odashi

#!/usr/bin/python3

import math
import random
import sys
from argparse import ArgumentParser
from collections import defaultdict
from util.functions import trace

def parse_args():

odashi

# usage (single sentence):
#   ref = ['This', 'is', 'a', 'pen', '.']
#   hyp = ['There', 'is', 'a', 'pen', '.']
#   stats = get_bleu_stats(ref, hyp)
#   bleu = calculate_bleu(stats) # => 0.668740
#
# usage (multiple sentences):
#   stats = defaultdict(int)
#   for ref, hyp in zip(refs, hyps):
#     for k, v in get_bleu_stats(ref, hyp).items():

odashi

import java.io.*;
import java.util.*;

import edu.stanford.nlp.ling.Word;
import edu.stanford.nlp.process.WordTokenFactory;
import edu.stanford.nlp.process.PTBTokenizer;

public class StanfordTokenizerRunner {
  private static List<String> tokenize(String text) {
    PTBTokenizer<Word> tokenizer = new PTBTokenizer<Word>(

odashi

27 垓 100,000,000,000,000,000,000
22 京 10,000,000,000,000,000
18 根 stick-to-itiveness
18 闇 black-marketeering
17 兆 1,000,000,000,000
17 悦 self-satisfaction
16 訛 mispronunciation
16 識 acquaintanceship
16 矩 perpendicularity
16 鎌 sickle-and-chain

odashi

#!/usr/bin/python3

import datetime
import sys
import math
import numpy as np
from argparse import ArgumentParser
from collections import defaultdict

from chainer import FunctionSet, Variable, functions, optimizers

odashi

#!/usr/bin/python3
# RNNLM trainer
# date: 2015-8-25
# author: @odashi_t


import datetime
import sys
import math
import numpy as np

odashi

«
♡
🐶
♡»
♡♡
🙇✨
😇💓
♡♡♡
☺️💓
🌟✨💫

odashi

#include <map>
#include <random>
#include <iostream>
#include <cmath>
#include <sys/time.h>

using namespace std;

double mytime() {
    timeval tv;

odashi

# debug.py
# coding: utf-8

import sys


DEBUG = False


WHITE = '\033[37m'

odashi

#!/path/to/python3
# -*- coding: utf-8 -*-

import cgi
import cgitb
import io
import json
import os
import sys