7.6 KiB
7.6 KiB
KENLM_BUILD_PATH='/home/students/s434708/kenlm/build'
Preprocessing danych
import pandas as pd
import csv
import regex as re
def clean_text(text):
text = text.lower().replace('-\\\\n', '').replace('\\\\n', ' ')
text = re.sub(r'\p{P}', '', text)
return text
train_data = pd.read_csv('train/in.tsv.xz', sep='\t', error_bad_lines=False, warn_bad_lines=False, header=None, quoting=csv.QUOTE_NONE)
train_labels = pd.read_csv('train/expected.tsv', sep='\t', error_bad_lines=False, warn_bad_lines=False, header=None, quoting=csv.QUOTE_NONE)
train_data = train_data[[6, 7]]
train_data = pd.concat([train_data, train_labels], axis=1)
train_data['text'] = train_data[6] + train_data[0] + train_data[7]
train_data = train_data[['text']]
with open('processed_train.txt', 'w') as file:
for _, row in train_data.iterrows():
text = clean_text(str(row['text']))
file.write(text + '\n')
Model kenLM
!$KENLM_BUILD_PATH/bin/lmplz -o 5 --skip_symbols < processed_train.txt > model.arpa
=== 1/5 Counting and sorting n-grams === Reading /home/students/s434708/Desktop/Modelowanie Języka/challenging-america-word-gap-prediction-kenlm/processed_train.txt ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 ********************************Warning: <s> appears in the input. All instances of <s>, </s>, and <unk> will be interpreted as whitespace. ******************************************************************** Unigram tokens 135911223 types 4381594 === 2/5 Calculating and sorting adjusted counts === Chain sizes: 1:52579128 2:1295655936 3:2429355008 4:3886967808 5:5668495360 Statistics: 1 4381594 D1=0.841838 D2=1.01787 D3+=1.21057 2 26800631 D1=0.836734 D2=1.01657 D3+=1.19437 3 69811700 D1=0.878562 D2=1.11227 D3+=1.27889 4 104063034 D1=0.931257 D2=1.23707 D3+=1.36664 5 119487533 D1=0.938146 D2=1.3058 D3+=1.41614 Memory estimate for binary LM: type MB probing 6752 assuming -p 1.5 probing 7917 assuming -r models -p 1.5 trie 3572 without quantization trie 2120 assuming -q 8 -b 8 quantization trie 3104 assuming -a 22 array pointer compression trie 1652 assuming -a 22 -q 8 -b 8 array pointer compression and quantization === 3/5 Calculating and sorting initial probabilities === Chain sizes: 1:52579128 2:428810096 3:1396234000 4:2497512816 5:3345650924 ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 #################################################################################################### === 4/5 Calculating and writing order-interpolated probabilities === Chain sizes: 1:52579128 2:428810096 3:1396234000 4:2497512816 5:3345650924 ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 #################################################################################################### === 5/5 Writing ARPA model === ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 ----------------------------------------------------------------------------------------------------Last input should have been poison. The program should end soon with an error. If it doesn't, there's a bug. terminate called after throwing an instance of 'util::FDException' what(): /home/students/s434708/kenlm/util/file.cc:228 in void util::WriteOrThrow(int, const void*, std::size_t) threw FDException because `ret < 1'. No space left on device in /home/students/s434708/Desktop/Modelowanie Języka/challenging-america-word-gap-prediction-kenlm/model.arpa while writing 8189 bytes /bin/bash: line 1: 26725 Aborted /home/students/s434708/kenlm/build/bin/lmplz -o 5 --skip_symbols < processed_train.txt > model.arpa
!$KENLM_BUILD_PATH/bin/build_binary model.arpa model.binary
Reading model.arpa ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 **************************************************************************************************** /home/students/s434708/kenlm/util/file.cc:86 in int util::CreateOrThrow(const char*) threw ErrnoException because `-1 == (ret = open(name, 0100 | 01000 | 02, 0400 | 0200 | (0400 >> 3) | ((0400 >> 3) >> 3)))'. No space left on device while creating model.binary Byte: 94 ERROR
!rm processed_train.txt
!rm model.arpa
Predykcje
import kenlm
test_str = 'really good'
model = kenlm.Model('model.binary')
print(model.score(test_str, bos = True, eos = True))
for i in model.full_scores(test_str):
print(i)