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# Solves the exact evaluation of any tic tac toe position | |
import copy | |
# Square definitions | |
X_SQUARE = 'X' | |
O_SQUARE = 'O' | |
BLANK = '_' | |
# Evaluation definitions |
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,idx,f_name,txt | |
0,0,0147NewsData.txt,"하필 지방선거 전날 북미회담… 야당엔 초대형 악재? 한국당 “의도 개입된 날짜 선정” 민주당 “평화 여는 역사적 계기” | |
6·13 지방선거 전날인 다음 달 12일에 북·미 정상회담 개최가 확정되자 여야의 표정은 크게 엇갈렸다. 더불어민주당은 북·미 정상회담이 지방선거에서 호재로 작용할 것이라는 기대감을 감추지 않았다. 자유한국당과 바른미래당은 국제 이슈가 지방선거에 큰 영향을 주지 않을 것이라고 평가절하했다. 특히 한국당은 겉으로는 “미·북 정상회담의 성공을 기대한다”고 밝혔으나 당내에서는 “왜 하필 그날 열리는 것이냐”는 볼멘소리가 흘러나왔다. | |
추미애 민주당 대표는 11일 국회에서 열린 최고위원회의에서 “북·미 정상회담은 한·미 정상회담에서 열리기 시작한 평화의 문이 활짝 열리는 역사적 계기가 될 것”이라고 의미를 부여했다. | |
민주당은 북·미 정상회담에서 가시적 성과가 나온다면 민주당의 상승세가 더욱 거세질 것이라고 전망했다. 민주당 핵심 관계자는 “한반도 평화 모드에 대한 기대감이 이미 당 지지율에 반영됐다고 봐야 한다”면서도 “회담 성과가 예상을 뛰어넘을 경우 지방선거에서 엄청난 파괴력을 발휘할 것”이라고 말했다. 하지만 회담의 결과가 기대에 못 미칠 경우 역풍이 불 수 있다는 걱정도 없지 않다. |
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from transformers import BertTokenizer, BertForNextSentencePrediction | |
from torch.nn import functional as F | |
BATCH = [ | |
("I understand Tesla's vision.", "Haha, that's a nice [MASK]."), # pun? | |
("the man went to [MASK] store", "he bought a gallon [MASK] milk"), # is next | |
("the man [MASK] to the store", "penguin [MASK] are flight ##less birds") # not next | |
] | |
BERT_MODEL = "bert-base-uncased" |
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🌞 Morning 79 commits ███▌░░░░░░░░░░░░░░░░░ 17.1% | |
🌆 Daytime 166 commits ███████▌░░░░░░░░░░░░░ 35.9% | |
🌃 Evening 174 commits ███████▉░░░░░░░░░░░░░ 37.6% | |
🌙 Night 44 commits █▉░░░░░░░░░░░░░░░░░░░ 9.5% |
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# coding=utf-8 | |
"""TODO: Add a description here.""" | |
import csv | |
import json | |
import os | |
import datasets |
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import sys | |
import warnings | |
import numpy as np | |
import pandas as pd | |
import statsmodels.api as sm | |
from scipy.optimize import brute | |
from statsmodels.tsa.arima.model import ARIMA | |
warnings.simplefilter("ignore", category='UserWarning') |
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from datetime import datetime | |
import multiprocessing | |
from datetime import timedelta | |
from functools import partial | |
from multiprocessing import Manager | |
import pandas as pd | |
from LostChapter.secrets import controller | |
from LostChapter.utils.ARIMAPredictor import get_arima_predictions |