplit("/", 1)[1].split("_")[0]+"_train.csv", "r") as split_file_in:14 rdm_indices = [int(idx) for idx in split_file_in.readline().split(",")[:int(len(data)*rate)]]15 return rdm_indices16def build_data(data, dump_path, rate=1.0, MAX_SEQ_LEN=100, is_train=True, tolower=True):17 """Build data of sentence pair tasks18 """19 if os.path.isfile(dump_path):20 print(dump_path + " already existis. Skipping!")21 return22 rdm_indices = get_random_indices(dump_path, data, rate)23 with open(dump_path, 'w', encoding='utf-8') as writer:24 for idx, sample in tqdm(enumerate(data)):25 if rate < 1.0 and idx not in rdm_indices:26 continue27 ids = sample['uid']28 premise = bert_tokenizer.tokenize(sample['premise'])29 hypothesis = bert_tokenizer.tokenize(sample['hypothesis'])30 label = sample['label']31 if "spelling" in dump_path or "negation" in dump_path: # have already been truncated in preprocessing step32 truncate_len = 512-333 else:34 truncate_len = MAX_SEQ_LEN - 335 truncate_seq_pair(premise, hypothesis, truncate_len)36 input_ids =bert_tokenizer.convert_tokens_to_ids(['[CLS]'] + hypothesis + ['[SEP]'] + premise + ['[SEP]'])37 type_ids = [0] * ( len(hypothesis) + 2) + [1] * (len(premise) + 1)38 features = {'uid': ids, 'label': label, 'token_id': input_ids, 'type_id': type_ids, 'hypothesis': sample['hypothesis'], 'premise': sample['premise']}39 writer.write('{}\n'.format(json.dumps(features)))40def build_data_single(data, dump_path, rate=1.0, MAX_SEQ_LEN=100):41 """Build data of single sentence tasks42 """43 if os.path.isfile(dump_path):44 print(dump_path + " already existis. Skipping!")45 return46 rdm_indices = get_random_indices(dump_path, data, rate)47 with open(dump_path, 'w', encoding='utf-8') as writer:48 for idx, sample in tqdm(enumerate(data)):49 if rate < 1.0 and idx not in rdm_indices:50 continue51 ids = sample['uid']52 premise = bert_tokenizer.tokenize(sample['premise'])53 label = sample['label']54 if "spelling" in dump_path or "negation" in dump_path: # have already been truncated in preprocessing step55 premise = premise[:512 - 3]56 elif len(premise) > MAX_SEQ_LEN - 3:57 premise = premise[:MAX_SEQ_LEN - 3]58 input_ids =bert_tokenizer.convert_tokens_to_ids(['[CLS]'] + premise + ['[SEP]'])59 type_ids = [0] * ( len(premise) + 2)60 features = {'uid': ids, 'label': label, 'token_id': input_ids, 'type_id': type_ids, 'premise': sample['premise']}61 writer.write('{}\n'.format(json.dumps(features)))62def print_status(train_data, dev_data, test_data, test_negation, test_spelling, test_paraphrase, dataset):63 logger.info('Loaded {0} {1} train samples'.format(len(train_data), dataset))64 logger.info('Loaded {0} {1} dev samples'.format(len(dev_data), dataset))65 logger.info('Loaded {0} {1} test samples'.format(len(test_data), dataset))66 if test_negation != None:67 logger.info('Loaded {0} {1} test negation samples'.format(len(test_negation), dataset))68 if test_spelling != None:69 logger.info('Loaded {0} {1} test spelling samples'.format(len(test_spelling), dataset))70 if test_paraphrase != None:71 logger.info('Loaded {0} {1} test paraphras samples'.format(len(test_paraphrase), dataset))72 logger.info('\n')73def build_handler(train_data, dev_data, test_data, test_negation, test_spelling, test_paraphrase,74 dataset, mt_dnn_root, single=False, MAX_SEQ_LEN=100):75 build_fn = build_data_single if single == True else build_data76 logger.info('Start converting and storing train/dev/test files for the model')77 train_fout = os.path.join(mt_dnn_root, '{0}_train.json'.format(dataset))78 dev_fout = os.path.join(mt_dnn_root, '{0}_dev.json'.format(dataset))79 test_fout = os.path.join(mt_dnn_root, '{0}_test.json'.format(dataset))80 test_negation_fout = os.path.join(mt_dnn_root, '{0}_test_negation.json'.format(dataset))81 test_spelling_fout = os.path.join(mt_dnn_root, '{0}_test_spelling.json'.format(dataset))82 test_paraphrase_fout = os.path.join(mt_dnn_root, '{0}_test_paraphrase.json'.format(dataset))83 for rate in LOW_RESOURCE_DATA_RATES:84 build_fn(train_data, train_fout.split(".json")[0]+str(int(rate*100))+"p.json", rate, MAX_SEQ_LEN=MAX_SEQ_LEN)85 build_fn(train_data, train_fout)86 build_fn(dev_data, dev_fout)87 build_fn(test_data, test_fout)88 if test_negation != None:89 build_fn(test_negation, test_negation_fout)90 if test_spelling != None:91 build_fn(test_spelling, test_spelling_fout)92 if test_paraphrase != None:93 build_fn(test_paraphrase, test_paraphrase_fout)94 logger.info('done with {0}'.format(dataset))95def parse_args():96 parser = argparse.ArgumentParser(description='Preprocessing datasets.')97 parser.add_argument('--seed', type=int, default=13)98 parser.add_argument('--root_dir', type=str, default='data')99 parser.add_argument('--generate_adversarial', type=int, default=0, help="0 if no adversarial samples should be created, otherwise 1")100 parser.add_argument('--max_seq_len', type=int, default=100)101 parser.add_argument('--opennmt_gpu', type=int, default=-1, help="-1 for CPU, else GPU index.")102 parser.add_argument('--opennmt_batch_size', type=int, default=30)103 args = parser.parse_args()104 return args105def main(args):106 root = args.root_dir107 seed = args.seed108 CREATE_ADVERSARIAL = True if args.generate_adversarial == 1 else False109 MAX_SEQ_LEN = args.max_seq_len110 OPENNMT_GPU = args.opennmt_gpu # Machine translation on GPU111 OPENNMT_BATCH_SIZE = args.opennmt_batch_size # Machine translation model batch size112 assert os.path.exists(root)113 random.seed(seed)114 np.random.seed(seed)115 mt_dnn_root = os.path.join(root, 'mt_dnn')116 if not os.path.isdir(mt_dnn_root):117 os.mkdir(mt_dnn_root)118 ######################################119 # Stance Detection Tasks120 ######################################121 snopes_path = os.path.join(root, 'Snopes/snopes_corpus_2.csv')122 argmin_path = os.path.join(root, 'ArgMin/')123 fnc1_path = os.path.join(root, 'FNC-1/')124 arc_path = os.path.join(root, 'ARC/')125 ibm_claim_stance_path = os.path.join(root, 'IBM_CLAIM_STANCE/claim_stance_dataset_v1.csv')126 perspectrum_path = os.path.join(root, 'PERSPECTRUM/')127 semeval2016t6_path = os.path.join(root, 'SemEval2016Task6/')128 semeval2019t7_path = os.path.join(root, 'SemEval2019Task7/')129 scd_path = os.path.join(root, 'SCD/')130 iac1_path = os.path.join(root, 'IAC/')131 ######################################132 # Loading / Building DATA133 ######################################134 scd_train_data, scd_dev_data, scd_test_data, scd_test_negation, scd_test_spelling, scd_test_paraphrase = \135 load_scd(scd_path, GLOBAL_MAP['scd'], create_adversarial=CREATE_ADVERSARIAL, dataset='scd', MAX_SEQ_LEN=MAX_SEQ_LEN,136 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)137 print_status(scd_train_data, scd_dev_data, scd_test_data, scd_test_negation, scd_test_spelling,138 scd_test_paraphrase, 'scd')139 build_handler(scd_train_data, scd_dev_data, scd_test_data, scd_test_negation,140 scd_test_spelling, scd_test_paraphrase, 'scd', mt_dnn_root, single=True, MAX_SEQ_LEN=MAX_SEQ_LEN)141 semeval2016t6_train_data, semeval2016t6_dev_data, semeval2016t6_test_data, semeval2016t6_test_negation, \142 semeval2016t6_test_spelling, semeval2016t6_test_paraphrase\143 = load_semeval2016t6(semeval2016t6_path, GLOBAL_MAP['semeval2016t6'], create_adversarial=CREATE_ADVERSARIAL,144 dataset='semeval2016t6', MAX_SEQ_LEN=MAX_SEQ_LEN,145 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)146 print_status(semeval2016t6_train_data, semeval2016t6_dev_data, semeval2016t6_test_data, semeval2016t6_test_negation,147 semeval2016t6_test_spelling, semeval2016t6_test_paraphrase, 'semeval2016t6')148 build_handler(semeval2016t6_train_data, semeval2016t6_dev_data, semeval2016t6_test_data, semeval2016t6_test_negation,149 semeval2016t6_test_spelling, semeval2016t6_test_paraphrase, 'semeval2016t6', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)150 ibmcs_train_data, ibmcs_dev_data, ibmcs_test_data, ibmcs_test_negation, ibmcs_test_spelling,\151 ibmcs_test_paraphrase = load_ibmcs(ibm_claim_stance_path, GLOBAL_MAP['ibmcs'], create_adversarial=CREATE_ADVERSARIAL,152 dataset='ibmcs', MAX_SEQ_LEN=MAX_SEQ_LEN,153 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)154 print_status(ibmcs_train_data, ibmcs_dev_data, ibmcs_test_data, ibmcs_test_negation,155 ibmcs_test_spelling, ibmcs_test_paraphrase, 'ibmcs')156 build_handler(ibmcs_train_data, ibmcs_dev_data, ibmcs_test_data, ibmcs_test_negation, ibmcs_test_spelling,157 ibmcs_test_paraphrase, 'ibmcs', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)158 iac1_train_data, iac1_dev_data, iac1_test_data, iac1_test_negation, iac1_test_spelling, iac1_test_paraphrase = \159 load_iac1(iac1_path, GLOBAL_MAP['iac1'], create_adversarial=CREATE_ADVERSARIAL, dataset='iac1', MAX_SEQ_LEN=MAX_SEQ_LEN,160 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)161 print_status(iac1_train_data, iac1_dev_data, iac1_test_data, iac1_test_negation, iac1_test_spelling,162 iac1_test_paraphrase, 'iac1')163 build_handler(iac1_train_data, iac1_dev_data, iac1_test_data, iac1_test_negation, iac1_test_spelling,164 iac1_test_paraphrase, 'iac1', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)165 snopes_train_data, snopes_dev_data, snopes_test_data, snopes_test_negation,\166 snopes_test_spelling, snopes_test_paraphrase = load_snopes(snopes_path, GLOBAL_MAP['snopes'],167 create_adversarial=CREATE_ADVERSARIAL,168 dataset='snopes', MAX_SEQ_LEN=MAX_SEQ_LEN,169 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)170 print_status(snopes_train_data, snopes_dev_data, snopes_test_data, snopes_test_negation,171 snopes_test_spelling, snopes_test_paraphrase, 'snopes')172 build_handler(snopes_train_data, snopes_dev_data, snopes_test_data, snopes_test_negation,173 snopes_test_spelling, snopes_test_paraphrase, 'snopes', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)174 arc_train_data, arc_dev_data, arc_test_data, arc_test_negation, arc_test_spelling, arc_test_paraphrase = \175 load_fnc1_arc(arc_path, GLOBAL_MAP['arc'], create_adversarial=CREATE_ADVERSARIAL,176 dataset='arc', MAX_SEQ_LEN=MAX_SEQ_LEN,177 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)178 print_status(arc_train_data, arc_dev_data, arc_test_data, arc_test_negation, arc_test_spelling,179 arc_test_paraphrase, 'arc')180 build_handler(arc_train_data, arc_dev_data, arc_test_data, arc_test_negation, arc_test_spelling,181 arc_test_paraphrase, 'arc', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)182 semeval2019t7_train_data, semeval2019t7_dev_data, semeval2019t7_test_data, semeval2019t7_test_negation, \183 semeval2019t7_test_spelling, semeval2019t7_test_paraphrase\184 = load_semeval2019t7(semeval2019t7_path, GLOBAL_MAP['semeval2019t7'], create_adversarial=CREATE_ADVERSARIAL,185 dataset='semeval2019t7', MAX_SEQ_LEN=MAX_SEQ_LEN,186 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)187 print_status(semeval2019t7_train_data, semeval2019t7_dev_data, semeval2019t7_test_data, semeval2019t7_test_negation,188 semeval2019t7_test_spelling, semeval2019t7_test_paraphrase, 'semeval2019t7')189 build_handler(semeval2019t7_train_data, semeval2019t7_dev_data, semeval2019t7_test_data, semeval2019t7_test_negation,190 semeval2019t7_test_spelling, semeval2019t7_test_paraphrase, 'semeval2019t7', mt_dnn_root, single=True, MAX_SEQ_LEN=MAX_SEQ_LEN)191 perspectrum_train_data, perspectrum_dev_data, perspectrum_test_data, perspectrum_test_negation, \192 perspectrum_test_spelling, perspectrum_test_paraphrase = load_perspectrum(perspectrum_path, GLOBAL_MAP['perspectrum'],193 create_adversarial=CREATE_ADVERSARIAL,194 dataset='perspectrum', MAX_SEQ_LEN=MAX_SEQ_LEN,195 OPENNMT_GPU=OPENNMT_GPU,196 OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)197 print_status(perspectrum_train_data, perspectrum_dev_data, perspectrum_test_data, perspectrum_test_negation,198 perspectrum_test_spelling, perspectrum_test_paraphrase, 'perspectrum')199 build_handler(perspectrum_train_data, perspectrum_dev_data, perspectrum_test_data, perspectrum_test_negation,200 perspectrum_test_spelling, perspectrum_test_paraphrase, 'perspectrum', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)201 argmin_train_data, argmin_dev_data, argmin_test_data, argmin_test_negation, \202 argmin_test_spelling, argmin_test_paraphrase = load_argmin(argmin_path, GLOBAL_MAP['argmin'],203 create_adversarial=CREATE_ADVERSARIAL,204 dataset='argmin', MAX_SEQ_LEN=MAX_SEQ_LEN,205 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)206 print_status(argmin_train_data, argmin_dev_data, argmin_test_data, argmin_test_negation,207 argmin_test_spelling, argmin_test_paraphrase, 'argmin')208 build_handler(argmin_train_data, argmin_dev_data, argmin_test_data, argmin_test_negation,209 argmin_test_spelling, argmin_test_paraphrase, 'argmin', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)210 fnc1_train_data, fnc1_dev_data, fnc1_test_data, fnc1_test_negation, fnc1_test_spelling,\211 fnc1_test_paraphrase = load_fnc1_arc(fnc1_path, GLOBAL_MAP['fnc1'], create_adversarial=CREATE_ADVERSARIAL,212 dataset='fnc1', MAX_SEQ_LEN=MAX_SEQ_LEN,213 OPENNMT_GPU=OPENNMT_GPU, OPENNMT_BATCH_SIZE=OPENNMT_BATCH_SIZE)214 print_status(fnc1_train_data, fnc1_dev_data, fnc1_test_data, fnc1_test_negation,215 fnc1_test_spelling, fnc1_test_paraphrase, 'fnc1')216 build_handler(fnc1_train_data, fnc1_dev_data, fnc1_test_data, fnc1_test_negation, fnc1_test_spelling,217 fnc1_test_paraphrase, 'fnc1', mt_dnn_root, MAX_SEQ_LEN=MAX_SEQ_LEN)218if __name__ == '__main__':219 args = parse_args()...
scanners_improved.py
Source:scanners_improved.py
...39 new_beacon[i] += translations[i]40 beacons[index] = new_beacon41 scanners[unknown_scanner]['position'] = translations42 return scanners43def apply_test_negation(test_negation, control_known_coordinates,44 control_unknown_coordinates, test_coordinates):45 altered_test_coordinates = test_coordinates46 translations = []47 for index, i in enumerate(test_negation):48 if i == '1':49 altered_test_coordinates[index] *= -150 control_unknown_coordinates[index] *= -151 translations.append(control_known_coordinates[index] - control_unknown_coordinates[index])52 altered_test_coordinates[index] = test_coordinates[index] + translations[index]53 return altered_test_coordinates, translations54def apply_movements(movements, coordinates):55 new_coordinates = deque(maxlen=3)56 for index in range(3):57 new_coordinates.append(coordinates[movements[index]])58 59 return new_coordinates60def get_negations_and_translations(scanners, adjustments, known_scanner,61 unknown_scanner, control_known_beacon, control_unknown_beacon,62 test_known_beacon, test_unknown_beacon):63 control_known_beacon_coordinates = scanners[known_scanner]['beacons'][control_known_beacon]64 control_unknown_beacon_coordinates = scanners[unknown_scanner]['beacons'][control_unknown_beacon]65 test_known_beacon_coordinates = scanners[known_scanner]['beacons'][test_known_beacon]66 test_unknown_beacon_coordinates = scanners[unknown_scanner]['beacons'][test_unknown_beacon]67 movements = adjustments['movements']68 moved_control_unknown_beacon_coordinates = apply_movements(movements, control_unknown_beacon_coordinates)69 moved_test_unknown_beacon_coordinates = apply_movements(movements, test_unknown_beacon_coordinates)70 for negation in range(8):71 test_negation = bin(negation)[2:].zfill(3)72 test_coordinates, translations = apply_test_negation(73 test_negation, control_known_beacon_coordinates,74 deepcopy(moved_control_unknown_beacon_coordinates),75 deepcopy(moved_test_unknown_beacon_coordinates))76 if test_coordinates == test_known_beacon_coordinates:77 adjustments['negations'] = test_negation78 adjustments['translations'] = translations79 break80 81 if not adjustments.get('negations', ''):82 print('Did not find negations, please interrupt program')83 return adjustments84def get_movements(scanners, diff_to_evaluate, known_scanner,85 known_scanner_index, unknown_scanner, unknown_scanner_index):86 movements = {}...
test_ldap3_query_classes.py
Source:test_ldap3_query_classes.py
...32 '''33 Test query join with a two elements34 '''35 self.assertEqual(str(self.test_object('|', '(givenName=John)', '(objectClass=*)', '(targetAttribute>=10)', '(cn=*John*Doe*)', '(givenName~=John)')), '(|(givenName=John)(objectClass=*)(targetAttribute>=10)(cn=*John*Doe*)(givenName~=John))')36 def test_negation(self):37 '''38 Test query join negation39 '''40 self.assertEqual(-self.test_object('|', '(givenName=John)', '(objectClass=*)', '(targetAttribute>=10)', '(cn=*John*Doe*)', '(givenName~=John)'), '(!(|(givenName=John)(objectClass=*)(targetAttribute>=10)(cn=*John*Doe*)(givenName~=John)))')41class TestQueryAssertion(unittest.TestCase):42 '''43 Tests for the QueryAssertion class44 '''45 46 def setUp(self):47 self.test_object = ldap3_directories.ldap3_.QueryAssertion48 self.maxDiff = None49 def test_implicit_equality(self):50 '''51 Test query assertion with implicit equality52 '''53 self.assertEqual(self.test_object('givenName', 'John'), '(givenName=John)')54 def test_explicit_equality(self):55 '''56 Test query assertion with explicit equality57 '''58 self.assertEqual(self.test_object('givenName', 'John', '='), '(givenName=John)')59 def test_presence(self):60 '''61 Test query assertion for presence62 '''63 self.assertEqual(self.test_object('objectClass', '*'), '(objectClass=*)')64 def test_greater_or_equal(self):65 '''66 Test query assertion with greater or equal67 '''68 self.assertEqual(self.test_object('targetAttribute', 10, '>='), '(targetAttribute>=10)')69 def test_less_or_equal(self):70 '''71 Test query assertion with less or equal72 '''73 self.assertEqual(self.test_object('targetAttribute', 10, '<='), '(targetAttribute<=10)')74 def test_substring(self):75 '''76 Test query assertion with substring77 '''78 self.assertEqual(self.test_object('cn', '*John*Doe*'), '(cn=*John*Doe*)')79 def test_approximate_match(self):80 '''81 Test query assertion with approximate match82 '''83 self.assertEqual(self.test_object('givenName', 'John', '~='), '(givenName~=John)')84 def test_negation(self):85 '''86 Test query assertion negated87 '''...
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