-
Notifications
You must be signed in to change notification settings - Fork 5
/
Copy pathTweetText.py
68 lines (36 loc) · 1.21 KB
/
TweetText.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import pandas as pd
import s3fs
from smart_open import open
import boto3
from io import StringIO # python3; python2: BytesIO
from boto3.s3.transfer import TransferConfig
import metrics
import torch
from transformers import *
import numpy as np
import ast
import time
# In[ ]:
column_of_interest = ["text_ tokens"]
train_set = pd.read_csv('s3://recsys-challenge-2020/train_set.csv', encoding="utf-8",
usecols= [1])
val_set = pd.read_csv('s3://recsys-challenge-2020/val_set.csv', encoding="utf-8",
usecols= [1])
tokenizer = BertTokenizer.from_pretrained('bert-base-multilingual-cased', do_lower_case=False)
# In[ ]:
train_set.head()
# In[ ]:
def calculate_text(row):
tweet_tokens = tokenizer.decode(list(map(int, row.split('\t'))))
return tweet_tokens
# In[ ]:
train_set['user_text'] = train_set['text_ tokens'].apply(lambda x: calculate_text(x))
# In[ ]:
val_set['user_text'] = val_set['text_ tokens'].apply(lambda x: calculate_text(x))
# In[ ]:
train_set.to_csv('s3://recsys-challenge-2020/train_set_text.csv', index = False)
# In[ ]:
val_set.to_csv('s3://recsys-challenge-2020/val_set_text.csv', index = False)