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Hotfix/fixed some tests and refactored number_to_word.py #483

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Merged
merged 7 commits into from
Jun 2, 2023
Merged

Hotfix/fixed some tests and refactored number_to_word.py #483

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a8b4b24
refactored number_to_word.py
RakshitKhajuria Jun 1, 2023
6a789a8
fixes
RakshitKhajuria Jun 1, 2023
d8303f4
Update robustness.py
RakshitKhajuria Jun 2, 2023
166cbfe
fix conflict
RakshitKhajuria Jun 2, 2023
4fd91d5
Merge branch 'hotfix/fixed-number-to-word-issue-QA' of https://github…
RakshitKhajuria Jun 2, 2023
56ab782
fix
RakshitKhajuria Jun 2, 2023
bced588
fixes
RakshitKhajuria Jun 2, 2023
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15 changes: 6 additions & 9 deletions nlptest/transform/robustness.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
from nlptest.modelhandler.modelhandler import ModelFactory
from .utils import (CONTRACTION_MAP, TYPO_FREQUENCY, default_user_prompt ,ocr_typo_dict,abbreviation_dict,Slang_Nouns, Slang_Adverbs, Slang_Adjectives)
from ..utils.custom_types import Sample, Span, Transformation
from ..utils.number_to_word import engine
from ..utils.number_to_word import ConvertNumberToWord
from typing import List
import string
from ..utils.SoundsLikeFunctions import Search
Expand Down Expand Up @@ -599,7 +599,7 @@ def search_contraction(text):

class NumberToWord(BaseRobustness):
alias_name = "number_to_word"
infEng = engine()
num = ConvertNumberToWord()

@staticmethod
def transform(sample_list: List[Sample]) -> List[Sample]:
Expand All @@ -620,8 +620,7 @@ def convert_numbers(regex, text):

for match in re.finditer(regex, text):
token = match.group()
words = NumberToWord.infEng.number_to_words(
token, wantlist=True)
words = NumberToWord.num.number_to_words(token, wantlist=True)
new_words_len = len(' '.join(words))
trans.append(text[start_offset:match.start()])
trans.append(' '.join(words))
Expand All @@ -630,20 +629,18 @@ def convert_numbers(regex, text):
Transformation(
original_span=Span(
start=match.start(), end=match.end(), word=token),
new_span=Span(start=match.start(), end=match.start(
)+new_words_len, word=' '.join(words)),
new_span=Span(start=match.start(), end=match.start()+new_words_len, word=' '.join(words)),
ignore=False
)
)

trans.append(text[start_offset:])
results.append(''.join(trans))

return ''.join(results), transformations

for idx, sample in enumerate(sample_list):
if isinstance(sample, str):
sample_list[idx] = convert_numbers(r'(?<!\S)(\d+(\.\d+)?)(?=(\s|\n|$))', sample)
sample_list[idx], _ = convert_numbers(r'(?<!\S)(\d+(\.\d+)?)(?=(\s|\n|$))', sample)
else:
sample.test_case, transformations = convert_numbers(r'(?<!\S)(\d+(\.\d+)?)(?=(\s|\n|$))', sample.original)
if sample.task in ("ner", "text-classification"):
Expand Down
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