odashi

#include <chrono>
#include <cstdlib>
#include <iostream>
#include <random>
#include <thread>
#include <X11/Xlib.h>
#include <X11/Xutil.h>

using namespace std;

odashi

#!/usr/bin/env python3

import curses
from random import random
from time import sleep

def main(scr):
  curses.init_pair(1, curses.COLOR_BLACK, curses.COLOR_BLACK)
  curses.init_pair(2, curses.COLOR_BLACK, curses.COLOR_BLACK)
  curses.init_pair(3, curses.COLOR_WHITE, curses.COLOR_WHITE)

odashi

#!/usr/bin/env python3

import sys
from argparse import ArgumentParser
from collections import defaultdict

def parse_args():
  p = ArgumentParser('Converts word to integer using byte-pair encoding.')
  p.add_argument(
      '--input',

odashi

import builtins
import random

def word_list(filename):
  with open(filename) as fp:
    for l in fp:
      yield l.split()

def batch(generator, size):
  batch = []

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