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3cdf7bc
1 Parent(s): 7a36f7c

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Browse files
.gitattributes CHANGED
@@ -51,3 +51,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.jpg filter=lfs diff=lfs merge=lfs -text
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  *.jpeg filter=lfs diff=lfs merge=lfs -text
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  *.webp filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.jpg filter=lfs diff=lfs merge=lfs -text
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  *.jpeg filter=lfs diff=lfs merge=lfs -text
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  *.webp filter=lfs diff=lfs merge=lfs -text
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+ *.csv filter=lfs diff=lfs merge=lfs -text
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+ *.jsonl filter=lfs diff=lfs merge=lfs -text
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+ *.json filter=lfs diff=lfs merge=lfs -text
create_multilingual_simCSE.py ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
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+ import jsonlines
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+ import argparse
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+ import pandas as pd
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+ import pprint
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+ from random import *
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+
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+ def main(args):
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+ mainDict = {}
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+ with jsonlines.open(args.norwegian_input_file) as reader:
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+ for obj in reader:
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+ #Check if the value already exists
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+ neutral = ""
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+ entailment = ""
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+ contradiction = ""
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+ prompt = ""
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+
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+ if mainDict.get(obj['promptID'], None):
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+ prompt = obj['sentence1']
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+ entailment = mainDict[obj['promptID']].get('entailment','')
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+ contradiction = mainDict[obj['promptID']].get('contradiction','')
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+ neutral = mainDict[obj['promptID']].get('neutral','')
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+
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+ if obj['gold_label'] == "neutral":
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+ neutral = obj['sentence2']
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+ elif obj['gold_label'] == "contradiction":
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+ contradiction = obj['sentence2']
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+ elif obj['gold_label'] == "entailment":
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+ entailment = obj['sentence2']
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+
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+ mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction}
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+
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+ myList = []
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+ for promptID in mainDict:
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+ myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']})
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+
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+ df = pd.DataFrame.from_records(myList)
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+
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+ #Drop empty
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+ df.replace("", float("NaN"), inplace=True)
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+ df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True)
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+
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+ #Get the english file
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+ english = pd.read_csv(args.english_input_file)
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+
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+ #Get the multilingual lookup file
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+ multi = pd.read_csv(args.multilingual_input_file, sep='\t')
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+ multi.columns=['id','english','norwegian']
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+ multi['english'] = multi['english'].str.strip()
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+ multi['norwegian'] = multi['norwegian'].str.strip()
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+
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+ #Create dictionary
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+ mydict = {}
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+ for index,row in multi.iterrows():
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+ mydict[row['norwegian']] = row['english']
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+
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+ merged = df.copy()
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+ for index, row in merged.iterrows():
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+ flip = randint(1,6)
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+ if flip == 3 or flip == 4 or flip == 5:
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+ merged.at[index, 'sent0'] = mydict.get(row['sent0'],row['sent0'])
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+
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+ if flip == 2 or flip == 4 or flip == 6:
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+ merged.at[index, 'sent1'] = mydict.get(row['sent1'],row['sent1'])
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+
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+ if flip == 1 or flip == 5 or flip == 6:
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+ merged.at[index,'hard_neg'] = mydict.get(row['hard_neg'],row['hard_neg'])
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+
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+
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+ combined = pd.concat([df, english, merged])
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+
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+ combined = combined.sample(frac=1).reset_index(drop=True)
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+
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+ #Save csv
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+ combined.to_csv(args.output_file, index=False)
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+
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+ if __name__ == '__main__':
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+ parser = argparse.ArgumentParser()
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+ parser.add_argument('--norwegian_input_file', help="Norwegian json file.", required=True)
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+ parser.add_argument('--english_input_file', help="English csv file.", required=True)
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+ parser.add_argument('--multilingual_input_file', help="Multilingual tsv file.", required=True)
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+ parser.add_argument('--output_file', help="Output file.", required=True)
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+
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+ args = parser.parse_args()
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+ main(args)
create_multilingual_small_simCSE.py ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import jsonlines
3
+ import argparse
4
+ import pandas as pd
5
+ import pprint
6
+ from random import *
7
+
8
+ def main(args):
9
+ mainDict = {}
10
+ with jsonlines.open(args.norwegian_input_file) as reader:
11
+ for obj in reader:
12
+ #Check if the value already exists
13
+ neutral = ""
14
+ entailment = ""
15
+ contradiction = ""
16
+ prompt = ""
17
+
18
+ if mainDict.get(obj['promptID'], None):
19
+ prompt = obj['sentence1']
20
+ entailment = mainDict[obj['promptID']].get('entailment','')
21
+ contradiction = mainDict[obj['promptID']].get('contradiction','')
22
+ neutral = mainDict[obj['promptID']].get('neutral','')
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+
24
+ if obj['gold_label'] == "neutral":
25
+ neutral = obj['sentence2']
26
+ elif obj['gold_label'] == "contradiction":
27
+ contradiction = obj['sentence2']
28
+ elif obj['gold_label'] == "entailment":
29
+ entailment = obj['sentence2']
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+
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+ mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction}
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+
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+ myList = []
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+ for promptID in mainDict:
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+ myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']})
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+
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+ df = pd.DataFrame.from_records(myList)
38
+
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+ #Drop empty
40
+ df.replace("", float("NaN"), inplace=True)
41
+ df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True)
42
+
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+ #Get the english file
44
+ english = pd.read_csv(args.english_input_file)
45
+
46
+ #Get the multilingual lookup file
47
+ #multi = pd.read_csv(args.multilingual_input_file, sep='\t')
48
+ #multi.columns=['id','english','norwegian']
49
+ #multi['english'] = multi['english'].str.strip()
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+ #multi['norwegian'] = multi['norwegian'].str.strip()
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+
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+ #Create dictionary
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+ #mydict = {}
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+ #for index,row in multi.iterrows():
55
+ # mydict[row['norwegian']] = row['english']
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+
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+ #merged = df.copy()
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+ #for index, row in merged.iterrows():
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+ # flip = randint(1,6)
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+ # if flip == 3 or flip == 4 or flip == 5:
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+ # merged.at[index, 'sent0'] = mydict.get(row['sent0'],row['sent0'])
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+ #
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+ # if flip == 2 or flip == 4 or flip == 6:
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+ # merged.at[index, 'sent1'] = mydict.get(row['sent1'],row['sent1'])
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+ #
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+ # if flip == 1 or flip == 5 or flip == 6:
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+ # merged.at[index,'hard_neg'] = mydict.get(row['hard_neg'],row['hard_neg'])
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+
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+
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+ combined = pd.concat([df, english])
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+
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+ combined = combined.sample(frac=1).reset_index(drop=True)
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+
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+ #Save csv
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+ combined.to_csv(args.output_file, index=False)
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+
77
+ if __name__ == '__main__':
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+ parser = argparse.ArgumentParser()
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+ parser.add_argument('--norwegian_input_file', help="Norwegian json file.", required=True)
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+ parser.add_argument('--english_input_file', help="English csv file.", required=True)
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+ parser.add_argument('--output_file', help="Output file.", required=True)
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+
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+ args = parser.parse_args()
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+ main(args)
create_simCSE.py ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import jsonlines
3
+ import argparse
4
+ import pandas as pd
5
+ import pprint
6
+
7
+ def main(args):
8
+ mainDict = {}
9
+ with jsonlines.open(args.input_file) as reader:
10
+ for obj in reader:
11
+ #Check if the value already exists
12
+ neutral = ""
13
+ entailment = ""
14
+ contradiction = ""
15
+ prompt = ""
16
+
17
+ if mainDict.get(obj['promptID'], None):
18
+ prompt = obj['sentence1']
19
+ entailment = mainDict[obj['promptID']].get('entailment','')
20
+ contradiction = mainDict[obj['promptID']].get('contradiction','')
21
+ neutral = mainDict[obj['promptID']].get('neutral','')
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+
23
+ if obj['gold_label'] == "neutral":
24
+ neutral = obj['sentence2']
25
+ elif obj['gold_label'] == "contradiction":
26
+ contradiction = obj['sentence2']
27
+ elif obj['gold_label'] == "entailment":
28
+ entailment = obj['sentence2']
29
+
30
+ mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction}
31
+
32
+ myList = []
33
+ for promptID in mainDict:
34
+ myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']})
35
+
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+ df = pd.DataFrame.from_records(myList)
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+
38
+ #Drop empty
39
+ df.replace("", float("NaN"), inplace=True)
40
+ df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True)
41
+
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+ #Save csv
43
+ df.to_csv(args.output_file, index=False)
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+
45
+ if __name__ == '__main__':
46
+ parser = argparse.ArgumentParser()
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+ parser.add_argument('--input_file', help="Input file.", required=True)
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+ parser.add_argument('--output_file', help="Output file.", required=True)
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+
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+ args = parser.parse_args()
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+ main(args)
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